Literature DB >> 20978827

Quantitative clinical pharmacology is transforming drug regulation.

Carl C Peck1.   

Abstract

Prior to 1970s, development and regulation of new drugs was devoid of a fully quantitative, pathophysiological conceptual foundation. Malcolm Rowland pioneered, in collaboration with colleagues and friends, our modern understanding of drug clearance concepts, and equipped drug development and regulatory scientists with key investigative tools such as physiologically-based pharmacokinetic (PBPK) modeling, standardized approaches to characterizing drug metabolism, and microdosing. From the 1970s to the present, Malcolm Rowland has contributed to key advances in pharmacokinetics that have had transformational impacts on drug regulatory science. These advances include concepts that have led to the fundamental understanding that mechanistically derived, quantitative variations in drug concentrations, rather than assigned dosage alone, drive pharmacodynamic effects (PKPD)-including disease biomarkers and clinical outcomes. This body of knowledge has transformed drug development and regulatory science theory and practice from naïve empiricism to a mechanism/model-based, quantitative scientific discipline. As a result, it is now possible to incorporate pre-clinical in vitro data on drug physico-chemical properties, metabolizing enzymes, transporters and permeability properties into PBPK-based simulations of expected PK distributions and drug-drug interactions in human populations. The most comprehensive application of PK-PD is in the modeling and simulation of clinical trials in the context of model-based drug development and regulation, imbedded in the "learn-confirm paradigm". Regulatory agencies have embraced these advances and incorporated them into regulatory requirements, approval acceleration pathways and regulatory decisions. These developments are reviewed here, with emphasis on key contributions of Malcolm Rowland that facilitated this transformation.

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Year:  2010        PMID: 20978827     DOI: 10.1007/s10928-010-9171-3

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  49 in total

1.  Use of microdosing to predict pharmacokinetics at the therapeutic dose: experience with 5 drugs.

Authors:  Graham Lappin; Wilhelm Kuhnz; Roeline Jochemsen; Johannes Kneer; Ajai Chaudhary; Berend Oosterhuis; Willem Jan Drijfhout; Malcolm Rowland; R Colin Garner
Journal:  Clin Pharmacol Ther       Date:  2006-09       Impact factor: 6.875

2.  Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004-2006.

Authors:  Yaning Wang; A Venkatesh Bhattaram; Pravin R Jadhav; Lawrence J Lesko; Rajanikanth Madabushi; J Robert Powell; Wei Qiu; He Sun; Dong S Yim; Jenny J Zheng; Jogarao V S Gobburu
Journal:  J Clin Pharmacol       Date:  2008-02       Impact factor: 3.126

Review 3.  Drug interactions evaluation: an integrated part of risk assessment of therapeutics.

Authors:  Lei Zhang; Kellie S Reynolds; Ping Zhao; Shiew-Mei Huang
Journal:  Toxicol Appl Pharmacol       Date:  2010-01-04       Impact factor: 4.219

4.  An evaluation of the integration of pharmacokinetic and pharmacodynamic principles in clinical drug development. Experience within Hoffmann La Roche.

Authors:  B G Reigner; P E Williams; I H Patel; J L Steimer; C Peck; P van Brummelen
Journal:  Clin Pharmacokinet       Date:  1997-08       Impact factor: 6.447

5.  A dispersion model of hepatic elimination: 1. Formulation of the model and bolus considerations.

Authors:  M S Roberts; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1986-06

6.  Variation in biologic availability of digoxin from four preparations.

Authors:  J Lindenbaum; M H Mellow; M O Blackstone; V P Butler
Journal:  N Engl J Med       Date:  1971-12-09       Impact factor: 91.245

7.  Lidocaine disposition kinetics in monkey and man. I. Prediction by a perfusion model.

Authors:  N Benowitz; F P Forsyth; K L Melmon; M Rowland
Journal:  Clin Pharmacol Ther       Date:  1974-07       Impact factor: 6.875

8.  Quantitative structure-pharmacokinetics relationships: I. Development of a whole-body physiologically based model to characterize changes in pharmacokinetics across a homologous series of barbiturates in the rat.

Authors:  G E Blakey; I A Nestorov; P A Arundel; L J Aarons; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1997-06

9.  Phenylbutazone-warfarin interaction in man: further stereochemical and metabolic considerations.

Authors:  C Banfield; R O'Reilly; E Chan; M Rowland
Journal:  Br J Clin Pharmacol       Date:  1983-12       Impact factor: 4.335

10.  Quantitative evaluation of pharmacokinetic inhibition of CYP3A substrates by ketoconazole: a simulation study.

Authors:  Ping Zhao; Isabelle Ragueneau-Majlessi; Lei Zhang; John M Strong; Kellie S Reynolds; Rene H Levy; Kenneth E Thummel; Shiew-Mei Huang
Journal:  J Clin Pharmacol       Date:  2009-03       Impact factor: 3.126

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  9 in total

1.  Research priorities in pharmacokinetics.

Authors:  Geoffrey T Tucker
Journal:  Br J Clin Pharmacol       Date:  2012-06       Impact factor: 4.335

Review 2.  Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine.

Authors:  Clara Hartmanshenn; Megerle Scherholz; Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-09-19       Impact factor: 2.745

Review 3.  Antiretroviral pharmacology in mucosal tissues.

Authors:  Corbin G Thompson; Myron S Cohen; Angela D M Kashuba
Journal:  J Acquir Immune Defic Syndr       Date:  2013-07       Impact factor: 3.731

4.  Model Informed Pediatric Development Applied to Bilastine: Ontogenic PK Model Development, Dose Selection for First Time in Children and PK Study Design.

Authors:  Valvanera Vozmediano; Ander Sologuren; John C Lukas; Nerea Leal; Mónica Rodriguez
Journal:  Pharm Res       Date:  2017-10-02       Impact factor: 4.200

Review 5.  Systems pharmacology, pharmacogenetics, and clinical trial design in network medicine.

Authors:  Elliott Antman; Scott Weiss; Joseph Loscalzo
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2012-05-11

Review 6.  Physiologically based pharmacokinetic models: integration of in silico approaches with micro cell culture analogues.

Authors:  A Chen; M L Yarmush; T Maguire
Journal:  Curr Drug Metab       Date:  2012-07       Impact factor: 3.731

7.  White paper: landscape on technical and conceptual requirements and competence framework in drug/disease modeling and simulation.

Authors:  G Vlasakakis; E Comets; A Keunecke; I Gueorguieva; P Magni; N Terranova; O Della Pasqua; E C de Lange; C Kloft
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-05-01

Review 8.  Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Authors:  Eva Germovsek; Charlotte I S Barker; Mike Sharland; Joseph F Standing
Journal:  Clin Pharmacokinet       Date:  2019-01       Impact factor: 5.577

9.  Pharmacokinetic and Pharmacodynamic Relationship of Blinatumomab in Patients with Non-Hodgkin Lymphoma.

Authors:  Youssef Hijazi; Matthias Klinger; Andrea Kratzer; Benjamin Wu; Patrick A Baeuerle; Peter Kufer; Andreas Wolf; Dirk Nagorsen; Min Zhu
Journal:  Curr Clin Pharmacol       Date:  2018
  9 in total

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