Mechanisms and Predictions of Interindividual Variability in Drug Pharmacokinetics and Adverse Drug Reactions

Predictions of drug disposition and toxicity from preclinical data, estimation of risk of drug-drug interactions and simulation of drug exposures in humans are essential for safe and effective drug development and clinical pharmacology. Despite decades of research, significant gaps still remain in translating preclinical findings to clinical drug development and practice. As a result, about 90% of drug candidates that enter Phase I clinical trials fail during development. In addition, uncertainty regarding the disposition characteristics of approved drugs often remains after drug approval leading to post marketing studies and label revisions. This wastes resources, leads to unnecessary risk to patients and limits access to life saving medications for specific patient populations. My laboratory works to bridge the knowledge gaps in translational science via mechanistic in vitro studies, mass spectrometry based proteomics experiments and state-of-the art in silico modeling. We develop novel proteomics methods to understand formation of drug adducts by small molecule drugs, evaluate how drug-protein and protein-protein interactions within a cell alter drug distribution and the activity of drug metabolizing enzymes, and assess how genetic variability and individual biology such as sex, disease and age alter drug exposures in tissues and in blood. Central questions of my research program include: What mechanisms cause significant under and overpredictions of drug exposures and drug-drug interactions in humans? Which individual factors define interindividual variability in drug-protein adduct formation making certain individuals highly susceptible? What mechanisms lead to changes in drug clearance in specific populations and between individuals? Answering these questions will advance developing individualized therapy and enable connecting observable patient specific factors with decisions of drug dosage adjustments. Our long term goal is to improve the preclinical, translational and computational methodologies used to predict and evaluate drug disposition and adverse drug reactions. Our current studies are focused on 1) development of innovative proteomic methods for discovery, characterization and quantification of protein adducts in simple and complex biological matrices; 2) evaluation of the role of fatty acid binding proteins in modulating tissue drug distribution and drug clearance and 3) developing novel physiologically based pharmacokinetic models to predict drug disposition in specific populations including vulnerable patients. Our studies advance innovative areas such as how intracellular binding proteins influence drug efficacy, and provide unprecedented insight into mechanisms of enzyme inactivation and quantitative relationships between adduct formation and metabolic activity in the liver. Our research will also provide open and accessible cutting-edge tools for high-dimensional proteomics data and novel PBPK models for prediction of drug disposition in specific patient populations. Our work promises to decrease failure rate during drug development and lead to expanded access to approved medications in specific patient groups through improved quantitative systems biology approaches. Project Number: 1R35GM161276-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of General Medical Sciences (NIGMS) | Principal Investigator: Nina Isoherranen | Institution: UNIVERSITY OF WASHINGTON, SEATTLE, WA | Award Amount: $388,750 | Activity Code: R35 | Study Section: Special Emphasis Panel[ZRG1 MCST-G (56)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11258832