Huang, Zhonghui;
Denti, Paolo;
Mistry, Hitesh;
Kloprogge, Frank;
(2024)
Machine Learning and Artificial Intelligence in PK-PD Modeling: Fad, Friend, or Foe?
Clinical Pharmacology & Therapeutics
10.1002/cpt.3165.
(In press).
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Abstract
Developing pharmacokinetic-pharmacodynamic (PK-PD) models requires a significant amount of time from highly skilled scientists and the demand for this expertise far outstrips the current supply. The use of machine learning (ML) and artificial intelligence (AL) in PK-PD modeling promises to reduce the number human supervision hours and improve predictive performance, but in its current form it suffers from various limitations. In this perspective, we aimed to structure the main trends and define boundaries and opportunities.
| Type: | Article |
|---|---|
| Title: | Machine Learning and Artificial Intelligence in PK-PD Modeling: Fad, Friend, or Foe? |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/cpt.3165 |
| Publisher version: | http://dx.doi.org/10.1002/cpt.3165 |
| Language: | English |
| Additional information: | Copyright © 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10185214 |
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