{"title":"贝叶斯药代动力学 I-II 期综合设计优化剂量安排方案","authors":"Mengyi Lu, Ying Yuan, Suyu Liu","doi":"10.1093/biostatistics/kxae034","DOIUrl":null,"url":null,"abstract":"The schedule of administering a drug has profound impact on the toxicity and efficacy profiles of the drug through changing its pharmacokinetics (PK). PK is an innate and indispensable component of the dose-schedule optimization. Motivated by this, we propose a Bayesian PK integrated dose-schedule finding (PKIDS) design to identify the optimal dose-schedule regime by integrating PK, toxicity, and efficacy data. Based on the causal pathway that dose and schedule affect PK, which in turn affects efficacy and toxicity, we jointly model the three endpoints by first specifying a Bayesian hierarchical model for the marginal distribution of the longitudinal dose-concentration process. Conditional on the drug concentration in plasma, we jointly model toxicity and efficacy as a function of the concentration. We quantify the risk-benefit of regimes using utility—continuously updating the estimates of PK, toxicity, and efficacy based on interim data—and make adaptive decisions to assign new patients to appropriate dose-schedule regimes via adaptive randomization. The simulation study shows that the PKIDS design has desirable operating characteristics.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Bayesian pharmacokinetics integrated phase I–II design to optimize dose-schedule regimes\",\"authors\":\"Mengyi Lu, Ying Yuan, Suyu Liu\",\"doi\":\"10.1093/biostatistics/kxae034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The schedule of administering a drug has profound impact on the toxicity and efficacy profiles of the drug through changing its pharmacokinetics (PK). PK is an innate and indispensable component of the dose-schedule optimization. Motivated by this, we propose a Bayesian PK integrated dose-schedule finding (PKIDS) design to identify the optimal dose-schedule regime by integrating PK, toxicity, and efficacy data. Based on the causal pathway that dose and schedule affect PK, which in turn affects efficacy and toxicity, we jointly model the three endpoints by first specifying a Bayesian hierarchical model for the marginal distribution of the longitudinal dose-concentration process. Conditional on the drug concentration in plasma, we jointly model toxicity and efficacy as a function of the concentration. We quantify the risk-benefit of regimes using utility—continuously updating the estimates of PK, toxicity, and efficacy based on interim data—and make adaptive decisions to assign new patients to appropriate dose-schedule regimes via adaptive randomization. The simulation study shows that the PKIDS design has desirable operating characteristics.\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2024-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1093/biostatistics/kxae034\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/biostatistics/kxae034","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
A Bayesian pharmacokinetics integrated phase I–II design to optimize dose-schedule regimes
The schedule of administering a drug has profound impact on the toxicity and efficacy profiles of the drug through changing its pharmacokinetics (PK). PK is an innate and indispensable component of the dose-schedule optimization. Motivated by this, we propose a Bayesian PK integrated dose-schedule finding (PKIDS) design to identify the optimal dose-schedule regime by integrating PK, toxicity, and efficacy data. Based on the causal pathway that dose and schedule affect PK, which in turn affects efficacy and toxicity, we jointly model the three endpoints by first specifying a Bayesian hierarchical model for the marginal distribution of the longitudinal dose-concentration process. Conditional on the drug concentration in plasma, we jointly model toxicity and efficacy as a function of the concentration. We quantify the risk-benefit of regimes using utility—continuously updating the estimates of PK, toxicity, and efficacy based on interim data—and make adaptive decisions to assign new patients to appropriate dose-schedule regimes via adaptive randomization. The simulation study shows that the PKIDS design has desirable operating characteristics.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.