在临床实践中将群体药代动力学模型与精确用药相结合的建议方法。

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Monika Berezowska, Isaac S Hayden, Andrew M Brandon, Arsenii Zats, Mehzabin Patel, Shelby Barnett, Kayode Ogungbenro, Gareth J Veal, Alaric Taylor, Jugal Suthar
{"title":"在临床实践中将群体药代动力学模型与精确用药相结合的建议方法。","authors":"Monika Berezowska, Isaac S Hayden, Andrew M Brandon, Arsenii Zats, Mehzabin Patel, Shelby Barnett, Kayode Ogungbenro, Gareth J Veal, Alaric Taylor, Jugal Suthar","doi":"10.1111/bcp.16335","DOIUrl":null,"url":null,"abstract":"<p><p>Current methods of dose determination have contributed to suboptimal and inequitable health outcomes in underrepresented patient populations. The persistent demand to individualise patient treatment, alongside increasing technological feasibility, is leading to a growing adoption of model-informed precision dosing (MIPD) at point of care. Population pharmacokinetic (popPK) modelling is a technique that supports treatment personalisation by characterising drug exposure in diverse patient groups. This publication addresses this important shift in clinical approach, by collating and summarising recommendations from literature. It seeks to provide standardised guidelines on best practices for the development of popPK models and their use in MIPD software tools, ensuring the safeguarding and optimisation of patient outcomes. Moreover, it consolidates guidance from key regulatory and advisory bodies on MIPD software deployment, as well as technical requirements for electronic health record integration. It also considers the future application and clinical impact of machine learning algorithms in popPK and MIPD. Ultimately, this publication aims to facilitate the incorporation of high-quality precision-dosing solutions into standard clinical workflows, thereby enhancing the effectiveness of individualised dose selection at point of care.</p>","PeriodicalId":9251,"journal":{"name":"British journal of clinical pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice.\",\"authors\":\"Monika Berezowska, Isaac S Hayden, Andrew M Brandon, Arsenii Zats, Mehzabin Patel, Shelby Barnett, Kayode Ogungbenro, Gareth J Veal, Alaric Taylor, Jugal Suthar\",\"doi\":\"10.1111/bcp.16335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Current methods of dose determination have contributed to suboptimal and inequitable health outcomes in underrepresented patient populations. The persistent demand to individualise patient treatment, alongside increasing technological feasibility, is leading to a growing adoption of model-informed precision dosing (MIPD) at point of care. Population pharmacokinetic (popPK) modelling is a technique that supports treatment personalisation by characterising drug exposure in diverse patient groups. This publication addresses this important shift in clinical approach, by collating and summarising recommendations from literature. It seeks to provide standardised guidelines on best practices for the development of popPK models and their use in MIPD software tools, ensuring the safeguarding and optimisation of patient outcomes. Moreover, it consolidates guidance from key regulatory and advisory bodies on MIPD software deployment, as well as technical requirements for electronic health record integration. It also considers the future application and clinical impact of machine learning algorithms in popPK and MIPD. Ultimately, this publication aims to facilitate the incorporation of high-quality precision-dosing solutions into standard clinical workflows, thereby enhancing the effectiveness of individualised dose selection at point of care.</p>\",\"PeriodicalId\":9251,\"journal\":{\"name\":\"British journal of clinical pharmacology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British journal of clinical pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/bcp.16335\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British journal of clinical pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/bcp.16335","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

摘要

目前的剂量确定方法已导致代表性不足的患者群体无法获得最佳和不公平的健康结果。对患者治疗个性化的持续需求,以及技术可行性的不断提高,导致在医疗点越来越多地采用模型信息精准给药(MIPD)。群体药代动力学(popPK)建模是一种通过描述不同患者群体的药物暴露特征来支持个性化治疗的技术。本出版物通过整理和总结文献中的建议,探讨了临床方法的这一重要转变。它旨在为 popPK 模型的开发及其在 MIPD 软件工具中的使用提供标准化的最佳实践指南,确保保障和优化患者的治疗效果。此外,它还整合了主要监管和咨询机构对 MIPD 软件部署的指导,以及电子病历集成的技术要求。它还考虑了机器学习算法在 popPK 和 MIPD 中的未来应用和临床影响。最终,本出版物旨在促进将高质量的精准配药解决方案纳入标准临床工作流程,从而提高医疗点个体化剂量选择的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice.

Current methods of dose determination have contributed to suboptimal and inequitable health outcomes in underrepresented patient populations. The persistent demand to individualise patient treatment, alongside increasing technological feasibility, is leading to a growing adoption of model-informed precision dosing (MIPD) at point of care. Population pharmacokinetic (popPK) modelling is a technique that supports treatment personalisation by characterising drug exposure in diverse patient groups. This publication addresses this important shift in clinical approach, by collating and summarising recommendations from literature. It seeks to provide standardised guidelines on best practices for the development of popPK models and their use in MIPD software tools, ensuring the safeguarding and optimisation of patient outcomes. Moreover, it consolidates guidance from key regulatory and advisory bodies on MIPD software deployment, as well as technical requirements for electronic health record integration. It also considers the future application and clinical impact of machine learning algorithms in popPK and MIPD. Ultimately, this publication aims to facilitate the incorporation of high-quality precision-dosing solutions into standard clinical workflows, thereby enhancing the effectiveness of individualised dose selection at point of care.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
6.30
自引率
8.80%
发文量
419
审稿时长
1 months
期刊介绍: Published on behalf of the British Pharmacological Society, the British Journal of Clinical Pharmacology features papers and reports on all aspects of drug action in humans: review articles, mini review articles, original papers, commentaries, editorials and letters. The Journal enjoys a wide readership, bridging the gap between the medical profession, clinical research and the pharmaceutical industry. It also publishes research on new methods, new drugs and new approaches to treatment. The Journal is recognised as one of the leading publications in its field. It is online only, publishes open access research through its OnlineOpen programme and is published monthly.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信