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Integration Analysis of Pharmacokinetics and Metabolomics to Predict Metabolic Phenotype and Drug Exposure of Remdesivir.

ABSTRACT: Remdesivir has displayed pharmacological activity against SARS-CoV-2. However, no pharmacometabolomics (PM) or correlation analysis with pharmacokinetics (PK) was revealed. Rats were intravenously administered remdesivir, and a series of blood samples were collected before and after treatment. Comprehensive metabolomics profile and PK were investigated and quantitated simultaneously using our previous reliable HPLC-MS/MS method. Both longitudinal and transversal metabolic analyses were conducted, and the correlation between PM and PK parameters was evaluated using Pearson's correlation analysis and the PLS model. Multivariate statistical analysis was employed for discovering candidate biomarkers which predicted drug exposure or toxicity of remdesivir. The prominent metabolic profile variation was observed between pre- and posttreatment, and significant changes were found in 65 metabolites. A total of 15 metabolites-12 carnitines, one N-acetyl-D-glucosamine, one allantoin, and one corticosterone-were significantly correlated with the concentration of Nuc (active metabolite of remdesivir). Adenosine, spermine, guanosine, sn-glycero-3-phosphocholine, and l-homoserine may be considered potential biomarkers for predicting drug exposure or toxicity. This study is the first attempt to apply PM and PK to study remdesivir response/toxicity, and the identified candidate biomarkers might be used to predict the AUC and C_max, indicating capability of discriminating good or poor responders. Currently, this study originally offers considerable evidence to metabolite reprogramming of remdesivir and sheds light on precision therapy development in fighting COVID-19.

SUBMITTER: Du P

PROVIDER: S-EPMC8766850 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWomen experience adverse drug reactions, ADRs, nearly twice as often as men, yet the role of sex as a biological factor in the generation of ADRs is poorly understood. Most drugs currently in use were approved based on clinical trials conducted on men, so women may be overmedicated. We determined whether sex differences in drug pharmacokinetics, PKs, predict sex differences in ADRs.MethodsSearches of the ISI Web of Science and PubMed databases were conducted with combinations of the terms: drugs, sex or gender, pharmacokinetics, pharmacodynamics, drug safety, drug dose, and adverse drug reaction, which yielded over 5000 articles with considerable overlap. We obtained information from each relevant article on significant sex differences in PK measures, predominantly area under the curve, peak/maximum concentrations, and clearance/elimination rates. ADRs were identified from every relevant article and recorded categorically as female-biased, male-biased, or not sex-biased.ResultsFor most of the FDA-approved drugs examined, elevated blood concentrations and longer elimination times were manifested by women, and these PKs were strongly linked to sex differences in ADRs. Of the 86 drugs evaluated, 76 had higher PK values in women; for 59 drugs with clinically identifiable ADRs, sex-biased PKs predicted the direction of sex-biased ADRs in 88% of cases. Ninety-six percent of drugs with female-biased PK values were associated with a higher incidence of ADRs in women than men, but only 29% of male-biased PKs predicted male-biased ADRs. Accessible PK information is available for only a small fraction of all drugs CONCLUSIONS: Sex differences in pharmacokinetics strongly predict sex-specific ADRs for women but not men. This sex difference was not explained by sex differences in body weight. The absence of sex-stratified PK information in public records for hundreds of drugs raises the concern that sex differences in PK values are widespread and of clinical significance. The common practice of prescribing equal drug doses to women and men neglects sex differences in pharmacokinetics and dimorphisms in body weight, risks overmedication of women, and contributes to female-biased adverse drug reactions. We recommend evidence-based dose reductions for women to counteract this sex bias.

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Integration Analysis of Pharmacokinetics and Metabolomics to Predict Metabolic Phenotype and Drug Exposure of Remdesivir.

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