Literature DB >> 20881214

Model-based drug development survey finds pharmacometrics impacting decision making in the pharmaceutical industry.

Julie A Stone1, Christopher Banfield, Marc Pfister, Stacey Tannenbaum, Sandy Allerheiligen, Jeffrey D Wetherington, Rajesh Krishna, Dennis M Grasela.   

Abstract

During the past decade, the pharmaceutical industry has seen the increasing application of pharmacometrics approaches in drug development. However, the full potential of incorporating model-based approaches in drug development and its impact on decision making has not been fully realized to date. In 2009, a survey on model-based drug development (MBDD) was conducted (1) to further understand the current state of MBDD in the pharmaceutical industry and (2) to identify opportunities to realize the full potential of MBDD. Ten large and mid-sized pharmaceutical companies provided responses to this survey. The results indicate that MBDD is achieving broad application in early and late development and is positively affecting both internal and regulatory decisions. Senior leadership (vice president and higher) within the companies indicated widely accepted utility for dose selection and gaining acceptance for study design and regulatory interactions but limited acceptance in discovery and commercial/pipeline decisions. Mounting appreciation for the impact of MBDD on internal and regulatory decision-making bodes well for the future of the pharmacometric discipline and the growth of opportunities to realize the full potential of MBDD.

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Year:  2010        PMID: 20881214     DOI: 10.1177/0091270010377628

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


  18 in total

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2.  Model based design and analysis of phase II HIV-1 trials.

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Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-07-11       Impact factor: 2.745

Review 3.  Dashboard systems: implementing pharmacometrics from bench to bedside.

Authors:  Diane R Mould; Richard N Upton; Jessica Wojciechowski
Journal:  AAPS J       Date:  2014-06-20       Impact factor: 4.009

Review 4.  Model-based clinical drug development in the past, present and future: a commentary.

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Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

5.  Delineating the effects of hot-melt extrusion on the performance of a polymeric film using artificial neural networks and an evolutionary algorithm.

Authors:  DeAngelo McKinley; Sravan Kumar Patel; Galit Regev; Lisa C Rohan; Ayman Akil
Journal:  Int J Pharm       Date:  2019-09-24       Impact factor: 5.875

6.  A tutorial on model informed approaches to cardiovascular safety with focus on cardiac repolarisation.

Authors:  S Y A Cheung; J Parkinson; U Wählby-Hamrén; C D Dota; Å M Kragh; L Bergenholm; T Vik; T Collins; C Arfvidsson; C E Pollard; H K Tomkinson; B Hamrén
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-05-07       Impact factor: 2.745

7.  Fuzzy optimization for detecting enzyme targets of human uric acid metabolism.

Authors:  Kai-Cheng Hsu; Feng-Sheng Wang
Journal:  Bioinformatics       Date:  2013-09-26       Impact factor: 6.937

8.  Improved Decision-Making Confidence Using Item-Based Pharmacometric Model: Illustration with a Phase II Placebo-Controlled Trial.

Authors:  Carolina Llanos-Paez; Claire Ambery; Shuying Yang; Maggie Tabberer; Misba Beerahee; Elodie L Plan; Mats O Karlsson
Journal:  AAPS J       Date:  2021-06-02       Impact factor: 4.009

9.  Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose.

Authors:  R J Keizer; M O Karlsson; A Hooker
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-06-26

10.  Modeling and simulation in clinical pharmacology and dose finding.

Authors:  A Staab; E Rook; M Maliepaard; L Aarons; C Benson
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-02-27
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