Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series

Daga, Pankaj R.; Bolger, Michael B.; Haworth, Ian S.; Clark, Robert D.; Martin, Eric J.

doi:10.1021/acs.molpharmaceut.7b00972

Cited by 33Computational Drug Discovery MethodsDrug Solubulity and Delivery SystemsPharmacogenetics and Drug Metabolism

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series

Daga, Pankaj R., Bolger, Michael B., Haworth, Ian S., Clark, Robert D., Martin, Eric J.·2018·Molecular Pharmaceutics

DOI 10.1021/acs.molpharmaceut.7b00972

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Abstract

When medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties mainly by following experience and general rules of thumb. More quantitative models that predict %F of proposed compounds from chemical structure alone have proven elusive. Global empirical %F quantitative structure–property (QSPR) models perform poorly, and projects have too little data to train local %F QSPR models. Mechanistic oral absorption and physiologically based pharmacokinetic (PBPK) models simulate the dissolution, absorption, systemic distribution, and clearance of a drug in preclinical species and humans. Attempts to build global PBPK models based purely on calculated inputs have not achieved the <2-fold average error needed to guide lead optimization. In this work, local GastroPlus PBPK models are instead customized for individual medchem series. The key innovation was building a local QSPR for a numerically fitted effective intrinsic clearance (CL loc ). All inputs are subsequently computed from structure alone, so the models can be applied in advance of synthesis. Training CL loc on the first 15–18 rat %F measurements gave adequate predictions, with clear improvements up to about 30 measurements, and incremental improvements beyond that.

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PBPK modelling can be successfully applied in discovery with minimal data.
“Physiologically based pharmacokinetic modelling can be successfully applied in discovery with minimal data [26].”
From Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies (2019) · cites this paper as [26]
Predicting clearance during early discovery remains challenging.
“Predicting clearance during early discovery remains challenging [18, 26]; however, success was recently demonstrated by applying QSPR models within a chemical series [24, 26].”
From Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies (2019) · cites this paper as [26]
Success in predicting clearance during early discovery was recently demonstrated by applying QSPR models within a chemical series.
“Predicting clearance during early discovery remains challenging [18, 26]; however, success was recently demonstrated by applying QSPR models within a chemical series [24, 26].”
From Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies (2019) · cites this paper as [26]

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Authors: Daga, P. R., Bolger, M. B., Haworth, I. S., Clark, R. D., & Martin, E. J.
Affiliations: Novartis Institute of Biomedical Research, Emeryville, California 94608, United States
Simulations Plus (United States) (US)
University of Southern California (US)
ORCID: Daga, Pankaj R.
Bolger, Michael B.
Haworth, Ian S.
Clark, Robert D.
Martin, Eric J.
Venue: Molecular Pharmaceutics
Publisher: American Chemical Society (ACS)
Published: 2018-01-16
Volume: 15
Issue: 3
Pages: 821-830
ISSN: 1543-8384 (ISSN-L)
1543-8392
DOI: 10.1021/acs.molpharmaceut.7b00972
OpenAlex: W2783115227
Cited by: 33
References: 38
Citations by year: 2026: 2 · 2025: 2 · 2024: 6 · 2023: 4 · 2022: 5 · 2021: 3 · 2020: 4 · 2019: 4 · 2018: 3
FWCI: 2.80
Type: journal article
Language: en
Open access: closed
Locations: Molecular Pharmaceutics (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Drug Solubulity and Delivery Systems
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
Keywords: physiologically based pharmacokinetic modeling, GastroPlus, bioavailability prediction, lead optimization, oral absorption, structure-activity relationship
MeSH terms: Administration, Oral, Animals, Biological Availability, Chemistry, Pharmaceutical, Computer Simulation, Enzyme Inhibitors, Humans, Intestinal Absorption, Microsomes, Liver, Models, Biological, Tissue Distribution, Caco-2 Cells, Quantitative Structure-Activity Relationship, 11-beta-Hydroxysteroid Dehydrogenase Type 1, Rats, Proto-Oncogene Proteins c-pim-1, Drug Discovery, Datasets as Topic

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Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series

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