Literature DB >> 21320067

Pharmacodynamic-pharmacokinetic integration as a guide to medicinal chemistry.

Johan Gabrielsson1, Ola Fjellström, Johan Ulander, Michael Rowley, Piet H Van Der Graaf.   

Abstract

A primary objective of pharmacokinetic-pharmacodynamic (PKPD) reasoning is to identify key in vivo drug and system proper¬ties, enabling prediction of the magnitude and time course of drug responses under physiological and pathological conditions in animals and man. Since the pharmacological response generated by a drug is highly dependent on the actual system used to study its action, knowledge about its potency and efficacy at a given concentration or dose is insufficient to obtain a proper understanding of its pharmacodynamic profile. Hence, the output of PKPD activities extends beyond the provision of quantitative measures (models) of results, to the design of future protocols. Furthermore, because PKPD integrates DMPK (e.g. clearance) and pharmacology (e.g. potency),it provides an anchor point for compound selection, and, as such, should be viewed as an important weapon in medicinal chemistry. Here we outline key PK concepts relevant to PD, and then consider real-life experiments to illustrate the importance to the medicinal chemist of data obtained by PKPD. Useful assumptions and potential pitfalls are described, providing a holistic view of the plethora of determinants behind in vitro-in vivo correlations. By condensing complexity to simplicity, there are not only consequences for experimental design, and for the ranking and design of compounds, but it is also possible to make important predictions such as the impact of changes in drug potency and kinetics. In short, by using quantitative methods to tease apart pharmacodynamic complexities such as temporal differences and changes in plasma protein binding, it is possible to target the changes necessary for improving a compound's profile.

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Year:  2011        PMID: 21320067     DOI: 10.2174/156802611794480864

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  10 in total

1.  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

2.  Quantitative pharmacological analysis of antagonist binding kinetics at CRF1 receptors in vitro and in vivo.

Authors:  Simeon J Ramsey; Neil J Attkins; Rebecca Fish; Piet H van der Graaf
Journal:  Br J Pharmacol       Date:  2011-10       Impact factor: 8.739

3.  A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.

Authors:  Yadir A Guerrero; Diti Desai; Connor Sullivan; Erick Kindt; Mary E Spilker; Tristan S Maurer; Deepak E Solomon; Derek W Bartlett
Journal:  AAPS J       Date:  2020-03-02       Impact factor: 4.009

4.  Population PKPD modeling of BACE1 inhibitor-induced reduction in Aβ levels in vivo and correlation to in vitro potency in primary cortical neurons from mouse and guinea pig.

Authors:  Juliette Janson; Susanna Eketjäll; Karin Tunblad; Fredrik Jeppsson; Stefan Von Berg; Camilla Niva; Ann-Cathrin Radesäter; Johanna Fälting; Sandra A G Visser
Journal:  Pharm Res       Date:  2013-10-03       Impact factor: 4.200

Review 5.  Modeling, simulation, and translation framework for the preclinical development of monoclonal antibodies.

Authors:  Kenneth T Luu; Eugenia Kraynov; Bing Kuang; Paolo Vicini; Wei-Zhu Zhong
Journal:  AAPS J       Date:  2013-02-14       Impact factor: 4.009

Review 6.  Translational PK-PD modeling in pain.

Authors:  Ashraf Yassen; Paul Passier; Yasuhisa Furuichi; Albert Dahan
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-11-30       Impact factor: 2.745

7.  Parameter Identifiability of Fundamental Pharmacodynamic Models.

Authors:  David L I Janzén; Linnéa Bergenholm; Mats Jirstrand; Joanna Parkinson; James Yates; Neil D Evans; Michael J Chappell
Journal:  Front Physiol       Date:  2016-12-05       Impact factor: 4.566

8.  Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy.

Authors:  Vasudev Kantae; Elke H J Krekels; Michiel J Van Esdonk; Peter Lindenburg; Amy C Harms; Catherijne A J Knibbe; Piet H Van der Graaf; Thomas Hankemeier
Journal:  Metabolomics       Date:  2016-12-19       Impact factor: 4.290

Review 9.  Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

Authors:  Xiangfang L Li; Wasiu O Oduola; Lijun Qian; Edward R Dougherty
Journal:  Cancer Inform       Date:  2016-01-13

10.  Correlating Drug-Target Kinetics and In vivo Pharmacodynamics: Long Residence Time Inhibitors of the FabI Enoyl-ACP Reductase.

Authors:  Fereidoon Daryaee; Andrew Chang; Johannes Schiebel; Yang Lu; Zhuo Zhang; Kanishk Kapilashrami; Stephen G Walker; Caroline Kisker; Christoph A Sotriffer; Stewart L Fisher; Peter J Tonge
Journal:  Chem Sci       Date:  2016-05-25       Impact factor: 9.825

  10 in total

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