Huybrecht T'jollyn1, Jan Snoeys2, Jan Van Bocxlaer3, Lies De Bock3, Pieter Annaert4, Achiel Van Peer2, Karel Allegaert5, Geert Mannens2, An Vermeulen3,2, Koen Boussery3. 1. Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium. huybrecht.tjollyn@ugent.be. 2. Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium. 3. Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium. 4. Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, O&N2, Herestraat 49, Box 921, 3000, Louvain, Belgium. 5. Department of Development and Regeneration, KU Leuven and Neonatal Intensive Care Unit, University Hospital Leuven, 3000, Louvain, Belgium.
Abstract
BACKGROUND AND OBJECTIVE: Although the measurement of cytochrome P450 (CYP) contributions in metabolism assays is straightforward, determination of actual in vivo contributions might be challenging. How representative are in vitro for in vivo CYP contributions? This article proposes an improved strategy for the determination of in vivo CYP enzyme-specific metabolic contributions, based on in vitro data, using an in vitro-in vivo extrapolation (IVIVE) approach. Approaches are exemplified using tramadol as model compound, and CYP2D6 and CYP3A4 as involved enzymes. METHODS: Metabolism data for tramadol and for the probe substrates midazolam (CYP3A4) and dextromethorphan (CYP2D6) were gathered in human liver microsomes (HLM) and recombinant human enzyme systems (rhCYP). From these probe substrates, an activity-adjustment factor (AAF) was calculated per CYP enzyme, for the determination of correct hepatic clearance contributions. As a reference, tramadol CYP contributions were scaled-back from in vivo data (retrograde approach) and were compared with the ones derived in vitro. In this view, the AAF is an enzyme-specific factor, calculated from reference probe activity measurements in vitro and in vivo, that allows appropriate scaling of a test drug's in vitro activity to the 'healthy volunteer' population level. Calculation of an AAF, thus accounts for any 'experimental' or 'batch-specific' activity difference between in vitro HLM and in vivo derived activity. RESULTS: In this specific HLM batch, for CYP3A4 and CYP2D6, an AAF of 0.91 and 1.97 was calculated, respectively. This implies that, in this batch, the in vitro CYP3A4 activity is 1.10-fold higher and the CYP2D6 activity 1.97-fold lower, compared to in vivo derived CYP activities. CONCLUSION: This study shows that, in cases where the HLM pool does not represent the typical mean population CYP activities, AAF correction of in vitro metabolism data, optimizes CYP contributions in the prediction of hepatic clearance. Therefore, in vitro parameters for any test compound, obtained in a particular batch, should be corrected with the AAF for the respective enzymes. In the current study, especially the CYP2D6 contribution was found, to better reflect the average in vivo situation. It is recommended that this novel approach is further evaluated using a broader range of compounds.
BACKGROUND AND OBJECTIVE: Although the measurement of cytochrome P450 (CYP) contributions in metabolism assays is straightforward, determination of actual in vivo contributions might be challenging. How representative are in vitro for in vivo CYP contributions? This article proposes an improved strategy for the determination of in vivo CYP enzyme-specific metabolic contributions, based on in vitro data, using an in vitro-in vivo extrapolation (IVIVE) approach. Approaches are exemplified using tramadol as model compound, and CYP2D6 and CYP3A4 as involved enzymes. METHODS: Metabolism data for tramadol and for the probe substrates midazolam (CYP3A4) and dextromethorphan (CYP2D6) were gathered in human liver microsomes (HLM) and recombinant human enzyme systems (rhCYP). From these probe substrates, an activity-adjustment factor (AAF) was calculated per CYP enzyme, for the determination of correct hepatic clearance contributions. As a reference, tramadolCYP contributions were scaled-back from in vivo data (retrograde approach) and were compared with the ones derived in vitro. In this view, the AAF is an enzyme-specific factor, calculated from reference probe activity measurements in vitro and in vivo, that allows appropriate scaling of a test drug's in vitro activity to the 'healthy volunteer' population level. Calculation of an AAF, thus accounts for any 'experimental' or 'batch-specific' activity difference between in vitro HLM and in vivo derived activity. RESULTS: In this specific HLM batch, for CYP3A4 and CYP2D6, an AAF of 0.91 and 1.97 was calculated, respectively. This implies that, in this batch, the in vitro CYP3A4 activity is 1.10-fold higher and the CYP2D6 activity 1.97-fold lower, compared to in vivo derived CYP activities. CONCLUSION: This study shows that, in cases where the HLM pool does not represent the typical mean population CYP activities, AAF correction of in vitro metabolism data, optimizes CYP contributions in the prediction of hepatic clearance. Therefore, in vitro parameters for any test compound, obtained in a particular batch, should be corrected with the AAF for the respective enzymes. In the current study, especially the CYP2D6 contribution was found, to better reflect the average in vivo situation. It is recommended that this novel approach is further evaluated using a broader range of compounds.
Authors: V Subrahmanyam; A B Renwick; D G Walters; P J Young; R J Price; A P Tonelli; B G Lake Journal: Drug Metab Dispos Date: 2001-08 Impact factor: 3.922
Authors: Tuukka Saarikoski; Teijo I Saari; Nora M Hagelberg; Mikko Neuvonen; Pertti J Neuvonen; Mika Scheinin; Klaus T Olkkola; Kari Laine Journal: Eur J Clin Pharmacol Date: 2012-12-15 Impact factor: 2.953
Authors: Orphélie Lootens; Marthe De Boevre; Elke Gasthuys; Jan Van Bocxlaer; An Vermeulen; Sarah De Saeger Journal: Front Microbiol Date: 2022-08-29 Impact factor: 6.064