Recent advances in computational metabolite structure predictions and altered metabolic pathways assessment to inform drug development processes

Abstract

Many drug candidates fail during preclinical and clinical trials due to variable or unexpected metabolism which may lead to variability in drug efficacy or adverse drug reactions. The drug metabolism field aims to address this important issue from many angles which range from the study of drug–drug interactions, pharmacogenomics, computational metabolic modeling, and others. This manuscript aims to provide brief but comprehensive manuscript summaries highlighting the conclusions and scientific importance of seven exceptional manuscripts published in recent years within the field of drug metabolism. Two main topics within the field are reviewed: novel computational metabolic modeling approaches which provide complex outputs beyond site of metabolism predictions, and experimental approaches designed to discern the impacts of interindividual variability and species differences on drug metabolism. The computational approaches discussed provide novel outputs in metabolite structure and formation likelihood and/or extend beyond the saturated field of drug phase I metabolism, while the experimental metabolic pathways assessments aim to highlight the impacts of genetic polymorphisms and clinical animal model metabolic differences on human metabolism and subsequent health outcomes.

Keywords:

• Computational modeling
• metabolism
• cytochromes P450
• interindividual variability
• drug–drug interactions
• genetic polymorphisms
• sites of metabolism (SoM)

Disclosure statement

The authors have no conflicts of interest to report.

Additional information

Funding

Schleiff is supported by the National Institute of General Medical Sciences [Award T32GM106999]. Sodhi was supported by an American Foundation for Pharmaceutical Education Predoctoral Fellowship, NIGMS grant [R25 GM56847] and a Louis Zeh Fellowship.