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Ushimaru Y, Katoh T, Sasaki M, Hata T, Hosaka M, Eguchi H, Doki Y, Nakajima K. Development of medical devices driven by academia-industry collaboration: An internal audit. Surgery 2025; 181:109289. [PMID: 40054052 DOI: 10.1016/j.surg.2025.109289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2024] [Revised: 01/20/2025] [Accepted: 02/02/2025] [Indexed: 04/30/2025]
Abstract
BACKGROUND Rapid and efficient processes are essential for medical device research and development. To address this need, we established an open innovation research and development platform involving clinicians, manufacturers, sales companies, and experts in intellectual property and regulatory, aiming to develop new medical devices for minimally invasive treatment. The purpose of this study is to retrospectively and internally evaluate the research and development activities and outcomes of this platform to identify factors contributing to successful development of medical devices. METHODS A retrospective analysis of our team was conducted, focusing on successful device development, device classification, development duration, targeted medical areas, intellectual property rights, and manufacturer involvement. The study also evaluated external funding, academic publications, and international market expansion. Data were extracted from our team's project database and analyzed using descriptive statistical methods. RESULTS The platform facilitated the development of 28 medical devices, achieving a successful device development rate of 50%. These devices primarily targeted endoscopy (48.2%) and laparoscopy (25%),with an average development of 36 months. The intellectual property acquisition rate was 50%, including patents (39.3%) and trademarks (44.6%). Collaboration with sales companies and manufacturers was high at 82.1% and 71.4%, respectively. External funding supported 44.6% of projects, and academic publications were associated with 32.1%. In addition, 12.5% of the projects achieved international market expansion. Key success factors included intellectual property acquisition (P < .001), external funding (P = .003), academic publications (P = .003), and involvement of sales companies in research and development (P = .03). CONCLUSION Our team has shown successful in research and development through collaborative efforts across academia, industry, and government. It highlights the importance of open innovation and interdisciplinary collaboration in addressing global health care challenges.
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Affiliation(s)
- Yuki Ushimaru
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan; Department of Gastroenterological Surgery, Osaka International Cancer Institute, Osaka, Japan
| | - Takamitsu Katoh
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan
| | - Motoki Sasaki
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan
| | - Taishi Hata
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan
| | - Makoto Hosaka
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hidetoshi Eguchi
- Department of Gastroenterological Surgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuichiro Doki
- Department of Gastroenterological Surgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kiyokazu Nakajima
- Department of Next Generation Endoscopic Intervention (Project ENGINE), Osaka University Graduate School of Medicine, Osaka, Japan; Department of Gastroenterological Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.
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Algaissi A, Khan E, Tabassum H, Samreen S, Khamjan NA, Lohani M, Khan S, Kameli N, Madkhali F, Ahmad IZ. Campesterol and dithymoquinone as a potent inhibitors of SARS cov-2 main proteases-promising drug candidates for targeting its novel variants. J Biomol Struct Dyn 2025; 43:2534-2548. [PMID: 38288958 DOI: 10.1080/07391102.2023.2301684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 09/13/2023] [Indexed: 02/16/2024]
Abstract
The sudden outbreak of the COVID-19 pandemic has currently taken approximately 2.4 million lives, with no specific medication and fast-tracked tested vaccines for prevention. These vaccines have their own adverse effects, which have severely affected the global healthcare system. The discovery of the main protease structure of coronavirus (Mpro/Clpro) has resulted in the identification of compounds having antiviral potential, especially from the herbal system. In this study, the computer-associated drug design tools were utilised to analyze the reported phytoconstituents of Nigella sativa for their antiviral activity against the main protease. Fifty-eight compounds were subjected to pharmacological parameter analysis to determine their lead likeness in comparison to the standard drugs (chloroquine and nirmatrelvir) used in the treatment of SARS-CoV-2. Nearly 31 compounds were docked against five different SARS-CoV-2 main proteases, and all compounds showed better binding affinity and inhibition constant against the proteases. However, dithymoquinone and campesterol displayed the best binding scores and hence were further subjected to dynamics and MMPBSA study for 100 ns. The stability analysis shows that dithymoquinone and campesterol show less variation in fluctuation in residues compared to standard complexes. Moreover, dithymoquinone exhibited higher binding affinity and favorable interaction followed by campesterol as compared to the standard drug. The in silico computational analysis provides a promising hit for regulating the main proteases activity.
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Affiliation(s)
- Abdullah Algaissi
- Department of Medical Laboratories Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
- Emerging and Epidemic Infectious Diseases Research Unit, Medical Research Center, Jazan University, Jazan, Saudi Arabia
| | - Elhan Khan
- Natural Products Laboratory, Department of Bioengineering, Integral University, Lucknow, Uttar Pradesh, India
| | - Heena Tabassum
- Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Sadiyah Samreen
- Natural Products Laboratory, Department of Bioengineering, Integral University, Lucknow, Uttar Pradesh, India
| | - Nizar A Khamjan
- Department of Medical Laboratories Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Mohtashim Lohani
- Medical Research Centre, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Saif Khan
- Department of Basic Dental and Medical Sciences, College of Dentistry, Ha'il University, Ha'il, Saudi Arabia
| | - Nader Kameli
- Department of Medical Laboratories Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Faisal Madkhali
- Department of Medical Laboratories Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Iffat Zareen Ahmad
- Natural Products Laboratory, Department of Bioengineering, Integral University, Lucknow, Uttar Pradesh, India
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Karimi-Sani I, Sharifi M, Abolpour N, Lotfi M, Atapour A, Takhshid MA, Sahebkar A. Drug repositioning for Parkinson's disease: An emphasis on artificial intelligence approaches. Ageing Res Rev 2025; 104:102651. [PMID: 39755176 DOI: 10.1016/j.arr.2024.102651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Revised: 12/09/2024] [Accepted: 12/26/2024] [Indexed: 01/06/2025]
Abstract
Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is the second most common NDD worldwide which affects approximately 1-2 percent of people over 65 years. It is an attractive pursuit for artificial intelligence (AI) to contribute to and evolve PD treatments through drug repositioning by repurposing existing drugs, shelved drugs, or even candidates that do not meet the criteria for clinical trials. A search was conducted in three databases Web of Science, Scopus, and PubMed. We reviewed the data related to the last years (1975-present) to identify those drugs currently being proposed for repositioning in PD. Moreover, we reviewed the present status of the computational approach, including AI/Machine Learning (AI/ML)-powered pharmaceutical discovery efforts and their implementation in PD treatment. It was found that the number of drug repositioning studies for PD has increased recently. Repositioning of drugs in PD is taking off, and scientific communities are increasingly interested in communicating its results and finding effective treatment alternatives for PD. A better chance of success in PD drug discovery has been made possible due to AI/ML algorithm advancements. In addition to the experimentation stage of drug discovery, it is also important to leverage AI in the planning stage of clinical trials to make them more effective. New AI-based models or solutions that increase the success rate of drug development are greatly needed.
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Affiliation(s)
- Iman Karimi-Sani
- Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Mehrdad Sharifi
- Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran; Artificial Intelligence Department, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Nahid Abolpour
- Artificial Intelligence Department, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Mehrzad Lotfi
- Artificial Intelligence Department, Shiraz University of Medical Sciences, Shiraz, Iran; Medical Imaging Research Center, Department of Radiology, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Amir Atapour
- Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Mohammad-Ali Takhshid
- Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran; Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Amirhossein Sahebkar
- Center for Global Health Research, Saveetha Medical College & Hospitals, Saveetha Institute of Medical & Technical Sciences, Saveetha University, Chennai, India; Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran; Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
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Kawata Y, Ichimaru T, Kogami M, Kodama K, Miyashita S, Sengoku S. Multi-layer platform coordination for open innovation in oligonucleotide therapeutics. Drug Discov Today 2025; 30:104288. [PMID: 39793651 DOI: 10.1016/j.drudis.2025.104288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2024] [Revised: 12/18/2024] [Accepted: 01/06/2025] [Indexed: 01/13/2025]
Abstract
As technology evolves and medical needs diversify, the pharmaceutical industry must accelerate its openness. This study analysed inter-organizational alliances in R&D for the new modality of oligonucleotide therapeutics to explore the requirements for establishing new markets. The results confirmed that the market has developed in stages, employing open innovation for different purposes according to technological progress. At each stage, it was crucial to form platforms among biotech companies on the drug discovery side, among pharmaceutical companies on the regulatory side and contract development manufacturing organizations (CDMOs) on the manufacturing side. These findings clarify the dynamics of open innovation in the biopharmaceutical industry and provide strategic implications for sustainable value creation in drug R&D.
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Affiliation(s)
- Yayoi Kawata
- Department of Innovation Science, School of Environment and Society, Institute of Science Tokyo, Japan
| | - Taisuke Ichimaru
- Department of Technology and Innovation Management, School of Environment and Society, Institute of Science Tokyo, Japan
| | - Masakazu Kogami
- Department of Technology and Innovation Management, School of Environment and Society, Institute of Science Tokyo, Japan
| | - Kota Kodama
- Medical Data Science Laboratory, Hoshi University, Japan
| | - Shuto Miyashita
- Department of Innovation Science, School of Environment and Society, Institute of Science Tokyo, Japan; Department of Technology and Innovation Management, School of Environment and Society, Institute of Science Tokyo, Japan
| | - Shintaro Sengoku
- Department of Innovation Science, School of Environment and Society, Institute of Science Tokyo, Japan; Department of Technology and Innovation Management, School of Environment and Society, Institute of Science Tokyo, Japan.
