• Formulation
• Personalized medicine
• Pharmaceutical manufacturing
• Precision medicine

• Precision Medicine/methods
• Humans
• Pharmaceutical Preparations/chemistry
• Pharmaceutical Preparations/administration & dosage
• Drug Compounding/methods
• Drug Development/methods
• Technology, Pharmaceutical/methods
• Chemistry, Pharmaceutical/methods

• R16 GM149372 NIGMS NIH HHS
• R25 GM061838 NIGMS NIH HHS
• U54 MD007600 NIMHD NIH HHS

• 3D printing technology
• MENA region
• On-demand production
• Personalized medicine
• Pharmaceutical manufacturing
• Pharmaceutical research and development
• SPIRTAM®

• genetics research
• population genetics
• translational research

• OATP1B1
• OATP1B3
• cancer therapeutics
• pharmacokinetics
• polymorphism

• Merck Sharp and Dohme

• MATE1
• TKIs
• drug-drug interactions
• knockout mice
• renal elimination

• R01CA215802 NIH HHS
• P30 CA016058 NCI NIH HHS
• U24 CA247648 NCI NIH HHS
• R01 CA238946 NCI NIH HHS
• R01CA238946 NIH HHS

• cancer systems biology
• data-driven oncology
• in silico cancer systems oncology
• multi-scale cancer modeling
• personalized cancer therapeutics
• predictive systems oncology

• CPIC dosing recommendation
• HLA
• adverse drug reaction
• allele prediction
• bioinformatics
• next-generation sequencing
• pharmacogenomics
• variant analysis
• variant effect prediction
• web-based-tool

• HSRI.64-104 the Health Systems Research Institute (HSRI), Thailand
• P-19-51269 the National Science and Technology Development Agency (NSTDA), Thailand

Tenofovir alafenamide fumarate (TAF) was approved for HBV treatment in China in 2018. Despite higher antiviral efficacy and less impact on renal function and bone mineral density, the pharmacokinetic profiles of TAF are highly variable. The objectives of this study were to investigate the pharmacokinetics of TAF in the Chinese population and explore the associations between TAF and genetic polymorphisms and non-genetic factors.

A total of 64 healthy Chinese subjects aged 18~65 years old were planned to enroll. According to the dietary intake status, the subjects were divided into two groups (n = 32 per group). The concentrations of TAF and tenofovir were measured by HPLC-MS/MS, and the single-nucleotide polymorphisms were analyzed by MALDI-TOF MS.

All the enrolled participants (18–35 years) completed the clinical trial study. Similar to the results reported in other ethnic populations, the pharmacokinetic profiles of TAF and tenofovir were highly variable in the Chinese people, and the HFHC diet can significantly increase the systemic exposure of TAF. We determined both HFHC diet and rs7311358 (SLCO1B3) genotypes were independently associated with TAF AUC_0-t, while HFHC diet, age and rs3740066 (ABCC2) variants were predictive of t_1/2 of tenofovir (P < 0.05). The subjects with the AA genotype in rs7311358 had significantly higher TAF AUC_0-t values (1.15 times) than those with a G allele, and the t_1/2 of tenofovir in the rs3740066 TT genotype group was 1.23 times longer than that of CC genotype group. Furthermore, there was a trend of higher TAF AUC and shorter tenofovir t_1/2 for the rs2032582 (ABCB1) T allele and rs3742106 (ABCC4) CC variant, respectively, although not statistically significant in the multiple linear regression analysis.

This study provided new evidence to suggest a critical link between both genetic and non-genetic factors and TAF pharmacokinetics in the Chinese people.

• ABCB1
• ABCC2
• ABCC4
• SLCO1B3
• pharmacokinetics
• tenofovir alafenamide fumarate

Anthracyclines are one of the most widely used and effective chemotherapies in oncology, but their most important side effect is the cumulative, dose-related cardiotoxicity leading to congestive heart failure in ~5% of individuals. Methodology and pharmacogenetic studies for predicting which individuals are at high risk and subsequently the development of targeted and individualized cardioprotective plans are beginning to make progress. Here, we review current putative risk genes and variants, the strength of evidence for each genetic association and the interaction between risk genes, in the context of known clinical risk factors and potential novel cardioprotective strategies.

• Adriamycin
• CBR3
• TRPC6
• cardiomyopathy
• cardiotoxicity
• chemotherapy
• doxorubicin
• pharmacogenetics
• risk variants

Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children’s Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.

