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Strategies for Determining Correct Cytochrome P450 Contributions in Hepatic Clearance Predictions: In Vitro-In Vivo Extrapolation as Modelling Approach and Tramadol as Proof-of Concept Compound.

Huybrecht T'jollynJan SnoeysJan Van BocxlaerLies De BockPieter AnnaertAchiel Van PeerKarel AllegaertGeert MannensAn VermeulenKoen Boussery
Published in: European journal of drug metabolism and pharmacokinetics (2018)
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.
Keyphrases
  • machine learning
  • electronic health record
  • big data
  • artificial intelligence