Improving the Accuracy of Predicted Human Pharmacokinetics: Lessons Learned from the AstraZeneca Drug Pipeline Over Two Decades

Davies, Michael, Jones, Rhys DO, Grime, Ken, Jansson-Lofmark, Rasmus, Fretland, Adrian J, Winiwarter, Susanne, Morgan, Paul and McGinnity, Dermot F (2020) Improving the Accuracy of Predicted Human Pharmacokinetics: Lessons Learned from the AstraZeneca Drug Pipeline Over Two Decades. TRENDS IN PHARMACOLOGICAL SCIENCES, 41 (6). pp. 390-408.

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Official URL: http://dx.doi.org/10.1016/j.tips.2020.03.004

Abstract

During drug discovery and prior to the first human dose of a novel candidate drug, the pharmacokinetic (PK) behavior of the drug in humans is predicted from preclinical data. This helps to inform the likelihood of achieving therapeutic exposures in early clinical development. Once clinical data are available, the observed human PK are compared with predictions, providing an opportunity to assess and refine prediction methods. Application of best practice in experimental data generation and predictive methodologies, and a focus on robust mechanistic understanding of the candidate drug disposition properties before nomination to clinical development, have led to maximizing the probability of successful PK predictions so that 83% of AstraZeneca drug development projects progress in the clinic with no PK issues; and 71% of key PK parameter predictions [64% of area under the curve (AUC) predictions; 78% of maximum concentration (C<sub>max</sub>) predictions; and 70% of half-life predictions] are accurate to within twofold. Here, we discuss methods to predict human PK used by AstraZeneca, how these predictions are assessed and what can be learned from evaluating the predictions for 116 candidate drugs.

Item Type:	Article
Uncontrolled Keywords:	Humans, Pharmacokinetics, Drug Discovery
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User:	Symplectic Admin
Date Deposited:	13 Jul 2021 14:54
Last Modified:	18 Jan 2023 21:36
DOI:	10.1016/j.tips.2020.03.004
Open Access URL:	https://www.cell.com/trends/pharmacological-scienc...
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3129898