ADME Gene-Related Pharmacogenomic Labeling of FDA-Approved Drugs: Comparison with Clinical Pharmacogenetics Implementation Consortium (CPIC) Evidence Levels.

Pharmacogenomics (PGx) can facilitate the transition to patient-specific drug regimens and thus improve their efficacy and reduce toxicity. The aim of this study was to evaluate the overlap of PGx classification for drug absorption, distribution, metabolism, and elimination (ADME)-related genes in the U.S. Food and Drug Administration (FDA) PGx labeling and in the Clinical Pharmacogenetics Implementation Consortium (CPIC) database. FDA-approved drugs and PGx labeling for ADME genes were identified in the CPIC database. Drugs were filtered by their association with ADME (pharmacokinetics)-related genes, PGx FDA labeling class, and CPIC evidence level. FDA PGx labeling was classified as either actionable, informative, testing recommended, or testing required, and varying CPIC evidence levels as either A, B, C, or D. From a total of 442 ADME and non-ADME gene-drug pairs in the CPIC database, 273, 55, and 48 pairs were excluded for lack of FDA labeling, mixed CPIC evidence level provisional classification, and non-ADME gene-drug pairs, respectively. The 66 ADME gene-drug pairs were classified into the following categories: 10 (15%) informative, 49 (74%) actionable, 6 (9%) testing recommended, and 1 (2%) testing required. CYP2D6 was the most prevalent gene among the FDA PGx labeling. From the ADME gene-drug pairs with both FDA and CPIC PGx classification, the majority of the drugs were for depression, cancer, and pain medications. The ADME gene-drug pairs with FDA PGx labeling considerably overlap with CPIC classification; however, a large number of ADME gene-drug pairs have only CPIC evidence levels but not FDA classification. PGx actionable labeling was the most common classification, with CYP2D6 as the most prevalent ADME gene in the FDA PGx labeling. Health professionals can impact therapeutic outcomes via pharmacogenetic interventions by analyzing and reconciling the FDA labels and CPIC database.

Simulation of drug-drug interactions between breast cancer chemotherapeutic agents and antiemetic drugs.

BACKGROUND: Chemotherapy-induced nausea and vomiting are commonly experienced side effects in breast cancer (BCa) patients. Antiemetic drugs used in BCa treatment are either inhibitors or inducers of cytochrome P450 (CYP) enzymes, while anticancer drugs are metabolized by CYPs. OBJECTIVES: The purpose of the present work was to evaluate in silico drug-drug interaction (DDI) potential between BCa chemotherapeutic drugs and antiemetic agents. METHODS: The Drug-Drug Interaction™ module of GastroPlus™ was employed to assess CYP-related interactions between antiemetic and anticancer therapy combinations. The CYP inhibitory or inducing parameters (IC50, Ki, EC50) used in simulations were obtained from the literature. RESULTS: Analyses of twenty-three BCa drugs indicated that 22% of the chemotherapeutic drugs do not need an antiemetic agent due to their low emetogenicity, whereas 30% of the anticancer drugs are not metabolized by CYPs. The remaining eleven anticancer drugs metabolized by CYPs generated ninety-nine combinations with nine antiemetics. Simulation of DDIs suggest that about half of the pairs did not demonstrate any potential for DDI, whereas 30%, 10%, and 9% of the pairs showed weak, moderate, and strong interaction potential, respectively. In the present study, netupitant was the only antiemetic that showed strong inhibitory interactions (predicted AUC ratio > 5) with CYP3A4-metabolzied anticancer therapies (e.g., docetaxel, ribociclib, olaparib). Moderate to no interactions were observed with ondansetron, aprepitant, rolapitant, and dexamethasone in combination with anticancer agents. CONCLUSION: It is critical to recognize that these interactions can get amplified in cancer patients because of the severity of the disease and chemotherapy toxicities. Clinicians need to be aware of the DDI likelihood of the drug combinations used in BCa treatment.

Evaluation of pharmacogenomic evidence for drugs related to ADME genes in CPIC database.