• best practice alerts (BPAs)
• clinical decision support (CDS)
• electronic health records (EHR)
• genomic indicators
• genotype
• pediatrics
• pharmacogenomics (PGx)
• phenotype

Organic cation transporter 1 (OCT1) is a transporter that regulates the hepatic uptake and subsequent elimination of diverse cationic compounds. Although OCT1 has been involved in drug-drug interactions and causes pharmacokinetic variability of many prescription drugs, details of the molecular mechanisms that regulate the activity of OCT1 remain incompletely understood. Based on an unbiased phospho-proteomics screen, we identified OCT1 as a tyrosine-phosphorylated transporter, and functional validation studies using genetic and pharmacological approaches revealed that OCT1 is highly sensitive to small molecules that target the protein kinase YES1, such as dasatinib. In addition, we found that dasatinib can inhibit hepatic OCT1 function in mice as evidenced from its ability to modulate levels of isobutyryl L-carnitine, a hepatic OCT1 biomarker identified from a targeted metabolomics analysis. These findings provide novel insight into the post-translational regulation of OCT1 and suggest that caution is warranted with polypharmacy regimes involving the combined use of OCT1 substrates and kinase inhibitors that target YES1.

• YES1 kinase
• drug-transporter interactions
• organic cation transporter 1
• post-translational modification
• tyrosine kinase inhibitors

• MIPD
• clinical decision support systems
• electronic health records
• individualized dosing
• model-informed precision dosing
• pharmacokinetic/pharmacodynamic modeling
• systems pharmacology

• health technology assessment
• precision medicine and diagnostics
• value frameworks

• Economics, Pharmaceutical
• Humans
• Precision Medicine/trends
• Technology Assessment, Biomedical

In recent years, Rutgers New Jersey Medical School Department of Family Medicine has integrated a quality assurance (QA) project as a required component of their 5-week medical student clerkship. This project requires each student to conduct a QA study at an assigned family practice and discuss the results with their preceptor. The aim of this study was to determine if sequential medical student QA projects impact physician readiness to improve guideline adherence over time.

A retrospective analysis of student reports was conducted to determine if physician readiness to improve compliance improved post implementation of the QA project using James Prochaska’s Transtheoretical Model of Behavioral Change. Fisher’s exact test or the χ² test were used as applicable to compare the change in results.

In academic year 2015–2016, there were 11 (6%) instances where physicians were precontemplating on change, 43 (24%) instances where physicians were contemplating, 101 (57%) instances where physicians were preparing to make change, 18 (10%) instances where physicians were acting, and 4 (2%) of instances where a physician were maintaining previous changes. The following year, the numbers were: 15 (8%), 38 (21%), 82 (46%), 34 (19%) and 11 (6%), respectively. There were increases of physicians in stages of precontemplation (p=0.047), action (p=0.02) and maintenance (p=0.047), a decrease in physicians that were in the stage of preparation (p=0.05) and no significant change in the instances they were in a stage of contemplation (p=0.60).

Student QA projects appear to leverage physician readiness to improve guideline adherence. Future studies will determine if raising awareness through these clerkship projects results in practice behavioural change.

• Clinical Clerkship/methods
• Clinical Clerkship/statistics & numerical data
• Education, Medical, Undergraduate/methods
• Family Practice/education
• Family Practice/methods
• Humans
• New Jersey
• Quality Assurance, Health Care/methods
• Quality Assurance, Health Care/statistics & numerical data
• Quality Improvement
• Retrospective Studies
• Students, Medical/psychology
• Students, Medical/statistics & numerical data

• Adverse drug reactions
• Anticancer
• Solute carrier
• Toxicity

• container virtualization
• pharmacogenomics
• precise medication

• Humans
• Pharmacogenetics
• Precision Medicine
• Software

• Genetic Variation/genetics
• Genome, Human/genetics
• High-Throughput Nucleotide Sequencing
• Human Genome Project
• Humans
• Linkage Disequilibrium
• Pharmacogenetics
• Pharmacogenomic Variants/genetics
• Polymorphism, Single Nucleotide/genetics
• Whole Genome Sequencing

• K99 HL116651 NHLBI NIH HHS
• U01 HL065899 NHLBI NIH HHS
• U01 HL105198 NHLBI NIH HHS

• Genomics
• Human Genome Project
• diagnosis
• gene therapy
• personalized medicine
• pharmacogenomics

• pharmacogenetics
• pharmacogenomics
• pharmaco-omics
• genomics
• adverse drug reactions
• drug efficacy
• precision medicine

• Drug-Related Side Effects and Adverse Reactions/prevention & control
• Genomics/methods
• Humans
• Pharmacogenetics/methods
• Precision Medicine

• U19 GM061388 NIGMS NIH HHS
• U54 GM114838 NIGMS NIH HHS
• R01 GM028157 NIGMS NIH HHS
• P50 CA116201 NCI NIH HHS
• R01 GM125633 NIGMS NIH HHS
• R01 CA196648 NCI NIH HHS

• Community advisory boards
• Informed consent
• Pharmaceutical industry
• Pharmacogenetics

