A proposal for scientific framework enabling specific population drug dosing recommendations. (30th July 2015)

• Record Type: Journal Article
• Authors: Jadhav, Pravin R.; Cook, Jack; Sinha, Vikram; Zhao, Ping; Rostami‐Hodjegan, Amin; Sahasrabudhe, Vaishali; Stockbridge, Norman; Powell, J. Robert
• Is Part Of: Journal of clinical pharmacology. Volume 55:Number 10(2015:Oct.)
• Page Start: 1073
• Page End: 1078
• Publication Date: 2015-07-30
• Subjects: Pharmacology -- Periodicals; Pharmacology -- Periodicals; Pharmacology, Clinical -- Periodicals; 615.1
• DOI: 10.1002/jcph.579
• Languages: English
• ISSNs: 0091-2700

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <sec id="jcph579-sec-0001" sec-type="section"> <p>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.</p> </sec> </abstract>