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Luo C, Zhang Y, Feng Q, Yao K, Zheng L, Yang Y, Zheng W, Li F, Lv Y, Cai Y. Novel candidate plasma proteins for the pathogenesis and treatment of atopic dermatitis revealed by proteome-wide association study. Sci Rep 2024; 14:30096. [PMID: 39627291 PMCID: PMC11615279 DOI: 10.1038/s41598-024-79906-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 11/13/2024] [Indexed: 12/06/2024] Open
Abstract
Atopic dermatitis (AD) is an immune-related skin disease with a genetic background. Numerous loci have been identified associated with AD to better comprehend its complicated genetic mechanisms by genome‑wide association studies (GWASs). However, current studies reveal the underlying mechanisms of these loci in the pathogenesis of AD inadequately. Therefore, we integrated the GWAS statistics of AD with plasma proteins to explore candidate proteins correlated with the pathogenesis of AD based on protein-centered omics studies. Herein, we adopted the updated AD GWAS statistics (N = 864,982) and the dataset of plasma protein quantitative trait loci (pQTLs), comprising 1,348 proteins from individuals of European descent. We first conducted the AD-related proteome-wide association studies (PWASs) (N = 7,213) by integrating pQTLs with the AD GWAS statistics and identified twenty-six significant plasma proteins by PWAS (FDR < 0.05). Then, the potential causal proteins of AD were identified via Mendelian randomization (MR), and seventeen causal proteins of AD were discovered afterward. Following this, Bayesian colocalization analysis was then utilized to explore proteins sharing the same causal variants. Five causal proteins strongly associated with the pathogenesis of AD were eventually pinpointed. Finally, we discovered drugs that could be repurposed for AD with the plasma proteins that might contribute to the pathogenesis of AD in the Drug Gene Interaction Database.
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Affiliation(s)
- Chen Luo
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - YaJing Zhang
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - QiFan Feng
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - KaiXin Yao
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - LeiLei Zheng
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - Ye Yang
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
- Department of Anesthesiology, Shanxi Hospital Affiliated to Cancer Hospital, Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China
| | - WenXin Zheng
- Department of Biochemistry and Molecular Biology, Basic Medical College, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan, China
| | - Feng Li
- Central Laboratory, Shanxi Hospital Affiliated to Cancer Hospital, Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
| | - YongQiang Lv
- Department of Operation Management, Shanxi Hospital Affiliated to Cancer Hospital, Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
| | - Yue Cai
- Department of Anesthesiology, Shanxi Hospital Affiliated to Cancer Hospital, Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
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Wang H, Song C, Shin K. Does the impact of open innovation depend on contextual factors? A case of the Korean biopharmaceutical industry. PLoS One 2024; 19:e0310311. [PMID: 39561172 PMCID: PMC11575768 DOI: 10.1371/journal.pone.0310311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 08/24/2024] [Indexed: 11/21/2024] Open
Abstract
Investments in the strategic development of the biopharmaceutical industry are increasing in both developed and developing countries. The biopharmaceutical industry is a technology-intensive industry where securing original technology and intellectual property rights is important. The role of open innovation is becoming more important due to the enormous research and development (R&D) funds and long development period in the early development process, and open innovation (OI) is becoming more important in the corporate world. Many empirical studies have been conducted on the impact on performance. However, the contextual factors that affect the relationship between OI activities and innovation performance have received relatively little attention, and studies from the perspective of developing countries catching up with developed countries are even rarer. Accordingly, this study examined the moderating effects (government R&D support, absorptive capacity, and alliance management capacity) that affect open innovation and innovation performance in the biopharmaceutical industry using data from Korea, one of the most representative latecomer countries in the biopharmaceutical industry. The basic information, OI activities, and patent achievements of Korean biopharmaceutical firms were collected and organized into a database. Samples with missing or incorrect information were excluded, and 527 firms were analyzed. Negative binomial regression analysis was performed considering the characteristics of patent performance, which is the dependent variable, and a time lag of one to two years was assumed considering the time required to generate results. OI in the form of technological cooperation, rather than technology purchasing, has a positive effect on patent performance. Meanwhile, the greater the absorptive capacity and government R&D support, the greater the positive impact of technological cooperation on patent performance. Conversely, the greater the alliance management capacity, the greater the positive impact of technological cooperation. These results indicate that the impact of OI activities on technological innovation performance may vary depending on context.
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Affiliation(s)
- HyeJoo Wang
- Department of Biomedical Convergence, Chungbuk National University, Cheongju, Chungcheongbuk-do, Republic of Korea
| | - Changhyeon Song
- Office of S&T Policy Planning, Korea Institute of Science & Technology Evaluation and Planning, Eumseong, Chungcheongbuk-do, Republic of Korea
| | - Kwangsoo Shin
- Graduate School of Public Health and Healthcare Management/Catholic Institute for Public Health and Healthcare Management, Songeui Medical Campus, The Catholic University of Korea, Seoul, Korea
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Bhushan A, Misra P. Economics of Antibody Drug Conjugates (ADCs): Innovation, Investment and Market Dynamics. Curr Oncol Rep 2024; 26:1224-1235. [PMID: 39037635 DOI: 10.1007/s11912-024-01582-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2024] [Indexed: 07/23/2024]
Abstract
PURPOSE OF REVIEW This review aims to explore the intricate interplay between scientific advancements and economic considerations in the development, production, and commercialization of Antibody Drug Conjugates (ADCs). The focus is on understanding the challenges and opportunities at this unique intersection, highlighting how scientific innovation and economic dynamics mutually influence the trajectory of ADCs in the pharmaceutical landscape. RECENT FINDINGS There has been a significant increase in interest and investment in the development of ADCs. Initially focused on hematological malignancies, ADCs are now being researched for use in treating solid tumors as well. Pharmaceutical companies are heavily investing to broaden the range of indications for which ADCs can be effective. According to a report from the end of 2023, the global ADCs market grew from USD 1.4 billion in 2016 to USD 11.3 billion in 2023, with projections estimating a value of USD 23.9 billion by 2032, growing at a CAGR of 10.7%. ADCs represent a promising class of biopharmaceuticals in oncology, with expanding applications beyond hematological malignancies to solid tumors. The significant growth in the ADC market underscores the impact of scientific and economic factors on their development. This review provides valuable insights into how these factors drive innovation and commercialization, shaping the future of ADCs in cancer treatment.
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Affiliation(s)
- Arya Bhushan
- Chembila Consulting, Nashua, New Hampshire, USA
- Yale University, Undergraduate Student, New Haven, CT, USA
| | - Preeti Misra
- Chembila Consulting, Nashua, New Hampshire, USA.
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Mubarak Z, Abbas N, Hashmi FK, Shahbaz H, Bukhari NI. Industrial prospects on regulatory gaps and barriers in pharmaceutical exports and their counteraction: Local experiential with global implication. PLoS One 2024; 19:e0305989. [PMID: 39028685 PMCID: PMC11259304 DOI: 10.1371/journal.pone.0305989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/07/2024] [Indexed: 07/21/2024] Open
Abstract
BACKGROUND The pharmaceutical sector in Pakistan has grown over a period with export potential, however, there are certain barriers in the framework that regulate the growth and export of domestically manufactured pharmaceuticals. The purpose of this study was to highlight the current challenges that hinder the export of pharmaceuticals, especially to the countries with stringent regulatory authorities (SRA), as perceived by the domestic pharmaceutical industry experts, and to highlight the facilitators that may help to resolve the identified challenges. METHODS In a qualitative study, the data were collected from the consented experts from the pharmaceutical industries in Lahore, Karachi, Peshawar, and Quetta. Industrial experts with a minimum of 10 years of experience and who were serving at managerial levels or above were recruited through purposive sampling. The semi-structured interviews were conducted for the collection of data from industrial experts. Thematic content analysis was applied to conclude the data. RESULTS Data analysis generated 4 themes and 16 codes. The export of pharmaceuticals, despite having greater potential was regarded as poor, which was attributed to the following: (a) inadequate industrial research and development, particularly on new molecules (b) non-compliance with the cGMP standards, (c) absence of high-tech equipment, (d) unwillingness of the pharmaceutical companies for bioequivalence studies on their generics, (e) unavailability of locally manufactured active pharmaceutical ingredients, (f) disruption in the supply of imported raw material, (g) poor international market perception about local pharmaceutical products and (h) lack of support from regulatory in process expedition. The respondents also suggested the measures for overcoming the above challenges to boost the export of domestic pharmaceuticals and expand their international market share in countries with SRA. CONCLUSION Export from Pakistan to the SRA countries can be enhanced with mandatory bioequivalence studies during generic registration. The pharmaceuticals export could effectively contribute to the national economy.
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Affiliation(s)
- Zobia Mubarak
- Punjab University College of Pharmacy, University of the Punjab, Lahore, Pakistan
| | - Nasir Abbas
- Punjab University College of Pharmacy, University of the Punjab, Lahore, Pakistan
| | | | - Hina Shahbaz
- Punjab University College of Pharmacy, University of the Punjab, Lahore, Pakistan
| | - Nadeem Irfan Bukhari
- Punjab University College of Pharmacy, University of the Punjab, Lahore, Pakistan
- Faculty of Pharmaceutical Sciences, Qarshi University, Lahore, Pakistan
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Abi Sleiman M, Younes M, Hajj R, Salameh T, Abi Rached S, Abi Younes R, Daoud L, Doumiati JL, Frem F, Ishak R, Medawar C, Naim HY, Rizk S. Urtica dioica: Anticancer Properties and Other Systemic Health Benefits from In Vitro to Clinical Trials. Int J Mol Sci 2024; 25:7501. [PMID: 39000608 PMCID: PMC11242153 DOI: 10.3390/ijms25137501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 07/05/2024] [Accepted: 07/05/2024] [Indexed: 07/16/2024] Open
Abstract
While conventional medicine has advanced in recent years, there are still concerns about its potential adverse reactions. The ethnopharmacological knowledge established over many centuries and the existence of a variety of metabolites have made medicinal plants, such as the stinging nettle plant, an invaluable resource for treating a wide range of health conditions, considering its minimal adverse effects on human health. The aim of this review is to highlight the therapeutic benefits and biological activities of the edible Urtica dioica (UD) plant with an emphasis on its selective chemo-preventive properties against various types of cancer, whereby we decipher the mechanism of action of UD on various cancers including prostate, breast, leukemia, and colon in addition to evaluating its antidiabetic, microbial, and inflammatory properties. We further highlight the systemic protective effects of UD on the liver, reproductive, excretory, cardiovascular, nervous, and digestive systems. We present a critical assessment of the results obtained from in vitro and in vivo studies as well as clinical trials to highlight the gaps that require further exploration for future prospective studies.
