4.3 Review

Clinical pharmacology: Current innovations and future challenges

期刊

FUNDAMENTAL & CLINICAL PHARMACOLOGY
卷 36, 期 3, 页码 456-467

出版社

WILEY
DOI: 10.1111/fcp.12747

关键词

connected devices; drugs; machine learning; precision medicine; translational research; trials

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Clinical pharmacology focuses on studying the use of drugs in humans and aims to present innovative approaches that could transform drug development in the future. Reliable data on drug mechanism of action and rigorous study design are essential before conducting pharmacological studies in humans. Randomized controlled trials (RCTs) are currently the gold standard for evaluating drug efficacy, but alternative designs and new technologies show promise for improving drug development. Precision medicine may benefit from identifying new disease phenotypes and endotypes to determine new therapeutic targets and identify patients who respond to treatment or are at risk for adverse drug events. It is important to prioritize translational research, transparent sharing of clinical trial data, and enhanced interactions between drug experts, patients, and the general public.
Clinical pharmacology is the study of drugs in humans, from first-in-human studies to randomized controlled trials (RCTs) and benefit-risk ratio assessment in large populations. The objective of this review is to present the recent innovations that may revolutionize the development of drugs in the future. On behalf of the French Society of Pharmacology and Therapeutics, we provide recommendations to address those future challenges in clinical pharmacology. Whatever the future will be, robust preliminary data on drug mechanism of action and rigorous study design will remain crucial prior to the start of pharmacological studies in human. At the present time, RCTs remain the gold standard to evaluate the efficacy of human drugs, although alternative designs (pragmatic trials, platform trials, etc.) are emerging. Innovations in healthy volunteers' studies and the contribution of new technologies such as artificial intelligence, machine learning, and internet-based trials have the potential to improve drug development. In the field of precision medicine, new disease phenotypes and endotypes will probably help to identify new pharmacological targets, responders to therapies, and patients at risk for drug adverse events. In such a moving landscape, the development of translational research through academic and private partnership, transparent sharing of clinical trial data and enhanced interactions between drug experts, patients, and the general public are priority areas for action.

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