{"title":"Application of pharmacometrics in drug development","authors":"Yuan Xiong, Mahesh N. Samtani, Daniele Ouellet","doi":"10.1016/j.addr.2024.115503","DOIUrl":null,"url":null,"abstract":"The last two decades have witnessed profound changes in how advanced computational tools can help leverage tons of data to improve our knowledge, and ultimately reduce cost and increase productivity in drug development. Pharmacometrics has demonstrated its impact through model-informed drug development (MIDD) approaches. It is now an indispensable component throughout the whole continuum of drug discovery, development, regulatory review, and approval. Today, applications of pharmacometrics are common in designing better trials and accelerating evidence-based decisions. Newly emerging technologies, especially those from data and computer sciences, are being integrated with existing computational tools used in the pharmaceutical industry at a remarkably fast pace. The new challenges faced by the pharmacometrics community are not what or how to contribute, but which optimal MIDD strategy should be adopted to maximize its value in the decision-making process. While we are embracing new innovative approaches and tools, this article discusses how a variety of existing modeling tools, with differentiated advantages and focus, can work in concert to inform drug development.","PeriodicalId":7254,"journal":{"name":"Advanced drug delivery reviews","volume":"7 1","pages":""},"PeriodicalIF":15.2000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced drug delivery reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.addr.2024.115503","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
The last two decades have witnessed profound changes in how advanced computational tools can help leverage tons of data to improve our knowledge, and ultimately reduce cost and increase productivity in drug development. Pharmacometrics has demonstrated its impact through model-informed drug development (MIDD) approaches. It is now an indispensable component throughout the whole continuum of drug discovery, development, regulatory review, and approval. Today, applications of pharmacometrics are common in designing better trials and accelerating evidence-based decisions. Newly emerging technologies, especially those from data and computer sciences, are being integrated with existing computational tools used in the pharmaceutical industry at a remarkably fast pace. The new challenges faced by the pharmacometrics community are not what or how to contribute, but which optimal MIDD strategy should be adopted to maximize its value in the decision-making process. While we are embracing new innovative approaches and tools, this article discusses how a variety of existing modeling tools, with differentiated advantages and focus, can work in concert to inform drug development.
期刊介绍:
The aim of the Journal is to provide a forum for the critical analysis of advanced drug and gene delivery systems and their applications in human and veterinary medicine. The Journal has a broad scope, covering the key issues for effective drug and gene delivery, from administration to site-specific delivery.
In general, the Journal publishes review articles in a Theme Issue format. Each Theme Issue provides a comprehensive and critical examination of current and emerging research on the design and development of advanced drug and gene delivery systems and their application to experimental and clinical therapeutics. The goal is to illustrate the pivotal role of a multidisciplinary approach to modern drug delivery, encompassing the application of sound biological and physicochemical principles to the engineering of drug delivery systems to meet the therapeutic need at hand. Importantly the Editorial Team of ADDR asks that the authors effectively window the extensive volume of literature, pick the important contributions and explain their importance, produce a forward looking identification of the challenges facing the field and produce a Conclusions section with expert recommendations to address the issues.