OBJECTIVES: Clinical Pharmacogenetics Implementation Consortium (CPIC) is a platform that advances the pharmacogenomics (PGx) practice by developing evidence-based guidelines. The purpose of this study was to analyze the CPIC database for ADME related genes and their corresponding drugs, and evidence level for drug-gene pairs; and to determine the presence of these drug-gene pairs in the highest mortality diseases in the United States. METHODS: CPIC database was evaluated for drug-gene pairs related to absorption, distribution, metabolism, and excretion (ADME) properties. National Vital Statistics from Centers for Disease Control and Prevention was used to identify the diseases with the highest mortality. CPIC levels are assigned to different drug-gene pairs based on varying levels of evidence as either A, B, C, or D. All drug-gene pairs assigned with A/B, B/C, or C/D mixed levels were excluded from this study. A stepwise exclusion process was followed to determine the prevalence of various ADME drug-gene pairs among phase I/II enzymes or transporters and stratify the drug-gene pairs relevant to different disease conditions most commonly responsible for death in the United States. RESULTS: From a total of 442 drug-gene pairs in the CPIC database, after exclusion of 86 drug-gene pairs with levels A/B, B/C, or C/D, and 211 non-ADME related genes, 145 ADME related drug-gene pairs resulted. From the 145 ADME related drug-genes pairs, the following were the distribution of levels: Level A: 43 (30%), Level B: 22 (15%), Level C: 59 (41%), Level D: 21 (14%). The most prevalent ADME gene with CPIC level A classification was cytochrome P450 2C9 (CYP2C9) (26%) and overall, the most prevalent ADME gene in the CPIC database was CYP2D6 (30%). The most prevalent diseases related to the CPIC evidence related drugs were cancer and depression. CONCLUSIONS: We found that there is an abundance of ADME related genes in the CPIC database, including in the high mortality disease states of cancer and depression. There is a differential level of pharmacogenomic evidence in drug-gene pairs enlisted in CPIC where levels A and D having the greatest number of drug-gene pairs. CYP2D6 was the most common ADME gene with CPIC evidence for drug-gene pairs. Pharmacogenomic applications of CPIC evidence can be leveraged to individualize patient therapy and lower adverse effect events.

Association between Vitamin D Status and Risk of Developing Severe COVID-19 Infection: A Meta-Analysis of Observational Studies.

OBJECTIVE: The relationship between 25-hydroxyvitamin D3 (25(OH)D), the surrogate marker for vitamin D3, serum concentration and COVID-19 has come to the forefront as a potential pathway to improve COVID-19 outcomes. The current evidence remains unclear on the impact of vitamin D status on the severity and outcomes of COVID-19 infection. To explore possible association between low 25(OH)D levels and risk of developing severe COVID-19 (i.e. need for invasive mechanical ventilation, the length of hospital stay, total deaths). We also aimed to understand the relationship between vitamin D insufficiency and elevated inflammatory and cardiac biomarkers. METHODS: We conducted a comprehensive electronic literature search for any original research study published up to March 30, 2021. For the purpose of this review, low vitamin D status was defined as a range of serum total 25(OH)D levels of <10 to <30 ng/ml. Two independent investigators assessed study eligibility, synthesized evidence, analyzed, critically examined, and interpreted herein. RESULTS: Twenty-four observational studies containing 3637 participants were included in the meta-analysis. The mean age of the patients was 61.1 years old; 56% were male. Low vitamin D status was statistically associated with higher risk of death (RR, 1.60 (95% CI, 1.10-2.32), higher risk of developing severe COVID-19 pneumonia (RR: 1.50; 95% CI, 1.10-2.05). COVID-19 patients with low vitamin D levels had a greater prevalence of hypertension and cardiovascular diseases, abnormally high serum troponin and peak D-dimer levels, as well as elevated interleukin-6 and C-reactive protein than those with serum 25(OH)D levels ≥30 ng/ml. CONCLUSIONS: In this meta-analysis, we found a potential increased risk of developing severe COVID-19 infection among patients with low vitamin D levels. There are plausible biological mechanisms supporting the role of vitamin D in COVID-19 severity. Randomized controlled trials are needed to test for potential beneficial effects of vitamin D in COVID-19 outcomes.

ADME and Pharmacokinetic Properties of Remdesivir: Its Drug Interaction Potential.

On 11 March 2020, the World Health Organization (WHO) classified the Coronavirus Disease 2019 (COVID-19) as a global pandemic, which tested healthcare systems, administrations, and treatment ingenuity across the world. COVID-19 is caused by the novel beta coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Since the inception of the pandemic, treatment options have been either limited or ineffective. Remdesivir, a drug originally designed to be used for Ebola virus, has antiviral activity against SARS-CoV-2 and has been included in the COVID-19 treatment regimens. Remdesivir is an adenosine nucleotide analog prodrug that is metabolically activated to a nucleoside triphosphate metabolite (GS-443902). The active nucleoside triphosphate metabolite is incorporated into the SARS-CoV-2 RNA viral chains, preventing its replication. The lack of reported drug development and characterization studies with remdesivir in public domain has created a void where information on the absorption, distribution, metabolism, elimination (ADME) properties, pharmacokinetics (PK), or drug-drug interaction (DDI) is limited. By understanding these properties, clinicians can prevent subtherapeutic and supratherapeutic levels of remdesivir and thus avoid further complications in COVID-19 patients. Remdesivir is metabolized by both cytochrome P450 (CYP) and non-CYP enzymes such as carboxylesterases. In this narrative review, we have evaluated the currently available ADME, PK, and DDI information about remdesivir and have discussed the potential of DDIs between remdesivir and different COVID-19 drug regimens and agents used for comorbidities. Considering the nascent status of remdesivir in the therapeutic domain, extensive future work is needed to formulate safer COVID-19 treatment guidelines involving this medication.