Validating the accuracy of mathematical model-based pharmacogenomics dose prediction with real-world data.

IF 2.4 3区医学 Q3 PHARMACOLOGY & PHARMACY

European Journal of Clinical Pharmacology Pub Date : 2025-01-17 DOI:10.1007/s00228-025-03805-x

Yolande Saab, Zahi Nakad

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引用次数: 0

Abstract

Objective: The study aims to verify the usage of mathematical modeling in predicting patients' medication doses in association with their genotypes versus real-world data.

Methods: The work relied on collecting, extracting, and using real-world data on dosing and patients' genotypes. Drug metabolizing enzymes, i.e., cytochrome CYP 450, were the focus. A total number of 1914 subjects from 26 studies were considered, and CYP2D6 and CYP2C19 gene polymorphisms were used for the verification.

Results: Results show that the mathematical model was able to predict the reported optimal dosing of the values provided in the considered studies. Predicting patients' optimal doses circumvents trial and error in patients' treatments.

Discussion: The authors discussed the advantages of using a mathematical model in patients' dosing and identified multiple issues that would hinder the usability of raw data in the future, especially in the era of artificial intelligence (AI). The authors recommend that researchers and healthcare professionals use simple descriptive metabolic activity terms for patients and use allele activity scores for drug dosing rather than phenotype/genotype classifications.

Conclusion: The authors verified that a mathematical model could assist in providing data for better-informed decision-making in clinical settings and drug research and development.

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用真实世界数据验证基于数学模型的药物基因组学剂量预测的准确性。

目的：该研究旨在验证数学模型在预测患者药物剂量与他们的基因型和现实世界数据相关的使用。方法：这项工作依赖于收集、提取和使用有关剂量和患者基因型的真实数据。药物代谢酶，即细胞色素cyp450是重点。共纳入26项研究的1914名受试者，采用CYP2D6和CYP2C19基因多态性进行验证。结果：结果表明，该数学模型能够预测所考虑的研究中所提供的值的报告最佳给药量。预测患者的最佳剂量可以避免患者治疗中的反复试验。讨论：作者讨论了在患者给药中使用数学模型的优势，并确定了未来会阻碍原始数据可用性的多个问题，特别是在人工智能（AI）时代。作者建议研究人员和医疗保健专业人员对患者使用简单的描述性代谢活性术语，并使用等位基因活性评分来给药，而不是使用表型/基因型分类。结论：作者验证了数学模型可以帮助为临床环境和药物研发提供更明智的决策数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Journal of Clinical Pharmacology 医学-药学

CiteScore

5.40

自引率

3.40%

发文量

170

审稿时长

3-8 weeks

期刊介绍： The European Journal of Clinical Pharmacology publishes original papers on all aspects of clinical pharmacology and drug therapy in humans. Manuscripts are welcomed on the following topics: therapeutic trials, pharmacokinetics/pharmacodynamics, pharmacogenetics, drug metabolism, adverse drug reactions, drug interactions, all aspects of drug development, development relating to teaching in clinical pharmacology, pharmacoepidemiology, and matters relating to the rational prescribing and safe use of drugs. Methodological contributions relevant to these topics are also welcomed. Data from animal experiments are accepted only in the context of original data in man reported in the same paper. EJCP will only consider manuscripts describing the frequency of allelic variants in different populations if this information is linked to functional data or new interesting variants. Highly relevant differences in frequency with a major impact in drug therapy for the respective population may be submitted as a letter to the editor. Straightforward phase I pharmacokinetic or pharmacodynamic studies as parts of new drug development will only be considered for publication if the paper involves -a compound that is interesting and new in some basic or fundamental way, or -methods that are original in some basic sense, or -a highly unexpected outcome, or -conclusions that are scientifically novel in some basic or fundamental sense.