{"title":"动力学-药效学模型:应用、局限性和前景:系统综述","authors":"Leonardo Xavier, Sandro Filho, Izabel Alves","doi":"10.22541/au.169996507.76550842/v1","DOIUrl":null,"url":null,"abstract":"Pharmacometrics is instrumental in drug development, guiding decisions on dose selection, study design, formulation optimization, biomarker identification and commercial viability. While traditional Pharmacokinetic-Pharmacodynamic (PK/PD) modeling is widely embraced, Kinetic-Pharmacodynamic (KPD) modeling remains relatively underutilized. This paper introduces KPD modeling as an alternative approach for understanding dose-effect relationships in scenarios where conventional PK data is limited. KPD models use dose as the primary input to predict key parameters, offering a valuable tool for clinical applications. To explore KPD modeling’s scope and potential benefits, we conducted a systematic review following PRISMA guidelines. The research question was “Where can KPD modeling be applied, and what are the main outcomes from KPD models?”. We searched databases, including PubMed, Web of Science, Cochrane and EMBASE, using specific terms. Eligible articles had to be in english and discuss KPD modeling applications or its role in model development. Our review covered 132 articles published from January 2004 to October 2023, identifying 51 meeting inclusion criteria. Data included publication year, country, institution, study type, studied compounds, software tools, KPD applications, and outcomes. This paper presents a comprehensive analysis of reviewed studies, highlighting diverse KPD modeling applications in clinical and preclinical settings. It outlines limitations and suggests avenues for rational KPD integration into research, clinical trials, and regulatory approvals. By harnessing KPD modeling’s power, pharmacometrics can enhance decision-making, addressing challenges posed by limited PK data, ultimately advancing drug development and patient care.","PeriodicalId":487619,"journal":{"name":"Authorea (Authorea)","volume":"51 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"kinetic-pharmacodynamic models: applications, limitations and perspectives: A systematic review\",\"authors\":\"Leonardo Xavier, Sandro Filho, Izabel Alves\",\"doi\":\"10.22541/au.169996507.76550842/v1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pharmacometrics is instrumental in drug development, guiding decisions on dose selection, study design, formulation optimization, biomarker identification and commercial viability. While traditional Pharmacokinetic-Pharmacodynamic (PK/PD) modeling is widely embraced, Kinetic-Pharmacodynamic (KPD) modeling remains relatively underutilized. This paper introduces KPD modeling as an alternative approach for understanding dose-effect relationships in scenarios where conventional PK data is limited. KPD models use dose as the primary input to predict key parameters, offering a valuable tool for clinical applications. To explore KPD modeling’s scope and potential benefits, we conducted a systematic review following PRISMA guidelines. The research question was “Where can KPD modeling be applied, and what are the main outcomes from KPD models?”. We searched databases, including PubMed, Web of Science, Cochrane and EMBASE, using specific terms. Eligible articles had to be in english and discuss KPD modeling applications or its role in model development. Our review covered 132 articles published from January 2004 to October 2023, identifying 51 meeting inclusion criteria. Data included publication year, country, institution, study type, studied compounds, software tools, KPD applications, and outcomes. This paper presents a comprehensive analysis of reviewed studies, highlighting diverse KPD modeling applications in clinical and preclinical settings. It outlines limitations and suggests avenues for rational KPD integration into research, clinical trials, and regulatory approvals. By harnessing KPD modeling’s power, pharmacometrics can enhance decision-making, addressing challenges posed by limited PK data, ultimately advancing drug development and patient care.\",\"PeriodicalId\":487619,\"journal\":{\"name\":\"Authorea (Authorea)\",\"volume\":\"51 10\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Authorea (Authorea)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22541/au.169996507.76550842/v1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Authorea (Authorea)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22541/au.169996507.76550842/v1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
药物计量学在药物开发、指导剂量选择、研究设计、配方优化、生物标志物鉴定和商业可行性方面发挥着重要作用。虽然传统的药代动力学-药效学(PK/PD)模型被广泛接受,但动力学-药效学(KPD)模型仍然相对未得到充分利用。本文介绍了KPD建模作为在常规PK数据有限的情况下理解剂量效应关系的替代方法。KPD模型使用剂量作为预测关键参数的主要输入,为临床应用提供了有价值的工具。为了探索KPD建模的范围和潜在的好处,我们按照PRISMA指南进行了系统的回顾。研究的问题是“KPD模型可以应用在哪里,KPD模型的主要结果是什么?”我们搜索数据库,包括PubMed, Web of Science, Cochrane和EMBASE,使用特定的术语。合格的文章必须是英文的,并且讨论KPD建模应用程序或其在模型开发中的作用。我们的综述涵盖了2004年1月至2023年10月期间发表的132篇文章,确定了51篇符合纳入标准。数据包括出版年份、国家、机构、研究类型、研究化合物、软件工具、KPD应用和结果。本文介绍了综述研究的综合分析,突出了临床和临床前环境中不同的KPD建模应用。它概述了局限性,并提出了将KPD合理整合到研究、临床试验和监管批准中的途径。通过利用KPD建模的力量,药物计量学可以增强决策,解决有限的PK数据带来的挑战,最终推进药物开发和患者护理。
kinetic-pharmacodynamic models: applications, limitations and perspectives: A systematic review
Pharmacometrics is instrumental in drug development, guiding decisions on dose selection, study design, formulation optimization, biomarker identification and commercial viability. While traditional Pharmacokinetic-Pharmacodynamic (PK/PD) modeling is widely embraced, Kinetic-Pharmacodynamic (KPD) modeling remains relatively underutilized. This paper introduces KPD modeling as an alternative approach for understanding dose-effect relationships in scenarios where conventional PK data is limited. KPD models use dose as the primary input to predict key parameters, offering a valuable tool for clinical applications. To explore KPD modeling’s scope and potential benefits, we conducted a systematic review following PRISMA guidelines. The research question was “Where can KPD modeling be applied, and what are the main outcomes from KPD models?”. We searched databases, including PubMed, Web of Science, Cochrane and EMBASE, using specific terms. Eligible articles had to be in english and discuss KPD modeling applications or its role in model development. Our review covered 132 articles published from January 2004 to October 2023, identifying 51 meeting inclusion criteria. Data included publication year, country, institution, study type, studied compounds, software tools, KPD applications, and outcomes. This paper presents a comprehensive analysis of reviewed studies, highlighting diverse KPD modeling applications in clinical and preclinical settings. It outlines limitations and suggests avenues for rational KPD integration into research, clinical trials, and regulatory approvals. By harnessing KPD modeling’s power, pharmacometrics can enhance decision-making, addressing challenges posed by limited PK data, ultimately advancing drug development and patient care.