Human hepatocytes and cytochrome P450-selective inhibitors predict variability in human drug exposure more accurately than human recombinant P450s.

Autor: Lindmark B; Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden., Lundahl A; Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden., Kanebratt KP; Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden., Andersson TB; Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden., Isin EM; Cardiovascular, Renal and Metabolism, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Gothenburg, Sweden.
Jazyk: angličtina
Zdroj: British journal of pharmacology [Br J Pharmacol] 2018 Jun; Vol. 175 (11), pp. 2116-2129. Date of Electronic Publication: 2018 Apr 19.
DOI: 10.1111/bph.14203
Abstrakt: Background and Purpose: Drugs metabolically eliminated by several enzymes are less vulnerable to variable compound exposure in patients due to drug-drug interactions (DDI) or if a polymorphic enzyme is involved in their elimination. Therefore, it is vital in drug discovery to accurately and efficiently estimate and optimize the metabolic elimination profile.
Experimental Approach: CYP3A and/or CYP2D6 substrates with well described variability in vivo in humans due to CYP3A DDI and CYP2D6 polymorphism were selected for assessment of fraction metabolized by each enzyme (fm CYP ) in two in vitro systems: (i) human recombinant P450s (hrP450s) and (ii) human hepatocytes combined with selective P450 inhibitors. Increases in compound exposure in poor versus extensive CYP2D6 metabolizers and by the strong CYP3A inhibitor ketoconazole were mathematically modelled and predicted changes in exposure were compared with in vivo data.
Key Results: Predicted changes in exposure were within twofold of reported in vivo values using fm CYP estimated in human hepatocytes and there was a strong linear correlation between predicted and observed changes in exposure (r 2  = 0.83 for CYP3A, r 2  = 0.82 for CYP2D6). Predictions using fm CYP in hrP450s were not as accurate (r 2  = 0.55 for CYP3A, r 2  = 0.20 for CYP2D6).
Conclusions and Implications: The results suggest that variability in human drug exposure due to DDI and enzyme polymorphism can be accurately predicted using fm CYP from human hepatocytes and CYP-selective inhibitors. This approach can be efficiently applied in drug discovery to aid optimization of candidate drugs with a favourable metabolic elimination profile and limited variability in patients.
(© 2018 The British Pharmacological Society.)
Databáze: MEDLINE
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