• Gastric cancer
• bevacizumab
• monoclonal antibody
• ramucirumab
• trastuzumab

• Animals
• Antibodies, Monoclonal/therapeutic use
• Antibodies, Monoclonal, Humanized
• Bevacizumab/therapeutic use
• Clinical Trials as Topic/methods
• Humans
• Panitumumab
• Prognosis
• Stomach Neoplasms/diagnosis
• Stomach Neoplasms/drug therapy
• Stomach Neoplasms/immunology
• Treatment Outcome
• Ramucirumab

• adverse polypharmacology
• complex cellular network
• drug action
• pathophysiology
• personalized medicine
• pharmacokinetics/pharmacodynamics
• quantitative and systems pharmacology
• side effects
• systems biology
• systems pharmacology
• therapeutic polypharmacology
• virtual screening

It has been suggested that pharmacogenomic phenotypes are influenced by genetic variants with larger effect sizes than other phenotypes, such as complex disease risk. This is presumed to reflect the fact that relevant environmental factors (drug exposure) are appropriately measured and taken into account. To test this hypothesis, we performed a systematic comparison of effect sizes between pharmacogenomic and non-pharmacogenomic phenotypes across all genome-wide association studies (GWAS) reported in the NHGRI GWAS catalog. We found significantly larger effect sizes for studies focused on pharmacogenomic phenotypes, as compared to complex disease risk, morphological phenotypes, and endophenotypes. We found no significant differences in effect sizes between pharmacogenomic studies focused on adverse events versus those focused on drug efficacy. Furthermore, we found that this pattern persists among sample size-matched studies, suggesting that this pattern does not reflect over-estimation of effect sizes due to smaller sample sizes in pharmacogenomic studies.

• Blood Pressure/drug effects
• Gene Expression Regulation/physiology
• Genetic Association Studies
• Genetic Variation
• Humans
• Hypertension/genetics
• Kidney/physiopathology
• Polymorphism, Genetic
• Reactive Oxygen Species/metabolism
• Renin-Angiotensin System/drug effects
• Renin-Angiotensin System/physiology
• Sodium, Dietary/pharmacology

• R01 DK039308 NIDDK NIH HHS
• P01 HL068686 NHLBI NIH HHS
• R01 HL023081 NHLBI NIH HHS
• R01DK090918 NIDDK NIH HHS
• R01 DK090918 NIDDK NIH HHS
• P01HL068686 NHLBI NIH HHS
• R01DK039308 NIDDK NIH HHS
• R01 HL092196 NHLBI NIH HHS
• R01HL092196 NHLBI NIH HHS
• R37HL023081 NHLBI NIH HHS
• P01 HL074940 NHLBI NIH HHS
• P01HL074940 NHLBI NIH HHS

• R01 DK039308 NIDDK NIH HHS
• P01 HL068686 NHLBI NIH HHS
• R01 HL023081 NHLBI NIH HHS
• R01 DK090918 NIDDK NIH HHS
• R01 HL092196 NHLBI NIH HHS
• P01 HL074940 NHLBI NIH HHS

One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest. We use this strategy to compare the intellectual status and available evidence for two models or views of mechanisms of transmembrane drug transport into intact biological cells. One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose “natural” biological roles, and substrates are based in intermediary metabolism. Despite a recent review elsewhere, we can find no evidence able to support BDII as we can find no experiments in intact cells in which phospholipid bilayer diffusion was either varied independently or measured directly (although there are many papers where it was inferred by seeing a covariation of other dependent variables). By contrast, we find an abundance of evidence showing cases in which changes in the activities of named and genetically identified transporters led to measurable changes in the rate or extent of drug uptake. PBIN also has considerable predictive power, and accounts readily for the large differences in drug uptake between tissues, cells and species, in accounting for the metabolite-likeness of marketed drugs, in pharmacogenomics, and in providing a straightforward explanation for the late-stage appearance of toxicity and of lack of efficacy during drug discovery programmes despite macroscopically adequate pharmacokinetics. Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

• Recon2
• drug transporters
• pharmacogenomics
• systems pharmacology

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

• Type 2 diabetes
• Single nucleotide polymorphisms
• Expression quantitative trait locus
• Expression regulatory SNPs
• Gene-environment interaction
• Genome-wide association study

• R01 DK039311 NIDDK NIH HHS
• R01 DK090111 NIDDK NIH HHS

• Africa
• cytochrome P450
• genetic diversity
• genetics variation
• pharmacogenetics
• pharmacogenomics
• public health

• P50 HG003374 NHGRI NIH HHS
• R21 HG006612 NHGRI NIH HHS

• Animals
• Chromosome Mapping/methods
• Chromosome Mapping/trends
• Drug Design
• Genetic Predisposition to Disease/genetics
• Humans
• Pharmacogenetics/methods
• Pharmacogenetics/trends
• Sequence Analysis, DNA/methods
• Sequence Analysis, DNA/trends

• UL1 RR025774 NCRR NIH HHS
• UL1 TR000109 NCATS NIH HHS
• TR000109 NCATS NIH HHS