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Affiliation(s)
- Marc Abi Sleiman
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Maria Younes
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Roy Hajj
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Tommy Salameh
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Samir Abi Rached
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Rimane Abi Younes
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Lynn Daoud
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Jean Louis Doumiati
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Francesca Frem
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Ramza Ishak
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Christopher Medawar
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
| | - Hassan Y Naim
- Department of Biochemistry, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Sandra Rizk
- Department of Natural Sciences, Lebanese American University, Byblos P.O. Box 36, Lebanon
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Peters U, Tomlinson I. Utilizing Human Genetics to Develop Chemoprevention for Cancer-Too Good an Opportunity to be Missed. Cancer Prev Res (Phila) 2024; 17:7-12. [PMID: 38173394 DOI: 10.1158/1940-6207.capr-22-0523] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/20/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024]
Abstract
Large-scale genetic studies are reliably identifying many risk factors for disease in the general population. Several of these genetic risk factors encode potential drug targets, and genetics has already helped to introduce targeted agents for some diseases, an example being lipid-lowering drugs to reduce the incidence of cardiovascular disease. Multiple drugs have been developed to treat cancers based on somatic mutations and genomics, but in stark contrast, there seems to be a reluctance to use germline genetic data to develop drugs to prevent malignancy, despite the large numbers of people who could benefit, the potential for lowering cancer rates, and the widespread current use of non-pharmaceutical measures to reduce cancer risk factors such as tobacco, alcohol, and infectious diseases. We argue that concerted efforts for cancer prevention based on genetics, including genes influenced by common polymorphisms that modulate cancer risk, are urgently needed. There are enormous, yet underutilized, opportunities to develop novel targeted agents for chemoprevention of cancer based on human germline genetics. Such efforts are likely to require the support of a dedicated funding program by national and international agencies. See related commentary by Winham and Sherman, p. 13.
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Affiliation(s)
- Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle, Washington
| | - Ian Tomlinson
- Department of Oncology, University of Oxford, Oxford, United Kingdom
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Rodríguez-Molinero A, Pérez-López C, Salazar González JL, Garcia-Lerma E, Álvarez-García JA, Soria Morillo LM, Salas Fernández T. Drug Repurposing for Cancers With Limited Survival: Protocol for a Retrospective Cohort Study. JMIR Res Protoc 2023; 12:e48925. [PMID: 37962929 PMCID: PMC10686206 DOI: 10.2196/48925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/20/2023] [Accepted: 10/10/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Only 5% of the molecules tested in oncology phase 1 trials reach the market after an average of 7.5 years of waiting and at a cost of tens of millions of dollars. To reduce the cost and shorten the time of discovery of new treatments, "drug repurposing" (research with molecules already approved for another indication) and the use of secondary data (not collected for the purpose of research) have been proposed. Due to advances in informatics in clinical care, secondary data can, in some cases, be of equal quality to primary data generated through prospective studies. OBJECTIVE The objective of this study is to identify drugs currently marketed for other indications that may have an effect on the prognosis of patients with cancer. METHODS We plan to monitor a cohort of patients with high-lethality cancers treated in the public health system of Catalonia between 2006 and 2012, retrospectively, for survival for 5 years after diagnosis or until death. A control cohort, comprising people without cancer, will also be retrospectively monitored for 5 years. The following study variables will be extracted from different population databases: type of cancer (patients with cancer cohort), date and cause of death, pharmacological treatment, sex, age, and place of residence. During the first stage of statistical analysis of the patients with cancer cohort, the drugs consumed by the long-term survivors (alive at 5 years) will be compared with those consumed by nonsurvivors. In the second stage, the survival associated with the consumption of each relevant drug will be analyzed. For the analyses, groups will be matched for potentially confounding variables, and multivariate analyses will be performed to adjust for residual confounding variables if necessary. The control cohort will be used to verify whether the associations found are exclusive to patients with cancer or whether they also occur in patients without cancer. RESULTS We anticipate discovering multiple significant associations between commonly used drugs and the survival outcomes of patients with cancer. We expect to publish the initial results in the first half of 2024. CONCLUSIONS This retrospective study may identify several commonly used drugs as candidates for repurposing in the treatment of various cancers. All analyses are considered exploratory; therefore, the results will have to be confirmed in subsequent clinical trials. However, the results of this study may accelerate drug discovery in oncology. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/48925.
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Affiliation(s)
| | - Carlos Pérez-López
- Àrea de Recerca, Consorci Sanitari de l'Alt Penedès i Garraf, Vilafranca del Penedès, Spain
| | | | - Esther Garcia-Lerma
- Biostatistics Unit, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | | | - Luis M Soria Morillo
- Dpto de Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Sevilla, Spain
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12
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Bieske L, Zinner M, Dahlhausen F, Trübel H. Trends, challenges, and success factors in pharmaceutical portfolio management: Cognitive biases in decision-making and their mitigating measures. Drug Discov Today 2023; 28:103734. [PMID: 37572999 DOI: 10.1016/j.drudis.2023.103734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 07/29/2023] [Accepted: 08/05/2023] [Indexed: 08/14/2023]
Abstract
Effective portfolio management is crucial for innovation and sustaining revenue in pharmaceutical companies. This article holistically reviews trends, challenges, and approaches to pharmaceutical portfolio management and focuses, in particular, on cognitive biases in portfolio decision-making. Portfolio managers strongly rely on external innovation and face increasing competitive pressure and portfolio complexity. The ability to address biases and make robust decisions remains a challenge. Portfolio management practitioners most commonly face confirmation bias, champion bias, or misaligned incentives, which they seek to mitigate through expert input, team diversity, and rewarding truth-seeking. Ultimately, highest-quality portfolio management decision-making could be enabled by three factors: high-quality data, structured review processes, and comprehensive mitigating measures against biases in decision-making.
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Affiliation(s)
- Linn Bieske
- Faculty of Health, Witten/Herdecke University, Germany
| | | | | | - Hubert Trübel
- Faculty of Health, Witten/Herdecke University, Germany; The Knowledge House GmbH, Düsseldorf, Germany.
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13
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Rake B, Sengupta K, Lewin L, Sandström A, McKelvey M. Doing science together: Gaining momentum from long-term explorative university-industry research programs. Drug Discov Today 2023; 28:103687. [PMID: 37356615 DOI: 10.1016/j.drudis.2023.103687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/06/2023] [Accepted: 06/20/2023] [Indexed: 06/27/2023]
Abstract
'Doing science together' collaborations are a more intense form of university-industry interactions and are characterized by a mutual involvement and active participation of academic and company scientists in scientific research. Here, we examine the successful approach that AstraZeneca and its internationally renowned academic partners, Karolinska Institutet and Uppsala University, implemented to fully unlock the potential of all parties in long-term, explorative, truly collaborative research programs. The underlying premises of these successful research programs are three collaborative governance mechanisms (3MCs) that are required that leverage the strengths of each organization: mutual collaboration; mutually beneficial science; and a mutual governance model with senior management involvement.
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Affiliation(s)
- Bastian Rake
- School of Business, Maynooth University, Maynooth, Co Kildare, Ireland; Gothenburg U-GOT KIES Centre, University of Gothenburg, Gothenburg, Sweden.
| | - Kaushik Sengupta
- Alliance Management, Business Development, Licensing and Strategy (BDL&S), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Lena Lewin
- Faculty Office and International Relations, Karolinska Institutet, Stockholm, Sweden
| | - Anna Sandström
- Global Corporate Affairs, AstraZeneca, Stockholm, Sweden
| | - Maureen McKelvey
- Department of Economy & Society, University of Gothenburg, Gothenburg, Sweden; Gothenburg U-GOT KIES Centre, University of Gothenburg, Gothenburg, Sweden
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14
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Kiss B, Borbély J. Business Risk Mitigation in the Development Process of New Monoclonal Antibody Drug Conjugates for Cancer Treatment. Pharmaceutics 2023; 15:1761. [PMID: 37376209 DOI: 10.3390/pharmaceutics15061761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
Recent developments aim to extend the cytotoxic effect and therapeutic window of mAbs by constructing antibody-drug conjugates (ADCs), in which the targeting moiety is the mAb that is linked to a highly toxic drug. According to a report from mid of last year, the global ADCs market accounted for USD 1387 million in 2016 and was worth USD 7.82 billion in 2022. It is estimated to increase in value to USD 13.15 billion by 2030. One of the critical points is the linkage of any substituent to the functional group of the mAb. Increasing the efficacy against cancer cells' highly cytotoxic molecules (warheads) are connected biologically. The connections are completed by different types of linkers, or there are efforts to add biopolymer-based nanoparticles, including chemotherapeutic agents. Recently, a combination of ADC technology and nanomedicine opened a new pathway. To fulfill the scientific knowledge for this complex development, our aim is to write an overview article that provides a basic introduction to ADC which describes the current and future opportunities in therapeutic areas and markets. Through this approach, we show which development directions are relevant both in terms of therapeutic area and market potential. Opportunities to reduce business risks are presented as new development principles.
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Affiliation(s)
- Balázs Kiss
- Faculty of Economics, University of Debrecen, 4032 Debrecen, Hungary
- BBS Dominus LLC, 4225 Debrecen, Hungary
| | - János Borbély
- Doctoral School of Clinical Medicine, University of Debrecen, 4032 Debrecen, Hungary
- BBS Biochemicals LLC, 4225 Debrecen, Hungary
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15
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Agarwal A, Orlow SJ. Skin in the Game: An Analysis of Venture Capital Investment in Dermatology from 2002 to 2021. J Invest Dermatol 2023; 143:533-537.e1. [PMID: 36639307 DOI: 10.1016/j.jid.2022.11.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/27/2022] [Accepted: 11/04/2022] [Indexed: 01/13/2023]
Affiliation(s)
- Aneesh Agarwal
- New York University Leonard N. Stern School of Business, New York, New York, USA
| | - Seth J Orlow
- The Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, New York, USA.
