Literature DB >> 26464083

Towards integrative systems pharmacology models in oncology drug development.

J G Coen van Hasselt1, Piet H van der Graaf2.   

Abstract

Quantitative systems pharmacology (QSP) modeling represents an emerging area of value to further streamline knowledge integration and to better inform decision making processes in drug development. QSP models reside at the interface between systems biology models and pharmacological models, yet their concrete implementation still needs to be established further. This review outlines key modeling techniques in both of these areas and to subsequently discuss challenges and opportunities for further integration, in oncology drug development.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26464083     DOI: 10.1016/j.ddtec.2015.06.004

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  17 in total

1.  Quantitative systems pharmacology analysis of drug combination and scaling to humans: the interaction between noradrenaline and vasopressin in vasoconstriction.

Authors:  Anyue Yin; Akihiro Yamada; Wiro B Stam; Johan G C van Hasselt; Piet H van der Graaf
Journal:  Br J Pharmacol       Date:  2018-07-10       Impact factor: 8.739

Review 2.  Executable cancer models: successes and challenges.

Authors:  Matthew A Clarke; Jasmin Fisher
Journal:  Nat Rev Cancer       Date:  2020-04-27       Impact factor: 69.800

3.  A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations.

Authors:  Yumi Yamamoto; Pyry A Välitalo; Dirk-Jan van den Berg; Robin Hartman; Willem van den Brink; Yin Cheong Wong; Dymphy R Huntjens; Johannes H Proost; An Vermeulen; Walter Krauwinkel; Suruchi Bakshi; Vincent Aranzana-Climent; Sandrine Marchand; Claire Dahyot-Fizelier; William Couet; Meindert Danhof; Johan G C van Hasselt; Elizabeth C M de Lange
Journal:  Pharm Res       Date:  2016-11-18       Impact factor: 4.200

4.  Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines.

Authors:  Peter Blattmann; David Henriques; Michael Zimmermann; Fabian Frommelt; Uwe Sauer; Julio Saez-Rodriguez; Ruedi Aebersold
Journal:  Cell Syst       Date:  2017-12-06       Impact factor: 10.304

5.  Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.

Authors:  Helen E Benson; Steven Watterson; Joanna L Sharman; Chido P Mpamhanga; Andrew Parton; Christopher Southan; Anthony J Harmar; Peter Ghazal
Journal:  Br J Pharmacol       Date:  2017-11-26       Impact factor: 8.739

6.  Logic Modeling in Quantitative Systems Pharmacology.

Authors:  Pauline Traynard; Luis Tobalina; Federica Eduati; Laurence Calzone; Julio Saez-Rodriguez
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2017-07-29

7.  Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy.

Authors:  Robert C Jackson; Giovanni Y Di Veroli; Siang-Boon Koh; Ian Goldlust; Frances M Richards; Duncan I Jodrell
Journal:  PLoS Comput Biol       Date:  2017-05-03       Impact factor: 4.475

8.  Effects of Pharmacist-Led Clinical Pathway/Order Sets on Cancer Patients: A Systematic Review.

Authors:  Zhiyuan Tan; Zhiheng Yu; Ken Chen; Wei Liu; Rongsheng Zhao
Journal:  Front Pharmacol       Date:  2021-05-21       Impact factor: 5.810

Review 9.  Harvesting the promise of AOPs: An assessment and recommendations.

Authors:  Annamaria Carusi; Mark R Davies; Giovanni De Grandis; Beate I Escher; Geoff Hodges; Kenneth M Y Leung; Maurice Whelan; Catherine Willett; Gerald T Ankley
Journal:  Sci Total Environ       Date:  2018-02-22       Impact factor: 7.963

10.  Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

Authors:  Thomas J Snowden; Piet H van der Graaf; Marcus J Tindall
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-03-26       Impact factor: 2.745

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