Jadhav Pravin R, Cook Jack, Sinha Vikram, Zhao Ping, Rostami-Hodjegan Amin, Sahasrabudhe Vaishali, Stockbridge Norman, Powell J Robert
Quantitative Pharmacology and Pharmacometrics, Merck and Co., Kenilworth, NJ, USA.
Clinical Pharmacology, Pfizer Inc., Groton, CT, USA.
J Clin Pharmacol. 2015 Oct;55(10):1073-8. doi: 10.1002/jcph.579. Epub 2015 Jul 30.
Over the last 3 decades, there has been little change in the paradigm to derive dosing recommendations for specific populations (e.g., renal failure, elderly, or obese patients) despite better understanding of clearance pathways in these groups and availability of modeling and simulation tools. Dosing recommendations for specific populations are often incomplete or unavailable at the time of drug approval. Currently, there is no regulatory framework to incorporate model-based dosing recommendations for specific populations. This paper proposes a scientific framework for using modeling and simulation to support specific population dosing recommendations. This framework creates a knowledgebase of drug and population attributes where model-based approaches can be developed to inform dosing recommendations. The framework may benefit patients by having reliable dosing information at the time of drug approval. Patients with conditions where studies are difficult to perform would benefit from dosing based on state-of-the-art knowledge. Industry and regulators would benefit from a scientific and efficient approach to improve specific population prediction. A research approach to determine specific population dose prediction is discussed along with challenges and risks. We hope to initiate a dialogue to explore the role of modeling based on data for drugs with similar clearance mechanisms to predict drug dosing.
在过去三十年里,尽管对特定人群(如肾衰竭患者、老年患者或肥胖患者)的清除途径有了更深入的了解,且有了建模和模拟工具,但在为这些特定人群制定给药建议的模式上几乎没有变化。在药物获批时,针对特定人群的给药建议往往不完整或根本没有。目前,尚无将基于模型的给药建议纳入特定人群的监管框架。本文提出了一个利用建模和模拟来支持特定人群给药建议的科学框架。该框架创建了一个药物和人群属性的知识库,在此基础上可以开发基于模型的方法来指导给药建议。该框架可能会让患者受益,因为在药物获批时就能获得可靠的给药信息。对于那些难以开展研究的病症患者,基于最新知识的给药方式会使其受益。行业和监管机构将从一种科学且高效的方法中受益,以改进对特定人群的预测。本文讨论了一种确定特定人群剂量预测的研究方法以及其中的挑战和风险。我们希望展开对话,探讨基于具有相似清除机制的药物数据进行建模在预测药物剂量方面的作用。