Literature DB >> 18851702

Quantitative disease, drug, and trial models.

Jogarao V S Gobburu1, Lawrence J Lesko.   

Abstract

Quantitative disease-drug-trial models allow learning from prior experience and summarize the knowledge in a ready to apply format. Employing these models to plan future development is proposed as a powerful solution to improve pharmaceutical R&D productivity. The disease and trial models are, to a large extent, independent of the product, but the drug model is not. The goals are to apply the disease and trial models to future development and regulatory decisions, and publicly share them. We propose working definitions of these models, describe the various subcomponents, provide examples, and discuss the challenges and potential solutions for developing such models. Building useful disease-drug-trial models is a challenging task and cannot be achieved by any single organization. It requires a consorted effort by industry, academic, and regulatory scientists. We also describe the strategic goals of the FDA Pharmacometrics group.

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Year:  2009        PMID: 18851702     DOI: 10.1146/annurev.pharmtox.011008.145613

Source DB:  PubMed          Journal:  Annu Rev Pharmacol Toxicol        ISSN: 0362-1642            Impact factor:   13.820


  29 in total

1.  Structural models describing placebo treatment effects in schizophrenia and other neuropsychiatric disorders.

Authors:  Venkatesh Pilla Reddy; Magdalena Kozielska; Martin Johnson; An Vermeulen; Rik de Greef; Jing Liu; Geny M M Groothuis; Meindert Danhof; Johannes H Proost
Journal:  Clin Pharmacokinet       Date:  2011-07       Impact factor: 6.447

2.  Systems pharmacology: bridging systems biology and pharmacokinetics-pharmacodynamics (PKPD) in drug discovery and development.

Authors:  Piet H van der Graaf; Neil Benson
Journal:  Pharm Res       Date:  2011-05-11       Impact factor: 4.200

3.  Exposure-response analysis after subcutaneous administration of RBP-7000, a once-a-month long-acting Atrigel formulation of risperidone.

Authors:  Vijay Ivaturi; Mathangi Gopalakrishnan; Jogarao V S Gobburu; Weiyan Zhang; Yongzhen Liu; Christian Heidbreder; Celine M Laffont
Journal:  Br J Clin Pharmacol       Date:  2017-03-31       Impact factor: 4.335

4.  Exposure-response modeling of anti-depressant treatments: the confounding role of placebo effect.

Authors:  Navin Goyal; Roberto Gomeni
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-12-21       Impact factor: 2.745

5.  From in vitro EC₅₀ to in vivo dose-response for antiretrovirals using an HIV disease model. Part I: a framework.

Authors:  Jing Fang; Pravin R Jadhav
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-06-27       Impact factor: 2.745

6.  Towards regulatory endorsement of drug development tools to promote the application of model-informed drug development in Duchenne muscular dystrophy.

Authors:  Daniela J Conrado; Jane Larkindale; Alexander Berg; Micki Hill; Jackson Burton; Keith R Abrams; Richard T Abresch; Abby Bronson; Douglass Chapman; Michael Crowther; Tina Duong; Heather Gordish-Dressman; Lutz Harnisch; Erik Henricson; Sarah Kim; Craig M McDonald; Stephan Schmidt; Camille Vong; Xiaoxing Wang; Brenda L Wong; Florence Yong; Klaus Romero
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-05-24       Impact factor: 2.745

7.  Clinical trials in the era of personalized oncology.

Authors:  Michael L Maitland; Richard L Schilsky
Journal:  CA Cancer J Clin       Date:  2011-10-27       Impact factor: 508.702

8.  Development of a placebo effect model combined with a dropout model for bipolar disorder.

Authors:  Wan Sun; Thomas P Laughren; Hao Zhu; Guenther Hochhaus; Yaning Wang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-03-02       Impact factor: 2.745

Review 9.  The role of concentration-effect relationships in the assessment of QTc interval prolongation.

Authors:  Nicholas P France; Oscar Della Pasqua
Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

Review 10.  Moving from basic toward systems pharmacodynamic models.

Authors:  William J Jusko
Journal:  J Pharm Sci       Date:  2013-05-16       Impact factor: 3.534

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