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16
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Chopra H, Verma R, Kaushik S, Parashar J, Madan K, Bano A, Bhardwaj R, Pandey P, Kumari B, Purohit D, Kumar M, Bhatia S, Rahman MH, Mittal V, Singh I, Kaushik D. Cyclodextrin-Based Arsenal for Anti-Cancer Treatments. Crit Rev Ther Drug Carrier Syst 2023; 40:1-41. [PMID: 36734912 DOI: 10.1615/critrevtherdrugcarriersyst.2022038398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Anti-cancer drugs are mostly limited in their use due to poor physicochemical and biopharmaceutical properties. Their lower solubility is the most common hurdle limiting their use upto their potential. In the recent years, the cyclodextrin (CD) complexation have emerged as existing approach to overcome the problem of poor solubility. CD-based nano-technological approaches are safe, stable and showed well in vivo tolerance and greater payload for encapsulation of hydrophobic drugs for the targeted delivery. They are generally chosen due to their ability to get self-assembled to form liposomes, nanoparticles, micelles and nano-sponges etc. This review paper describes a birds-eye view of the various CD-based nano-technological approaches applied for the delivery of anti-cancer moieties to the desired target such as CD based liposomes, niosomes, niosoponges, micelles, nanoparticles, monoclonal antibody, magnetic nanoparticles, small interfering RNA, nanorods, miscellaneous formulation of anti-cancer drugs containing CD. Moreover, the author also summarizes the various shortcomings of such a system and their way ahead.
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Affiliation(s)
- Hitesh Chopra
- Chitkara College of Pharmacy, Chitkara University, Punjab 140401, India
| | - Ravinder Verma
- Department of Pharmacy, G.D. Goenka University, Sohna Road, Gurugram 122103, India
| | - Sakshi Kaushik
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak 124001, India
| | - Jatin Parashar
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak 124001, India
| | - Kumud Madan
- Lloyd Institute of Management and Technology (Pharm), Knowledge Park, Greater Noida, U.P., India
| | - Afsareen Bano
- Centre for Medical Biotechnology, Maharshi Dayanand University, Rohtak 124001, India
| | - Rashmi Bhardwaj
- Centre for Medical Biotechnology, Maharshi Dayanand University, Rohtak 124001, India
| | - Parijat Pandey
- Department of Pharmaceutical Sciences, Gurugram University, Gurugram 122413, India
| | - Beena Kumari
- Department of Pharmaceutical Sciences, Indira Gandhi University, Meerpur, Rewari, India
| | - Deepika Purohit
- Department of Pharmaceutical Sciences, Indira Gandhi University, Meerpur, Rewari, India
| | - Manish Kumar
- M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala 133207, Haryana, India
| | - Saurabh Bhatia
- Natural and Medical Sciences Research Center, University of Nizwa, Nizwa, Sultanate of Oman; School of Health Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand 248007, India
| | - Md Habibur Rahman
- Department of Pharmacy, Southeast University, Banani, Dhaka 1213, Bangladesh
| | - Vineet Mittal
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak 124001, India
| | - Inderbir Singh
- Chitkara College of Pharmacy, Chitkara University, Punjab 140401, India
| | - Deepak Kaushik
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak 124001, India
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17
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Ray SK, Mukherjee S. Starring Role of Biomarkers and Anticancer Agents as a Major Driver in Precision Medicine of Cancer Therapy. Curr Mol Med 2023; 23:111-126. [PMID: 34939542 DOI: 10.2174/1566524022666211221152947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 10/18/2021] [Accepted: 10/26/2021] [Indexed: 12/16/2022]
Abstract
Precision medicine is the most modern contemporary medicine approach today, based on great amount of data on people's health, individual characteristics, and life circumstances, and employs the most effective ways to prevent and cure diseases. Precision medicine in cancer is the most precise and viable treatment for every cancer patient based on the disease's genetic profile. Precision medicine changes the standard one size fits all medication model, which focuses on average responses to care. Consolidating modern methodologies for streamlining and checking anticancer drugs can have long-term effects on understanding the results. Precision medicine can help explicit anticancer treatments using various drugs and even in discovery, thus becoming the paradigm of future cancer medicine. Cancer biomarkers are significant in precision medicine, and findings of different biomarkers make this field more promising and challenging. Naturally, genetic instability and the collection of extra changes in malignant growth cells are ways cancer cells adapt and survive in a hostile environment, for example, one made by these treatment modalities. Precision medicine centers on recognizing the best treatment for individual patients, dependent on their malignant growth and genetic characterization. This new era of genomics progressively referred to as precision medicine, has ignited a new episode in the relationship between genomics and anticancer drug development.
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Affiliation(s)
| | - Sukhes Mukherjee
- Department of Biochemistry. All India Institute of Medical Sciences. Bhopal, Madhya Pradesh-462020. India
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18
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Ozieranski P, Martinon L, Jachiet PA, Mulinari S. Tip of the Iceberg? Country- and Company-Level Analysis of Drug Company Payments for Research and Development in Europe. Int J Health Policy Manag 2022; 11:2842-2859. [PMID: 35297231 PMCID: PMC10105170 DOI: 10.34172/ijhpm.2022.6575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 02/21/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Creating new therapies often involves drug companies paying healthcare professionals and institutions for research and development (R&D) activities, including clinical trials. However, industry sponsorship can create conflicts of interest (COIs). We analysed approaches to drug company R&D payment disclosure in European countries and the distribution of R&D payments at the country and company level. METHODS Using documentary sources and a stakeholder survey we identified country- regulatory approaches to R&D payment disclosure. We reviewed company-level descriptions of disclosure practices in the United Kingdom, a country with a major role in Europe's R&D. We obtained country-level R&D payment data from industry trade groups and public authorities and company-level data from eurosfordocs.eu, a publicly available payments database. We conducted content analysis and descriptive statistical analysis. RESULTS In 32 of 37 studied countries, all R&D payments were reported without named recipients, following a self-regulatory approach developed by the industry. The methodological descriptions from 125 companies operating in the United Kingdom suggest that within the self-regulatory approach companies had much leeway in deciding what activities and payments were considered as R&D. In five countries, legislation mandated the disclosure of R&D payment recipients, but only in two were payments practically identifiable and analysable. In 17 countries with available data, R&D constituted 19%-82% of all payments reported, with self-regulation associated with higher shares. Available company-level data from three countries with self-regulation suggests that R&D payments were concentrated by big funders, and some companies reported all, or nearly all, payments as R&D. CONCLUSION The lack of full disclosure of R&D payments in countries with industry self-regulation leaves considerable sums of money unaccounted for and potentially many COIs undetected. Disclosure mandated by legislation exists in few countries and rarely enhances transparency practically. We recommend a unified European approach to R&D payment disclosure, including clear definitions and a centralised database.
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Affiliation(s)
- Piotr Ozieranski
- Department of Social and Policy Sciences, University of Bath, Bath, UK
| | | | | | - Shai Mulinari
- Department of Sociology, Lund University, Lund, Sweden
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19
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NTD Health: an electronic medical record system for neglected tropical diseases. BIOMEDICA : REVISTA DEL INSTITUTO NACIONAL DE SALUD 2022; 42:602-610. [PMID: 36511677 PMCID: PMC9788840 DOI: 10.7705/biomedica.6269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Indexed: 12/14/2022]
Abstract
INTRODUCTION The use of technological resources to support processes in health systems has generated robust, interoperable and dynamic platforms. In the case of institutions working with neglected tropical diseases (NTD), there is a need for NTD-specific customizations. OBJECTIVES To establish a medical records platform, specialized for NTD, which would facilitate the analysis of treatment evolution in patients, as well as generate more accurate data about various clinical aspects. MATERIALS AND METHODS Here we developed a customized electronic medical record system based on OpenMRS for multiple NTDs. A set of forms and functionalities was developed under the OpenMRS guidelines, using shared community modules. RESULTS All the customized information was packaged in a distribution called NTD Health. The platform is web-based and can be upgraded and improved by users without technological barriers. CONCLUSIONS The EMR system can become a useful tool for other institutions to improve their health practices as well as the quality of life for NTD patients, simplifying the customization of healthcare systems able to interoperate with other platforms.
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20
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Billette de Villemeur E, Scannell JW, Versaevel B. Biopharmaceutical R&D outsourcing: Short-term gain for long-term pain? Drug Discov Today 2022; 27:103333. [PMID: 36007753 DOI: 10.1016/j.drudis.2022.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 07/08/2022] [Accepted: 08/09/2022] [Indexed: 11/25/2022]
Abstract
Research and development (R&D) outsourcing offers some obvious productivity benefits (e.g., access to new technology, variabilised costs, risk sharing, etc.). However, recent work in economics points to a productivity headwind at the level of the innovation ecosystem. The market for technologies with economies of scope and knowledge spillovers (those with the biggest impact on industry economics and social welfare) has structural features that allow customers to capture a disproportionate share of economic value and transfer a disproportionate share of economic risk to technology providers, even though the providers aim to maximise profit. This reduces the incentives to invest in new ventures that specialise in the most promising early-stage projects. Therefore, near-term gains from R&D outsourcing can be offset by slower innovation in the long run.
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Affiliation(s)
| | - Jack W Scannell
- Science, Technology, and Innovation Studies, University of Edinburgh, Edinburgh EH1 1LZ, UK; JW Scannell Analytics LTD, 32 Queens Crescent, Edinburgh EH9 2BA, UK.
| | - Bruno Versaevel
- Emlyon Business School, Lyon, France; Groupe d'Analyse et de Théorie Economique, Lyon, France
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21
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Liao J, Wang Q, Wu F, Huang Z. In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets. Molecules 2022; 27:7103. [PMID: 36296697 PMCID: PMC9609013 DOI: 10.3390/molecules27207103] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/12/2022] [Accepted: 08/25/2022] [Indexed: 07/30/2023] Open
Abstract
Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active site identification methods, including the identification of binding sites and assessment of druggability. We provide some guidelines for selecting methods for the identification of binding sites and assessment of druggability. In addition, we list the databases and tools commonly used with these methods, present examples of individual and combined applications, and compare the methods and tools. Finally, we discuss the challenges and limitations of binding site identification and druggability assessment at the current stage and provide some recommendations and future perspectives.
