The potential and pitfalls of artificial intelligence in clinical pharmacology

被引：16

作者：

Johnson, Martin ^{[1
]}

Patel, Mishal ^{[2
]}

Phipps, Alex ^{[1
]}

Van der Schaar, Mihaela ^{[3
,4
]}

Boulton, Dave ^{[5
]}

Gibbs, Megan ^{[5
]}

机构：

[1] AstraZeneca, Clin Pharmacol & Quantitat Pharmacol, Clin Pharmacol & Safety Sci, R&D, Cambridge, England

[2] AstraZeneca, Clin Pharmacol & Quantitat Pharmacol, Artificial Intelligence & Data Analyt, R&D, Cambridge, England

[3] Univ Cambridge, Cambridge Ctr Artificial Intelligence Med, Dept Appl Math & Theoret Phys, Cambridge, England

[4] Univ Cambridge, Dept Populat Hlth, Cambridge, England

[5] AstraZeneca, Clin Pharmacol & Quantitat Pharmacol, Clin Pharmacol & Safety Sci, R&D, 1 Medimmune Way, Gaithersburg, MD 20878 USA

来源：

CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY | 2023年 / 12卷 / 03期

关键词：

D O I：

10.1002/psp4.12902

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Artificial intelligence (AI) involves using data and algorithms to perform activities normally achieved through human intelligence. AI and its key component machine learning contextualize data and enhance decision making to transform how we operate, discover, and develop drugs. Transforming clinical pharmacology (CP) as AI-augmented CP (AI/CP) requires an ecosystem including digitized data collection, standardized processes, complementary technologies, and an ethical framework. This commentary aims to highlight the future perspectives of AI/CP in drug development.

引用

页码：279 / 284

页数：6

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