Pharmacogenetics is nowadays increasingly incorporated in the clinic to better predict pharmacokinetics and optimize dosing regimens of drug treatments. While this approach has been successful and improved our prediction of drug metabolism, drug levels within patients may still commonly deviate between and within individuals. Phenoconversion described this mismatch between the genotype-based prediction of drug metabolism and the true capacity of an individual to metabolize drugs (phenotype) due to the presence of non-genetic factors [1, 2]. Phenoconversion may be a consequence of the use of concomitant medication or presence of comorbidities, such as inflammation. Although the influence of drug-drug interactions and inflammation on drug metabolism is established, it remains still unclear how pharmacogenetic variability may modulate the outcomes of these non-genetic factors on drug metabolism [2, 3]. To improve our understanding of the impact of phenoconversion we are currently investigating the interplay between pharmacogenetic variation and the effects of inflammation and drug-drug interactions in experimental liver models. For this research we are using human hepatocyte models (2D/3D) in which human drug metabolism can be adequately studied and (endogenous) genetic variation is conserved or can be introduced. This project will take place in close contact with collaborators (J. Swen) of the hospital pharmacy of the Leiden University Medical Center (LUMC) to facilitate translation of these findings to- and from the clinic. 1. Shah, R.R. and R.L. Smith, Addressing phenoconversion: the Achilles' heel of personalized medicine. Br J Clin Pharmacol, 2015. 79(2): p. 222-40. 2. Klomp, S.D., et al., Phenoconversion of Cytochrome P450 Metabolism: A Systematic Review. J Clin Med, 2020. 9(9). 3. de Jong, L.M., et al., Distinct Effects of Inflammation on Cytochrome P450 Regulation and Drug Metabolism: Lessons from Experimental Models and a Potential Role for Pharmacogenetics. Genes (Basel), 2020. 11(12).
- Laura de Jong