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Affiliation(s)
- Jianbo Liao
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China
- The Second School of Clinical Medicine, Guangdong Medical University, Dongguan 523808, China
| | - Qinyu Wang
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China
| | - Fengxu Wu
- Hubei Key Laboratory of Wudang Local Chinese Medicine Research, School of Pharmaceutical Sciences, Hubei University of Medicine, Shiyan 442000, China
| | - Zunnan Huang
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China
- Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang 524023, China
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22
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Zheng S, Venkatakrishnan K, Kennedy BB. How resilient were we in 2021? Results of a LinkedIn Survey including biomedical and pharmaceutical professionals using the Benatti Resiliency Model. Clin Transl Sci 2022; 15:2355-2365. [PMID: 35981318 PMCID: PMC9579401 DOI: 10.1111/cts.13364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/03/2022] [Accepted: 06/22/2022] [Indexed: 01/25/2023] Open
Abstract
Enhancing resiliency should elevate innovation and efficiency in biomedical research and development (R&D); however, compared with other professions, data on practice of resilience is lacking. Using the Benatti Resiliency Model (5 anchors: Well-Being, Self-Awareness, Brand, Connection, and Innovation), we surveyed professionals, including those in biomedical and pharmaceutical R&D. A structured LinkedIn questionnaire (March 16-May 23, 2021), surveyed each model anchor using five categories. One hundred fifty-eight participants (~6% student/trainee, 18%, 27%, and 49% in 1-5, 5-15 or >15 years post-terminal degree) took the survey (90 in biomedical and pharmaceutical R&D). Over 50% chose "always"/"often" across questions, except external influence or engagement. The question with one of the lowest "always" scores (~15%) was "I get feedback on my influence and impact in my career" in Brand, highlighting areas for leadership development and coaching. In the anchor of Well-being, nutrition and stress management also received some lowest "always" scores (~15% for both). Connection and Innovation scores trended slightly higher in biomedical and pharmaceutical R&D. No students/trainees chose "always" in Brand, indicating evolution of brand maturity over time. Self- and survey-assessed resiliency scores were associated (rs = 0.37, p < 0.0001). Our survey yielded actionable insights on Resilience, including "best practices" through an open-ended question for one thing most useful to boost resilience in the survey and is the first application of the Benatti Model for crowdsourced research.
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Affiliation(s)
| | - Karthik Venkatakrishnan
- EMD Serono Research & Development Institute, Inc.BillericaMassachusettsUSA,A Business of Merck KGaADarmstadtGermany
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23
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Park SM, Vonortas NS. Translational research: from basic research to regional biomedical entrepreneurship. SMALL BUSINESS ECONOMICS 2022; 60:1761-1783. [PMID: 38625332 PMCID: PMC9425788 DOI: 10.1007/s11187-022-00676-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 08/02/2022] [Indexed: 04/17/2024]
Abstract
This paper examines the effect of translational research on knowledge production and biomedical entrepreneurship across U.S. regions. Researchers have earlier investigated the outputs of translational research by focusing on academic publications. Little attention has been paid to linking translational research to biomedical entrepreneurship. We construct an analytical model based on the knowledge spillover theory of entrepreneurship and the entrepreneurial ecosystem approach to examine the relationship between translational research, biomedical patents, clinical trials, and biomedical entrepreneurship. We test the model across 381 U.S. metropolitan statistical areas using 10 years of panel data related to the NIH Clinical and Translational Science Awards (CTSA) program. CTSA appears to increase the number of biomedical patents and biomedical entrepreneurship as proxied by the NIH Small Business Innovation Research (SBIR) grants. However, the magnitudes of the effects are relatively small. Path analysis shows that the effect of translational research on regional biomedical entrepreneurship is not strongly conveyed through biomedical patents or clinical trials.
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Affiliation(s)
- Sang-Min Park
- Science, Technology and Innovation Support Team, Ministry of Science and ICT, Sejong Finance Center II, 194, Gareum-ro, Sejong-si, 30121 South Korea
| | - Nicholas S. Vonortas
- Institute for International Science and Technology Policy & Department of Economics, George Washington University, 1957 E Street NW Suite 403, Washington DC, 20052 USA
- São Paulo Excellence Chair, University of Campinas, Campinas, Brazil
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Bhatnagar B, Dörfler V, MacBryde J. Navigating the open innovation paradox: an integrative framework for adopting open innovation in pharmaceutical R&D in developing countries. JOURNAL OF TECHNOLOGY TRANSFER 2022; 48:1-45. [PMID: 35996639 PMCID: PMC9386677 DOI: 10.1007/s10961-022-09958-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2022] [Indexed: 11/05/2022]
Abstract
In this paper, we combine evidence from eight Indian pharmaceutical firms with extant literature and global best practices to conceptualize an integrative framework addressing the open innovation paradox (OIP), i.e., the tension between intellectual protection and openness. Firms in developing countries face additional challenges in the adoption of open innovation, such as the prevalence of open science norms, weak technology transfer systems, and mistrust between universities and industry; therefore, they employ open innovation selectively for pharmaceutical research. Prior research has examined the strategies to resolve OIP in the context of developed countries; the integrative framework proposed in this paper describes strategies for resolving the OIP in the context of developing countries. This framework illuminates the coping processes of the case firms and provides guidelines to uplift and accelerate the adoption of open innovation strategies in developing countries' pharmaceutical sectors, and thus provides value to both theory and praxis.
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Affiliation(s)
- Bhawani Bhatnagar
- Department of Management Science, University of Strathclyde, Level 7, Sir William Duncan Building, 130 Rottenrow, Glasgow, UK
| | - Viktor Dörfler
- Department of Management Science, University of Strathclyde, Level 7, Sir William Duncan Building, 130 Rottenrow, Glasgow, UK
| | - Jillian MacBryde
- Innovation and Operations Management, University of Strathclyde, Glasgow, UK
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Jung YL, Yoo HS, Hwang J. Artificial intelligence-based decision support model for new drug development planning. EXPERT SYSTEMS WITH APPLICATIONS 2022; 198:116825. [PMID: 35283560 PMCID: PMC8902892 DOI: 10.1016/j.eswa.2022.116825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 01/18/2022] [Accepted: 03/02/2022] [Indexed: 06/14/2023]
Abstract
New drug development guarantees a very high return on success, but the success rate is extremely low. Pharmaceutical companies have attempted to use various strategies to increase the success rate of drug development, but this goal has been difficult to achieve. In this study, we developed a model that can guide effective decision-making at the planning stage of new drug development by leveraging machine learning. The Drug Development Recommendation (DDR) model, we present here, is a hybrid model for recommending and/or predicting drug groups suitable for development by individual pharmaceutical companies. It combines association rule learning, collaborative filtering, and content-based filtering approaches for enterprise-customized recommendations. In the case of content-based filtering applying a random forest classification algorithm, the accuracy and area under curve were 78% and 0.74, respectively. In particular, the DDR model was applied to predict the success probability of companies developing Coronavirus disease 2019 (COVID-19) vaccines. It was demonstrated that the higher the predicted score from the DDR model, the more progress in the clinical phase of the COVID-19 vaccine development. Although our approach has limitations that should be improved, it makes scientific as well as industrial contributions in that the DDR model can support rational decision-making prior to initiating drug development by considering not only technical aspects but also company-related variables.
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Affiliation(s)
- Ye Lim Jung
- Division of Data Analysis, Korea Institute of Science and Technology Information (KISTI), Seoul 02456, Republic of Korea
| | - Hyoung Sun Yoo
- Division of Data Analysis, Korea Institute of Science and Technology Information (KISTI), Seoul 02456, Republic of Korea
- Science and Technology Management Policy, University of Science and Technology, Daejeon 34113, Republic of Korea
| | - JeeNa Hwang
- Division of Data Analysis, Korea Institute of Science and Technology Information (KISTI), Seoul 02456, Republic of Korea
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26
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Open innovation: A paradigm shift in pharma R&D? Drug Discov Today 2022; 27:2395-2405. [DOI: 10.1016/j.drudis.2022.05.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/06/2022] [Accepted: 05/18/2022] [Indexed: 11/20/2022]
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27
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A Bibliometric Analysis and Systematic Review on E-Marketplaces, Open Innovation, and Sustainability. SUSTAINABILITY 2022. [DOI: 10.3390/su14095456] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In recent years, the rise of e-commerce has prompted the emergence of electronic marketplaces, or e-marketplaces, which act as intermediaries in the buying and selling process, bringing together several vendors to offer a wide range of products and services to customers, generating modalities such as business-to-business (B2B), business-to-consumer (B2C) or consumer-to-consumer (C2C) e-marketplaces. E-marketplaces offer advantages such as access to potential buyers, business and product visibility, the reduction of transaction costs, the comparison of offers and prices among competitors, and the ease of business internationalization. However, the success of e-marketplace business models depends on the sustainability of these platforms, which must involve different stakeholders in order to meet economic, environmental, and social objectives. Therefore, this study presents a bibliometric analysis and systematic review of e-marketplaces, open innovation, and sustainability for the last ten, five, and two years. The analysis includes the number, types, and subject areas of documents published each year, as well as considerations such as the most-cited publications and the leading authors, journals, countries, and institutional affiliations. The analysis also includes a study of the relevant concepts in the publications and their relationships, identifying the predominant topics related to e-marketplaces, open innovation, and sustainability. The results indicate a focus on subject areas such as social sciences, environmental sciences, energy, business, management, and accounting, which is consistent with the economic, environmental, and social dimensions of sustainability. The findings show that e-marketplaces, open innovation, and sustainability are closely related to concepts such as sustainable development, e-commerce, digital marketing, China (the leading country in terms of publications in all periods), logistics, supply chain management, big data, planning, and decision making. Future works should address traffic congestion and environmental impact, new delivery practices in last-mile logistics, and the motives for users’ engagement in e-marketplaces. Likewise, future research can be oriented toward sustainability dimensions and stakeholders’ integration through open innovation and toward the limitations of SMEs in order to access and benefit from digital platforms.
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28
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Pillai N, Dasgupta A, Sudsakorn S, Fretland J, Mavroudis PD. Machine-learning-guided early drug discovery of small molecules. Drug Discov Today 2022; 27:2209-2215. [PMID: 35364270 DOI: 10.1016/j.drudis.2022.03.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 12/19/2021] [Accepted: 03/25/2022] [Indexed: 11/17/2022]
Abstract
Machine learning (ML) approaches have been widely adopted within the early stages of the drug discovery process, particularly within the context of small-molecule drug candidates. Despite this, the use of ML is still limited in the pharmacokinetic/pharmacodynamic (PK/PD) application space. Here, we describe recent progress and the role of ML used in preclinical drug discovery. We summarize the advances and current strategies used to predict ADME properties of small molecules based on their structures, and predict structures based on the desired properties for molecular screening and optimization. Finally, we discuss the use of ML to predict PK to rank the ability of drug candidates to achieve appropriate exposures and hence provide important insights into safety and efficacy. Teaser: In this short review we highlight key advances in the application of machine learning to early drug discovery for small molecules in the preclinical setting.
