Literature DB >> 26109076

A proposal for scientific framework enabling specific population drug dosing recommendations.

Pravin R Jadhav1, Jack Cook2, Vikram Sinha3, Ping Zhao3, Amin Rostami-Hodjegan4, Vaishali Sahasrabudhe2, Norman Stockbridge5, J Robert Powell6.   

Abstract

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.
© 2015, The American College of Clinical Pharmacology.

Entities:  

Keywords:  clinical pharmacology; dosing and administration; drug approval; drug development; labeling; modeling and simulation; specific populations

Mesh:

Year:  2015        PMID: 26109076     DOI: 10.1002/jcph.579

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  19 in total

1.  Translational Modeling and Simulation in Supporting Early-Phase Clinical Development of New Drug: A Learn-Research-Confirm Process.

Authors:  Dongyang Liu; Yi Zhang; Ji Jiang; John Choi; Xuening Li; Dalong Zhu; Dawei Xiao; Yanhua Ding; Hongwei Fan; Li Chen; Pei Hu
Journal:  Clin Pharmacokinet       Date:  2017-08       Impact factor: 6.447

Review 2.  Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation.

Authors:  Daniel Scotcher; Christopher Jones; Maria Posada; Aleksandra Galetin; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2016-08-09       Impact factor: 4.009

3.  Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation.

Authors:  Thomas M Polasek; Geoffrey T Tucker; Michael J Sorich; Michael D Wiese; Titus Mohan; Amin Rostami-Hodjegan; Porntipa Korprasertthaworn; Vidya Perera; Andrew Rowland
Journal:  Br J Clin Pharmacol       Date:  2018-01-11       Impact factor: 4.335

Review 4.  Proceedings of a Workshop: Precision Dosing: Defining the Need and Approaches to Deliver Individualized Drug Dosing in the Real-World Setting.

Authors:  Kimberly Maxfield; Lauren Milligan; Lingshan Wang; Daniel Gonzalez; Bernadette Johnson-Williams; Qi Liu; Rajanikanth Madabushi; Robert Powell; Yaning Wang; Hao Zhu; Issam Zineh
Journal:  Clin Pharmacol Ther       Date:  2020-07-14       Impact factor: 6.875

5.  Development of a Whole-Body Physiologically Based Pharmacokinetic Approach to Assess the Pharmacokinetics of Drugs in Elderly Individuals.

Authors:  Jan-Frederik Schlender; Michaela Meyer; Kirstin Thelen; Markus Krauss; Stefan Willmann; Thomas Eissing; Ulrich Jaehde
Journal:  Clin Pharmacokinet       Date:  2016-12       Impact factor: 6.447

6.  Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations.

Authors:  Daniel Scotcher; Christopher R Jones; Aleksandra Galetin; Amin Rostami-Hodjegan
Journal:  J Pharmacol Exp Ther       Date:  2017-01-05       Impact factor: 4.030

7.  Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model.

Authors:  L Kuepfer; C Niederalt; T Wendl; J-F Schlender; S Willmann; J Lippert; M Block; T Eissing; D Teutonico
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-10-19

8.  Systematic and quantitative assessment of the effect of chronic kidney disease on CYP2D6 and CYP3A4/5.

Authors:  K Yoshida; B Sun; L Zhang; P Zhao; D R Abernethy; T D Nolin; A Rostami-Hodjegan; I Zineh; S-M Huang
Journal:  Clin Pharmacol Ther       Date:  2016-03-07       Impact factor: 6.875

9.  Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance.

Authors:  Daniel Scotcher; Christopher Jones; Amin Rostami-Hodjegan; Aleksandra Galetin
Journal:  Eur J Pharm Sci       Date:  2016-03-28       Impact factor: 4.384

Review 10.  Reverse Translation in PBPK and QSP: Going Backwards in Order to Go Forward With Confidence.

Authors:  Amin Rostami-Hodjegan
Journal:  Clin Pharmacol Ther       Date:  2017-11-09       Impact factor: 6.875

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