{"title":"一期剂量递增设计的质量原则。","authors":"Jonathan M Siegel","doi":"10.1080/10543406.2025.2512988","DOIUrl":null,"url":null,"abstract":"<p><p>This paper discusses quality principles for Phase I model-based dose escalation design. It emphasizes that a loss function underlying a dose escalation trial estimator can be usefully interpreted as a quantified representation of the ethical assumptions underlying the treatment decisions to be made in the trial. Based on this principle, it discusses additional general quality design principles developers of clinical trial design methods should consider, including the role of continuous loss functions in quality per Taguchi, and per Deming the role of asymmetric loss functions and the importance of understanding the underlying process and its order of operations. It provides a number of model-based dose escalation designs as examples, including the mTPI as an introductory example, the EWOC design, and the CRM and modifications to it. It introduces some foundational scientific underpinnings and principles of quality philosophy, and explains how the principles apply to the examples. It stresses the importance of an engineering process by which a study is designed to meet identified and investigated user requirements.</p>","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1-9"},"PeriodicalIF":1.2000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quality principles in Phase I dose escalation design.\",\"authors\":\"Jonathan M Siegel\",\"doi\":\"10.1080/10543406.2025.2512988\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This paper discusses quality principles for Phase I model-based dose escalation design. It emphasizes that a loss function underlying a dose escalation trial estimator can be usefully interpreted as a quantified representation of the ethical assumptions underlying the treatment decisions to be made in the trial. Based on this principle, it discusses additional general quality design principles developers of clinical trial design methods should consider, including the role of continuous loss functions in quality per Taguchi, and per Deming the role of asymmetric loss functions and the importance of understanding the underlying process and its order of operations. It provides a number of model-based dose escalation designs as examples, including the mTPI as an introductory example, the EWOC design, and the CRM and modifications to it. It introduces some foundational scientific underpinnings and principles of quality philosophy, and explains how the principles apply to the examples. It stresses the importance of an engineering process by which a study is designed to meet identified and investigated user requirements.</p>\",\"PeriodicalId\":54870,\"journal\":{\"name\":\"Journal of Biopharmaceutical Statistics\",\"volume\":\" \",\"pages\":\"1-9\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2025-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biopharmaceutical Statistics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/10543406.2025.2512988\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biopharmaceutical Statistics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10543406.2025.2512988","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Quality principles in Phase I dose escalation design.
This paper discusses quality principles for Phase I model-based dose escalation design. It emphasizes that a loss function underlying a dose escalation trial estimator can be usefully interpreted as a quantified representation of the ethical assumptions underlying the treatment decisions to be made in the trial. Based on this principle, it discusses additional general quality design principles developers of clinical trial design methods should consider, including the role of continuous loss functions in quality per Taguchi, and per Deming the role of asymmetric loss functions and the importance of understanding the underlying process and its order of operations. It provides a number of model-based dose escalation designs as examples, including the mTPI as an introductory example, the EWOC design, and the CRM and modifications to it. It introduces some foundational scientific underpinnings and principles of quality philosophy, and explains how the principles apply to the examples. It stresses the importance of an engineering process by which a study is designed to meet identified and investigated user requirements.
期刊介绍:
The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers:
Drug, device, and biological research and development;
Drug screening and drug design;
Assessment of pharmacological activity;
Pharmaceutical formulation and scale-up;
Preclinical safety assessment;
Bioavailability, bioequivalence, and pharmacokinetics;
Phase, I, II, and III clinical development including complex innovative designs;
Premarket approval assessment of clinical safety;
Postmarketing surveillance;
Big data and artificial intelligence and applications.