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Affiliation(s)
- Nikhil Pillai
- Quantitative Pharmacology, DMPK, Sanofi US, Waltham, MA, USA.
| | - Aparajita Dasgupta
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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29
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Kurata H, Ishino T, Ohshima Y, Yohda M. CDMOs Play a Critical Role in the Biopharmaceutical Ecosystem. Front Bioeng Biotechnol 2022; 10:841420. [PMID: 35387299 PMCID: PMC8978586 DOI: 10.3389/fbioe.2022.841420] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/07/2022] [Indexed: 12/14/2022] Open
Abstract
Biopharmaceutical industries have advanced significantly after the millennium. Novel biopharmaceuticals have been developed one after another, and blockbuster drugs have been produced. Accompanying the increase in the demand for biopharmaceuticals, a business model called “contract development manufacturing organization (CDMO)” has emerged. A CDMO is entrusted with the development and manufacturing of production processes from pharmaceutical companies. In this review, we identify the success factors of the biopharmaceutical CDMO by analyzing the foundry business for the semiconductor industry. Furthermore, we also review monoclonal antibody production platforms and new technologies that are critical aspects of differentiation strategies in the biopharmaceutical CDMO.
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Affiliation(s)
- Hideyuki Kurata
- Technology General Division, AGC Inc., Tokyo, Japan
- Institute of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan
| | - Tetsuya Ishino
- Technology General Division, AGC Inc., Tokyo, Japan
- AGC Biologics, Bothell, WA, United States
| | | | - Masafumi Yohda
- Institute of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan
- *Correspondence: Masafumi Yohda,
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30
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Gao CQ, Zhou YK, Xin XH, Min H, Du PF. DDA-SKF: Predicting Drug-Disease Associations Using Similarity Kernel Fusion. Front Pharmacol 2022; 12:784171. [PMID: 35095495 PMCID: PMC8792612 DOI: 10.3389/fphar.2021.784171] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 12/20/2021] [Indexed: 12/13/2022] Open
Abstract
Drug repositioning provides a promising and efficient strategy to discover potential associations between drugs and diseases. Many systematic computational drug-repositioning methods have been introduced, which are based on various similarities of drugs and diseases. In this work, we proposed a new computational model, DDA-SKF (drug-disease associations prediction using similarity kernels fusion), which can predict novel drug indications by utilizing similarity kernel fusion (SKF) and Laplacian regularized least squares (LapRLS) algorithms. DDA-SKF integrated multiple similarities of drugs and diseases. The prediction performances of DDA-SKF are better, or at least comparable, to all state-of-the-art methods. The DDA-SKF can work without sufficient similarity information between drug indications. This allows us to predict new purpose for orphan drugs. The source code and benchmarking datasets are deposited in a GitHub repository (https://github.com/GCQ2119216031/DDA-SKF).
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Affiliation(s)
| | | | | | | | - Pu-Feng Du
- College of Intelligence and Computing, Tianjin University, Tianjin, China
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31
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Groothuis P. Model Systems in Endometriosis Research: Translation, Translation, Translation! FRONTIERS IN REPRODUCTIVE HEALTH 2022; 3:809366. [PMID: 36304048 PMCID: PMC9580766 DOI: 10.3389/frph.2021.809366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 12/20/2021] [Indexed: 12/31/2022] Open
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32
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Um SI, Sohn UD, Jung SY, You SH, Kim C, Lee S, Lee H. Longitudinal study of the impact of three major regulations on the Korean pharmaceutical industry in the last 30 years. Health Res Policy Syst 2022; 20:4. [PMID: 34991612 PMCID: PMC8734354 DOI: 10.1186/s12961-021-00797-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 11/25/2021] [Indexed: 11/23/2022] Open
Abstract
Background The pharmaceutical industry is heavily regulated. Partly for this reason, new drugs generally take over 10 years from the product development stage to market entry. Although regulations affect the pharmaceutical industry over a long period, previous studies investigating the impact of new regulatory policies have usually focused on the short period before and after implementing that policy. Therefore, the purpose of this study is to examine whether and how significantly regulatory policies affect long-term innovation in the pharmaceutical industry in Korea. Methods This study focused on three significant regulatory policies: the introduction of the product patent system, changes in the Good Manufacturing Practice (GMP) system, and the Drug Expenditure Rationalization Plan (DERP). The study used interrupted time series (ITS) analysis to investigate the long-term impacts of the policies before and after implementation. Results Our results show that introducing the product patent system in 1987 significantly increased the number of Korean patent applications. The effect of the revised GMP policies was also statistically significant, both before and after implementation and between pre-emptive companies and non-pre-emptive ones. However, due to the companies' negotiations with the regulatory authorities or the regulatory system that links drug approval and price evaluation, the DERP did not significantly delay new drug registration in Korea. Conclusion This study showed that the policies of the product patent system, GMP policies, and DERP regulations have significantly encouraged pharmaceutical companies to strive to meet regulatory requirements and promote innovation in Korea. The study suggests that it is necessary for companies to pre-emptively respond to systemic changes in development and production strategies to deal with regulatory changes and achieve sustainable growth. Also, our study results indicate that since government policies motivate the innovative system of the pharmaceutical industry, governmental authorities, when formulating pharmaceutical policies, need to consider the impact on the long-term innovation of the industry.
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Affiliation(s)
- Seung In Um
- Korea Pharmaceutical and Bio-Pharma Manufacturers Association, Seoul, South Korea
| | - Uy Dong Sohn
- Department of Pharmacology, Chung-Ang University, Seoul, South Korea
| | - Sun-Young Jung
- College of Pharmacy, Chung-Ang University, Seoul, South Korea
| | - Seung-Hun You
- Department of Global Innovative Drugs, Chung-Ang University, Seoul, South Korea
| | - Changone Kim
- Graduate School of Global Entrepreneurship, Keimyung University, Daegu, South Korea
| | - Sora Lee
- Graduate School of Management of Technology, Sungkyunkwan University, Suwon, South Korea
| | - Heesang Lee
- Graduate School of Management of Technology, Sungkyunkwan University, Suwon, South Korea.
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33
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Russo M, Cejas CM, Pitingolo G. Advances in microfluidic 3D cell culture for preclinical drug development. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2022; 187:163-204. [PMID: 35094774 DOI: 10.1016/bs.pmbts.2021.07.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Drug development is often a very long, costly, and risky process due to the lack of reliability in the preclinical studies. Traditional current preclinical models, mostly based on 2D cell culture and animal testing, are not full representatives of the complex in vivo microenvironments and often fail. In order to reduce the enormous costs, both financial and general well-being, a more predictive preclinical model is needed. In this chapter, we review recent advances in microfluidic 3D cell culture showing how its development has allowed the introduction of in vitro microphysiological systems, laying the foundation for organ-on-a-chip technology. These findings provide the basis for numerous preclinical drug discovery assays, which raise the possibility of using micro-engineered systems as emerging alternatives to traditional models, based on 2D cell culture and animals.
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Affiliation(s)
- Maria Russo
- Microfluidics, MEMS, Nanostructures (MMN), CNRS UMR 8231, Institut Pierre Gilles de Gennes (IPGG) ESPCI Paris, PSL Research University, Paris France.
| | - Cesare M Cejas
- Microfluidics, MEMS, Nanostructures (MMN), CNRS UMR 8231, Institut Pierre Gilles de Gennes (IPGG) ESPCI Paris, PSL Research University, Paris France
| | - Gabriele Pitingolo
- Bioassays, Microsystems and Optical Engineering Unit, BIOASTER, Paris France
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34
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Dagenais S, Russo L, Madsen A, Webster J, Becnel L. Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design. Clin Pharmacol Ther 2022; 111:77-89. [PMID: 34839524 PMCID: PMC9299990 DOI: 10.1002/cpt.2480] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 10/30/2021] [Indexed: 12/28/2022]
Abstract
Interest in real-world data (RWD) and real-world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third-party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single-arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness "big" RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient-derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.
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Affiliation(s)
| | - Leo Russo
- Global Medical Epidemiology, Worldwide Medical and SafetyPfizer IncCollegevillePennsylvaniaUSA
| | - Ann Madsen
- Global Medical Epidemiology, Worldwide Medical and SafetyPfizer IncNew YorkNew YorkUSA
| | - Jen Webster
- Real World EvidencePfizer IncNew YorkNew YorkUSA
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35
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Hong CC. The grand challenge of discovering new cardiovascular drugs. FRONTIERS IN DRUG DISCOVERY 2022; 2:1027401. [PMID: 37123434 PMCID: PMC10134778 DOI: 10.3389/fddsv.2022.1027401] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
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36
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Santos JLD. Innovation in Pharmaceutical Assistance. BRAZ J PHARM SCI 2022. [DOI: 10.1590/s2175-97902022e19724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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37
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Kansy M, Caron G. New therapeutic modalities in drug discovery and development: Insights & opportunities. ADMET AND DMPK 2021; 9:227-230. [PMID: 35300374 PMCID: PMC8920101 DOI: 10.5599/admet.1209] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 12/13/2021] [Indexed: 11/18/2022] Open
Abstract
New Therapeutic Modalities in Drug Discovery and Development: Insights & Opportunities (Editorial for the special issue of ADMET and DMPK)
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Affiliation(s)
- Manfred Kansy
- Independent Consultant, 79111, Freiburg im Breisgau, Germany
| | - Giulia Caron
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Quarello 15, 10135 Torino, Italy
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38
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Wigge C, Stefanovic A, Radjainia M. The rapidly evolving role of cryo-EM in drug design. DRUG DISCOVERY TODAY. TECHNOLOGIES 2021; 38:91-102. [PMID: 34895645 DOI: 10.1016/j.ddtec.2020.12.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 12/09/2020] [Accepted: 12/22/2020] [Indexed: 01/18/2023]
Abstract
Since the early 2010s, cryo-electron microscopy (cryo-EM) has evolved to a mainstream structural biology method in what has been dubbed the "resolution revolution". Pharma companies also began to use cryo-EM in drug discovery, evidenced by a growing number of industry publications. Hitherto limited in resolution, throughput and attainable molecular weight, cryo-EM is rapidly overcoming its main limitations for more widespread use through a new wave of technological advances. This review discusses how cryo-EM has already impacted drug discovery, and how the state-of-the-art is poised to further revolutionize its application to previously intractable proteins as well as new use cases.
