S Y A Cheung1, T Rodgers2, L Aarons3, I Gueorguieva4, G L Dickinson5, S Murby3, C Brown6, B Collins3, M Rowland3. 1. Quantitative Clinical Pharmacology, Early Clinical Development, iMED AstraZeneca, Cambridge, UK. 2. Icon Development Solutions, Manchester, UK. 3. Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, UK. 4. Eli Lilly, Surrey, UK. 5. Eli Lilly, Indianapolis, IN, USA. 6. Redx Pharma, Macclesfield, UK.
Abstract
BACKGROUND AND PURPOSE: Whole body physiologically based pharmacokinetic (PBPK) models have been increasingly applied in drug development to describe kinetic events of therapeutic agents in animals and humans. The advantage of such modelling is the ability to incorporate vast amounts of physiological information, such as organ blood flow and volume, to ensure that the model is as close to reality as possible. EXPERIMENTAL APPROACH: Previous PBPK model development of enantiomers of a series of seven racemic β-blockers, namely, acebutolol, betaxolol, bisoprolol, metoprolol, oxprenolol, pindolol and propranolol, together with S-timolol in rat was based on tissue and blood concentration data at steady state. Compounds were administered in several cassettes with the composition mix and blood and tissue sampling times determined using a D-optimal design. KEY RESULTS: Closed-loop PBPK models were developed initially based on the application of open loop forcing function models to individual tissues and compounds. For the majority of compounds and tissues, distribution kinetics was adequately characterized by perfusion rate-limited models. For some compounds in the testes and gut, a permeability rate-limited distribution model was required to best fit the data. Parameter estimates of the tissue-to-blood partition coefficient through fitting of individual enantiomers and of racemic pair were generally in agreement and also concur with those from previous steady-state experiments. CONCLUSIONS AND IMPLICATIONS: PBPK modelling is a very powerful tool to aid drug discovery and development of therapeutic agents in animals and humans. However, careful consideration of the assumptions made during the modelling exercise is essential.
BACKGROUND AND PURPOSE: Whole body physiologically based pharmacokinetic (PBPK) models have been increasingly applied in drug development to describe kinetic events of therapeutic agents in animals and humans. The advantage of such modelling is the ability to incorporate vast amounts of physiological information, such as organ blood flow and volume, to ensure that the model is as close to reality as possible. EXPERIMENTAL APPROACH: Previous PBPK model development of enantiomers of a series of seven racemic β-blockers, namely, acebutolol, betaxolol, bisoprolol, metoprolol, oxprenolol, pindolol and propranolol, together with S-timolol in rat was based on tissue and blood concentration data at steady state. Compounds were administered in several cassettes with the composition mix and blood and tissue sampling times determined using a D-optimal design. KEY RESULTS: Closed-loop PBPK models were developed initially based on the application of open loop forcing function models to individual tissues and compounds. For the majority of compounds and tissues, distribution kinetics was adequately characterized by perfusion rate-limited models. For some compounds in the testes and gut, a permeability rate-limited distribution model was required to best fit the data. Parameter estimates of the tissue-to-blood partition coefficient through fitting of individual enantiomers and of racemic pair were generally in agreement and also concur with those from previous steady-state experiments. CONCLUSIONS AND IMPLICATIONS: PBPK modelling is a very powerful tool to aid drug discovery and development of therapeutic agents in animals and humans. However, careful consideration of the assumptions made during the modelling exercise is essential.
Authors: Michael J Curtis; Richard A Bond; Domenico Spina; Amrita Ahluwalia; Stephen P A Alexander; Mark A Giembycz; Annette Gilchrist; Daniel Hoyer; Paul A Insel; Angelo A Izzo; Andrew J Lawrence; David J MacEwan; Lawrence D F Moon; Sue Wonnacott; Arthur H Weston; John C McGrath Journal: Br J Pharmacol Date: 2015-07 Impact factor: 8.739
Authors: S Y A Cheung; T Rodgers; L Aarons; I Gueorguieva; G L Dickinson; S Murby; C Brown; B Collins; M Rowland Journal: Br J Pharmacol Date: 2017-12-01 Impact factor: 8.739