From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools
Abstract
During the past decade, the pharmaceutical industry has invested considerably in technologies that have the potential to increase throughput in discovery projects. For large compound libraries, efficacy, availability and safety should be determined as early and as reliably as possible. The latest step in this effort is the implementation of in silico methods that combine and interpret (sometimes replace) experimental in vitro data. For ADME properties (absorption, distribution, metabolism and excretion) rational predictive models have been developed that rely on basic physicochemical input data and on mechanistic descriptions of the underlying biophysical and biochemical processes. Some of these models have become commercially available (e.g., GastroPlus: Simulations Plus; PK-Map, PK-Sim: Bayer Technology Services). The contribution of such models to an optimised research and development process will be discussed.
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In addition to the mechanistic models available in Simcyp for estimation of Kp values, the PK-Sim standard and Schmitt models can be applied in PK-Sim.
“In addition to the mechanistic models available in Simcyp for estimation of K p values, the PK‐Sim standard 45 and Schmitt 46 models can be applied in PK‐Sim.”
From Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction (2022) · cites this paper as [45]
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Rajput, A. J., Aldibani, H. K. A., & Rostami‐Hodjegan, A. (2023) · Biopharmaceutics & Drug Disposition · doi:10.1002/bdd.2357 · Cited by 12 · see citing works
Metabolism and pharmacokinetics in children and the elderly
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Integration of in vitro and in silico approaches enables prediction of drug-induced liver injury
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- Authors
- Willmann, S., Lippert, J., & Schmitt, W.
- Affiliations
- Bayer (Germany) (DE)
- Venue
- Expert Opinion on Drug Metabolism & Toxicology
- Publisher
- Informa UK Limited
- Published
- 2005-06
- Volume
- 1
- Issue
- 1
- Pages
- 159-168
- ISSN
- 1742-5255 (ISSN-L)
- 1744-7607
- OpenAlex
- W2031742675
- Cited by
- 140
- References
- 19
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 8 · 2023: 9 · 2022: 11 · 2021: 12 · 2020: 6 · 2019: 4 · 2018: 4 · 2017: 6 · 2016: 6 · 2015: 3 · 2014: 3 · 2013: 6 · 2012: 5
- FWCI
- 6.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Opinion on Drug Metabolism & Toxicology (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
- ADME prediction, absorption, distribution, metabolism, excretion, physicochemical properties, computational drug discovery, physiologically based pharmacokinetic modeling, GastroPlus, PK-Sim
- MeSH terms
- Animals, Drug Evaluation, Preclinical, Pharmaceutical Preparations, Humans, Intestinal Absorption, Predictive Value of Tests, Technology, Pharmaceutical, Computational Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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