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Affiliation(s)
- Christoph Wigge
- Thermo Fisher Scientific, Achtseweg Noord 5, 5651 GG Eindhoven, The Netherlands
| | | | - Mazdak Radjainia
- Thermo Fisher Scientific, Achtseweg Noord 5, 5651 GG Eindhoven, The Netherlands.
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39
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Overhoff B, Falls Z, Mangione W, Samudrala R. A Deep-Learning Proteomic-Scale Approach for Drug Design. Pharmaceuticals (Basel) 2021; 14:1277. [PMID: 34959678 PMCID: PMC8709297 DOI: 10.3390/ph14121277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/27/2021] [Accepted: 11/29/2021] [Indexed: 12/26/2022] Open
Abstract
Computational approaches have accelerated novel therapeutic discovery in recent decades. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget therapeutic discovery, repurposing, and design aims to improve their efficacy and safety by employing a holistic approach that computes interaction signatures between every drug/compound and a large library of non-redundant protein structures corresponding to the human proteome fold space. These signatures are compared and analyzed to determine if a given drug/compound is efficacious and safe for a given indication/disease. In this study, we used a deep learning-based autoencoder to first reduce the dimensionality of CANDO-computed drug-proteome interaction signatures. We then employed a reduced conditional variational autoencoder to generate novel drug-like compounds when given a target encoded "objective" signature. Using this approach, we designed compounds to recreate the interaction signatures for twenty approved and experimental drugs and showed that 16/20 designed compounds were predicted to be significantly (p-value ≤ 0.05) more behaviorally similar relative to all corresponding controls, and 20/20 were predicted to be more behaviorally similar relative to a random control. We further observed that redesigns of objectives developed via rational drug design performed significantly better than those derived from natural sources (p-value ≤ 0.05), suggesting that the model learned an abstraction of rational drug design. We also show that the designed compounds are structurally diverse and synthetically feasible when compared to their respective objective drugs despite consistently high predicted behavioral similarity. Finally, we generated new designs that enhanced thirteen drugs/compounds associated with non-small cell lung cancer and anti-aging properties using their predicted proteomic interaction signatures. his study represents a significant step forward in automating holistic therapeutic design with machine learning, enabling the rapid generation of novel, effective, and safe drug leads for any indication.
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Affiliation(s)
| | | | | | - Ram Samudrala
- Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA; (B.O.); (Z.F.); (W.M.)
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40
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Olías-Molero AI, de la Fuente C, Cuquerella M, Torrado JJ, Alunda JM. Antileishmanial Drug Discovery and Development: Time to Reset the Model? Microorganisms 2021; 9:2500. [PMID: 34946102 PMCID: PMC8703564 DOI: 10.3390/microorganisms9122500] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 11/26/2021] [Accepted: 12/01/2021] [Indexed: 01/27/2023] Open
Abstract
Leishmaniasis is a vector-borne parasitic disease caused by Leishmania species. The disease affects humans and animals, particularly dogs, provoking cutaneous, mucocutaneous, or visceral processes depending on the Leishmania sp. and the host immune response. No vaccine for humans is available, and the control relies mainly on chemotherapy. However, currently used drugs are old, some are toxic, and the safer presentations are largely unaffordable by the most severely affected human populations. Moreover, its efficacy has shortcomings, and it has been challenged by the growing reports of resistance and therapeutic failure. This manuscript presents an overview of the currently used drugs, the prevailing model to develop new antileishmanial drugs and its low efficiency, and the impact of deconstruction of the drug pipeline on the high failure rate of potential drugs. To improve the predictive value of preclinical research in the chemotherapy of leishmaniasis, several proposals are presented to circumvent critical hurdles-namely, lack of common goals of collaborative research, particularly in public-private partnership; fragmented efforts; use of inadequate surrogate models, especially for in vivo trials; shortcomings of target product profile (TPP) guides.
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Affiliation(s)
- Ana Isabel Olías-Molero
- Department of Animal Health, Faculty of Veterinary Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.I.O.-M.); (C.d.l.F.); (M.C.)
| | - Concepción de la Fuente
- Department of Animal Health, Faculty of Veterinary Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.I.O.-M.); (C.d.l.F.); (M.C.)
| | - Montserrat Cuquerella
- Department of Animal Health, Faculty of Veterinary Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.I.O.-M.); (C.d.l.F.); (M.C.)
| | - Juan J. Torrado
- Department of Pharmaceutics and Food Technology, Faculty of Pharmacy, Universidad Complutense de Madrid, 28040 Madrid, Spain;
| | - José M. Alunda
- Department of Animal Health, Faculty of Veterinary Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.I.O.-M.); (C.d.l.F.); (M.C.)
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Matlin SA, Krief A, Hopf H, Mehta G. Re-imagining Priorities for Chemistry: A Central Science for "Freedom from Fear and Want". Angew Chem Int Ed Engl 2021; 60:25610-25623. [PMID: 34704655 DOI: 10.1002/anie.202108067] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Indexed: 11/10/2022]
Abstract
Human security, defined as "freedom from want and fear and freedom to live in dignity", provides an overarching concept to address threats to human security dimensions such as health, food, economics, the environment and sustainable development, while placing the individual at the centre of attention. Chemistry is central to addressing these challenges, but surprisingly its role and contributions to human security have hitherto not been explicitly set out. This article situates chemistry in the human security framework, highlighting areas where chemistry knowledge, methods and products are vital. It underscores three complementary facets: 1) chemistry contributes to many dimensions of human security, but needs to do much more in the light of oncoming global challenges; 2) the human security framing illuminates areas where chemistry itself needs to adapt to contribute better, by intensification of current approaches and/or by building or strengthening chemistry tools, skills and competencies; and 3) repositioning as central to human security affords chemistry a powerful opportunity to refresh itself as a science for the benefit of society-and it will need to engage more directly and dynamically at the interface of science, society and policy in order to do so.
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Affiliation(s)
- Stephen A Matlin
- Institute of Global Health Innovation, Imperial College London, Faculty Building, South Kensington, London, SW7 2AZ, UK
| | - Alain Krief
- Department of Chemistry, University of Namur, Belgium
| | - Henning Hopf
- Institute of Organic Chemistry, Technical University of Braunschweig, Germany
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42
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Matlin SA, Krief A, Hopf H, Mehta G. Re‐imagining Priorities for Chemistry: A Central Science for “Freedom from Fear and Want”. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202108067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Stephen A. Matlin
- Institute of Global Health Innovation Imperial College London Faculty Building, South Kensington London SW7 2AZ UK
| | - Alain Krief
- Department of Chemistry University of Namur Belgium
| | - Henning Hopf
- Institute of Organic Chemistry Technical University of Braunschweig Germany
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43
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Williams M. Improving Translational Paradigms in Drug Discovery and Development. Curr Protoc 2021; 1:e273. [PMID: 34780124 DOI: 10.1002/cpz1.273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Despite improved knowledge regarding disease causality, new drug targets, and enabling technologies, the attrition rate for compounds entering clinical trials has remained consistently high for several decades, with an average 90% failure rate. These failures are manifested in an inability to reproduce efficacy findings from animal models in humans and/or the occurrence of unexpected safety issues, and reflect failures in T1 translation. Similarly, an inability to sequentially demonstrate compound efficacy and safety in Phase IIa, IIb, and III clinical trials represents failures in T2 translation. Accordingly, T1 and T2 translation are colloquially termed 'valleys of death'. Since T2 translation dealt almost exclusively with clinical trials, T3 and T4 translational steps were added, with the former focused on facilitating interactions between laboratory- and population-based research and the latter on 'real world' health outcomes. Factors that potentially lead to T1/T2 compound attrition include: the absence of biomarkers to allow compound effects to be consistently tracked through development; a lack of integration/'de-siloing' of the diverse discipline-based and technical skill sets involved in drug discovery; the industrialization of drug discovery, which via volume-based goals often results in quantity being prioritized over quality; inadequate project governance and strategic oversight; and flawed decision making based on unreliable/irreproducible or incomplete data. A variety of initiatives have addressed this problem, including the NIH National Center for Advancing Translational Sciences (NCATS), which has focused on bringing an unbiased academic perspective to translation, to potentially revitalize the process. This commentary provides an overview of the basic concepts involved in translation, along with suggested changes in the conduct of biomedical research to avoid valleys of death, including the use of Translational Scoring as a tool to avoid translational attrition and the impact of the FDA Accelerated Approval Pathway in lowering the hurdle for drug approval. © 2021 Wiley Periodicals LLC.
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Affiliation(s)
- Michael Williams
- Department of Biological Chemistry and Pharmacology, College of Medicine, Ohio State University, Columbus, Ohio
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Kusynová Z, Pauletti GM, van den Ham HA, Leufkens HGM, Mantel-Teeuwisse AK. Unmet Medical Need as a Driver for Pharmaceutical Sciences - A Survey Among Scientists. J Pharm Sci 2021; 111:1318-1324. [PMID: 34634318 DOI: 10.1016/j.xphs.2021.10.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/05/2021] [Accepted: 10/05/2021] [Indexed: 12/12/2022]
Abstract
Historical antecedents of pharmaceutical sciences are sound on product orientation based on (analytical) chemistry, drug delivery and basic pharmacology. Over the last decades we have seen a transition towards a stronger disease orientation. This raises questions on whether, how and to what extent unmet medical need (UMN) is important in priority setting, funding and impact in pharmaceutical sciences. An online survey in 2020 collected perspectives of internationally recognised pharmaceutical scientists (N = 92), mainly from academia and industry, on drivers and influencing factors in pharmaceutical sciences. The study offers a unique global perspective, demonstrating a solid command of the global needs in pharmaceutical sciences. The survey revealed that UMN is currently seen as one of the three most important drivers, also in addition to emerging trends in science and opportunities driven by collaboration. There are expectations that UMN's impact becomes more influential. This was consistent for both industry and academic respondents. The majority of respondents also indicated that anticipated lessons learned from COVID-19 will strengthen the impact of UMN on science and leadership. This is important as prioritisation of research towards UMN can address the clinical needs where needed the most.
