An Evaluation of the Utility of Physiologically Based Models of Pharmacokinetics in Early Drug Discovery
Abstract
Generic physiologically-based models of pharmacokinetics were evaluated for early drug discovery. Plasma profiles after intravenous and oral dosing were simulated in rat for 68 compounds from six chemical classes. Input data consisted of structure based predictions of lipophilicity, ionization, and protein binding plus intrinsic clearance measured in rat hepatocytes, single measured values of aqueous solubility, and artificial membrane permeability. LogP of compounds was high with a mean of 3.9 while free fraction in plasma (mean 9%) and solubility (mean 37 microg/mL) were low. Predicted and observed clearance and volume showed mean fold-error and R2 of 1.8, 0.56, and 1.9, 0.25 respectively. Predicted bioavailability showed strong bias to under prediction correlated to very low aqueous solubility and a theoretical correction for bile salt solubilization in vivo brought some improvement in average prediction error (to 31%). Overall, this evaluation shows that generic simulation may be applicable for typical drug-like compounds to predict differences in pharmacokinetic parameters of more than twofold based upon minimal measured input data. However verification of the simulations with in vivo data for a few compounds of each compound class is recommended since recent discovery compounds may have properties beyond the scope of the current generic models.
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Accurate prediction of pharmacokinetics using many properties predicted from a structure may be possible but is not guaranteed, and verification with compounds from each chemical class has been recommended.
“Although accurate prediction of pharmacokinetics using many properties predicted from a structure may be possible [23], it is not guaranteed [24] and verification with compounds from each chemical class has been recommended [25].”
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- Authors
- Parrott, N., Paquereau, N., Coassolo, P., & Lavé, T.
- Affiliations
- F. Hoffmann-La Roche AG (CH)
- Corresponding author
- Parrott, Neil
- ORCID
- Parrott, Neil
- Venue
- Journal of Pharmaceutical Sciences
- Publisher
- Elsevier BV
- Published
- 2005-10
- Volume
- 94
- Issue
- 10
- Pages
- 2327-2343
- ISSN
- 0022-3549 (ISSN-L)
- OpenAlex
- W2039539582
- Cited by
- 107
- References
- 45
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 3 · 2023: 4 · 2022: 2 · 2021: 4 · 2020: 2 · 2019: 4 · 2018: 10 · 2017: 1 · 2016: 8 · 2015: 5 · 2014: 4 · 2013: 8 · 2012: 9
- FWCI
- 5.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Pharmaceutical Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Drug Solubulity and Delivery Systems
- Keywords
- physiologically based pharmacokinetic modeling, early drug discovery, bioavailability prediction, clearance prediction, volume of distribution, lipophilicity prediction, protein binding, water solubility, membrane permeability, rat hepatocytes, structure-based prediction
- MeSH terms
- Animals, Biological Availability, Computer Simulation, Pharmaceutical Preparations, Intestinal Absorption, Male, Models, Biological, Pharmacokinetics, Solubility, Time Factors, Drug Design, Reproducibility of Results, Rats, Wistar, Area Under Curve, Rats
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