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- Title
Bridging the Worlds of Pharmacometrics and Machine Learning.
- Authors
Stankevičiūtė, Kamilė; Woillard, Jean-Baptiste; Peck, Richard W.; Marquet, Pierre; van der Schaar, Mihaela
- Abstract
Precision medicine requires individualized modeling of disease and drug dynamics, with machine learning-based computational techniques gaining increasing popularity. The complexity of either field, however, makes current pharmacological problems opaque to machine learning practitioners, and state-of-the-art machine learning methods inaccessible to pharmacometricians. To help bridge the two worlds, we provide an introduction to current problems and techniques in pharmacometrics that ranges from pharmacokinetic and pharmacodynamic modeling to pharmacometric simulations, model-informed precision dosing, and systems pharmacology, and review some of the machine learning approaches to address them. We hope this would facilitate collaboration between experts, with complementary strengths of principled pharmacometric modeling and flexibility of machine learning leading to synergistic effects in pharmacological applications.
- Subjects
MACHINE learning; INDIVIDUALIZED medicine; BRIDGES
- Publication
Clinical Pharmacokinetics, 2023, Vol 62, Issue 11, p1551
- ISSN
0312-5963
- Publication type
Article
- DOI
10.1007/s40262-023-01310-x