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Affiliation(s)
- Z Kusynová
- Utrecht Centre for Pharmaceutical Policy and Regulation, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, the Netherlands; International Pharmaceutical Federation (FIP), The Hague, the Netherlands
| | - G M Pauletti
- International Pharmaceutical Federation (FIP), The Hague, the Netherlands; St. Louis College of Pharmacy, St. Louis, Missouri, United States
| | - H A van den Ham
- Utrecht Centre for Pharmaceutical Policy and Regulation, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, the Netherlands.
| | - H G M Leufkens
- Utrecht Centre for Pharmaceutical Policy and Regulation, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, the Netherlands
| | - A K Mantel-Teeuwisse
- Utrecht Centre for Pharmaceutical Policy and Regulation, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, the Netherlands
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Chang YC, Chen PH, Huang CL. Transforming R&D in a world-leading bicycle company (1972–2016): the dynamic capabilities perspective. INNOVATION-ORGANIZATION & MANAGEMENT 2021. [DOI: 10.1080/14479338.2021.1960536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Yuan-Chieh Chang
- Institute of Technology Management, National Tsing Hua University, Hsinchu City, Taiwan (R.O.C.)
| | - Po-Hsuan Chen
- Institute of Technology Management, National Tsing Hua University, Hsinchu City, Taiwan (R.O.C.)
- International Division, Chung-Hua Institution for Economic Research, Taipei City, Taiwan (R.O.C.)
| | - Chin-Lai Huang
- Institute of Technology Management, National Tsing Hua University, Hsinchu City, Taiwan (R.O.C.)
- AIPS Technology Co. Ltd and i-WOW Center, Giant Group. Ltd, Taichung City, Taiwan (R.O.C.)
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Choi G, Kim D, Oh J. AI-Based Drug Discovery of TKIs Targeting L858R/T790M/C797S-Mutant EGFR in Non-small Cell Lung Cancer. Front Pharmacol 2021; 12:660313. [PMID: 34393769 PMCID: PMC8356077 DOI: 10.3389/fphar.2021.660313] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/19/2021] [Indexed: 11/25/2022] Open
Abstract
Lung cancer has a high mortality rate, and non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Patients have been observed to acquire resistance against various anticancer agents used for NSCLC due to L858R (or Exon del19)/T790M/C797S-EGFR mutations. Therefore, next-generation drugs are being developed to overcome this problem of acquired resistance. The goal of this study was to use artificial intelligence (AI) to discover drug candidates that can overcome acquired resistance and reduce the limitations of the current drug discovery process, such as high costs and long durations of drug design and production. To generate ligands using AI, we collected data related to tyrosine kinase inhibitors (TKIs) from accessible libraries and used LSTM (Long short term memory) based transfer learning (TL) model. Through the simplified molecular-input line-entry system (SMILES) datasets of the generated ligands, we obtained drug-like ligands via parameter-filtering, cyclic skeleton (CSK) analysis, and virtual screening utilizing deep-learning method. Based on the results of this study, we are developing prospective EGFR TKIs for NSCLC that have overcome the limitations of existing third-generation drugs.
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Affiliation(s)
- Geunho Choi
- AI LAB, AllLive Healthcare Co.,Ltd., Seongnam, Korea
| | - Daegeun Kim
- AI LAB, AllLive Healthcare Co.,Ltd., Seongnam, Korea
| | - Junehwan Oh
- AI LAB, AllLive Healthcare Co.,Ltd., Seongnam, Korea
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Braddock M. From Target Identification to Drug Development in Space: Using the Microgravity Assist. Curr Drug Discov Technol 2021; 17:45-56. [PMID: 30648510 DOI: 10.2174/1570163816666190112150014] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 12/21/2018] [Accepted: 12/28/2018] [Indexed: 12/19/2022]
Abstract
The unique nature of microgravity encountered in space provides an opportunity for drug discovery and development that cannot be replicated on Earth. From the production of superior protein crystals to the identification and validation of new drug targets to microarray analyses of transcripts attenuated by microgravity, there are numerous examples which demonstrate the benefit of exploiting the space environment. Moreover, studies conducted on Space Shuttle missions, the International Space Station and other craft have had a direct benefit for drug development programmes such as those directed against reducing bone and muscle loss or increasing bone formation. This review will highlight advances made in both drug discovery and development and offer some future insight into how drug discovery and associated technologies may be further advanced using the microgravity assist.
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Affiliation(s)
- Martin Braddock
- Sherwood Observatory, Mansfield and Sutton Astronomical Society, Coxmoor Road, Sutton-in-Ashfield, Nottinghamshire, NG17 5LF, United Kingdom
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Gad El-Rab SMF, Halawani EM, Alzahrani SSS. Biosynthesis of silver nano-drug using Juniperus excelsa and its synergistic antibacterial activity against multidrug-resistant bacteria for wound dressing applications. 3 Biotech 2021; 11:255. [PMID: 33987072 DOI: 10.1007/s13205-021-02782-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 04/05/2021] [Indexed: 02/07/2023] Open
Abstract
We report here the synthesis of silver nanoparticles (AgNPs) from an aqueous extract of Juniperus excelsa and their use as an antimicrobial agent on their own or in combination with antibiotics in inhibiting multidrug-resistant bacteria (MDR). One strategy of bacterial infection control in wound healing is AgNP biosynthesis. We collected bacterial strains of patient skin infections from Al-Adwani Hospital. Phenotyping, biotyping, and molecular characterizations were applied using 16S rRNA gene analysis of bacterial isolates. Our results identified tested MDR bacteria Staphylococcus aureus strains (methicillin-resistant and methicillin-susceptible) and Proteus mirabilis. Gas chromatography/mass spectrometry (GC/MS) analysis was used to identify the Juniperus excelsa biomolecules in the leaf extract acting as both reducing and capping agents in the biosynthesis of AgNPs. The AgNPs appeared hexagonal and spherical in shape upon transmission electron microscope (TEM) analysis. The AgNP sizes ranged from 16.08 to 24.42 nm. X-ray diffraction (XRD) analysis confirmed the crystalline nature of the particles. The minimum inhibitory concentrations (MICs) of the AgNPs against the tested MDR bacteria ranged from 48 to 56 µg/ml, while the minimum bactericidal concentrations (MBCs) of the AgNPs against the tested strains ranged from 72 to 96 µg/ml. The AgNPs showed a good synergistic efficacy with Cefaclor, Cefoxitin, and Erythromycin. Their efficiency showed a threefold increase in the inhibition of tested strains when used in wound dressing, due to the AgNPs potentially activating the antibiotics. Consequently, we can use AgNPs with Cefaclor, Cefoxitin, and Erythromycin antibiotics as alternative antimicrobial agents, and they could be utilized in wound dressing to prevent microbial infections.
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Schuhmacher A, Wilisch L, Kuss M, Kandelbauer A, Hinder M, Gassmann O. R&D efficiency of leading pharmaceutical companies - A 20-year analysis. Drug Discov Today 2021; 26:1784-1789. [PMID: 34022459 DOI: 10.1016/j.drudis.2021.05.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 02/28/2021] [Accepted: 05/11/2021] [Indexed: 10/21/2022]
Abstract
Comparative analysis of the R&D efficiency of 14 leading pharmaceutical companies for the years 1999-2018 shows that there is a close positive correlation between R&D spending and the two investigated R&D output parameters, approved NMEs and the cumulative impact factor of their publications. In other words, higher R&D investments (input) were associated with higher R&D output. Second, our analyses indicate that there are 'economies of scale' (size) in pharmaceutical R&D.
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Affiliation(s)
- Alexander Schuhmacher
- Reutlingen University, Alteburgstrasse 150, DE-72762 Reutlingen, Germany; University of St Gallen, Dufourstrasse 40a, CH-9000 St Gallen, Switzerland.
| | - Lucas Wilisch
- University of St Gallen, Dufourstrasse 40a, CH-9000 St Gallen, Switzerland
| | - Michael Kuss
- PricewaterhouseCoopers AG, Birchstrasse 160, CH-8050 Zurich, Switzerland
| | | | - Markus Hinder
- Novartis Institute of BioMedical Research, Postfach, Forum 1, CH-4002 Basel, Switzerland
| | - Oliver Gassmann
- University of St Gallen, Dufourstrasse 40a, CH-9000 St Gallen, Switzerland
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GPCR_LigandClassify.py; a rigorous machine learning classifier for GPCR targeting compounds. Sci Rep 2021; 11:9510. [PMID: 33947911 PMCID: PMC8097070 DOI: 10.1038/s41598-021-88939-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Accepted: 04/12/2021] [Indexed: 02/02/2023] Open
Abstract
The current study describes the construction of various ligand-based machine learning models to be used for drug-repurposing against the family of G-Protein Coupled Receptors (GPCRs). In building these models, we collected > 500,000 data points, encompassing experimentally measured molecular association data of > 160,000 unique ligands against > 250 GPCRs. These data points were retrieved from the GPCR-Ligand Association (GLASS) database. We have used diverse molecular featurization methods to describe the input molecules. Multiple supervised ML algorithms were developed, tested and compared for their accuracy, F scores, as well as for their Matthews' correlation coefficient scores (MCC). Our data suggest that combined with molecular fingerprinting, ensemble decision trees and gradient boosted trees ML algorithms are on the accuracy border of the rather sophisticated deep neural nets (DNNs)-based algorithms. On a test dataset, these models displayed an excellent performance, reaching a ~ 90% classification accuracy. Additionally, we showcase a few examples where our models were able to identify interesting connections between known drugs from the Drug-Bank database and members of the GPCR family of receptors. Our findings are in excellent agreement with previously reported experimental observations in the literature. We hope the models presented in this paper synergize with the currently ongoing interest of applying machine learning modeling in the field of drug repurposing and computational drug discovery in general.
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