Literature DB >> 31132414

Better prediction of the local concentration-effect relationship: the role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development.

Sebastian Polak1, Zofia Tylutki2, Mark Holbrook3, Barbara Wiśniowska4.   

Abstract

Model-informed drug discovery and development (MID3) is an umbrella term under which sit several computational approaches: quantitative systems pharmacology (QSP), quantitative systems toxicology (QST) and physiologically based pharmacokinetics (PBPK). QSP models are built using mechanistic knowledge of the pharmacological pathway focusing on the putative mechanism of drug efficacy; whereas QST models focus on safety and toxicity issues and the molecular pathways and networks that drive these adverse effects. These can be mediated through exaggerated on-target or off-target pharmacology, immunogenicity or the physiochemical nature of the compound. PBPK models provide a mechanistic description of individual organs and tissues to allow the prediction of the intra- and extra-cellular concentration of the parent drug and metabolites under different conditions. Information on biophase concentration enables the prediction of a drug effect in different organs and assessment of the potential for drug-drug interactions. Together, these modelling approaches can inform the exposure-response relationship and hence support hypothesis generation and testing, compound selection, hazard identification and risk assessment through to clinical proof of concept (POC) and beyond to the market.
Copyright © 2019 Elsevier Ltd. All rights reserved.

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Year:  2019        PMID: 31132414     DOI: 10.1016/j.drudis.2019.05.016

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  6 in total

Review 1.  A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy.

Authors:  Ujwani Nukala; Marisabel Rodriguez Messan; Osman N Yogurtcu; Xiaofei Wang; Hong Yang
Journal:  AAPS J       Date:  2021-04-09       Impact factor: 4.009

Review 2.  Quantitative system pharmacology as a legitimate approach to examine extrapolation strategies used to support pediatric drug development.

Authors:  Karim Azer; Jeffrey S Barrett
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-05-24

Review 3.  Functional assays to assess the therapeutic potential of extracellular vesicles.

Authors:  Vivian V T Nguyen; Kenneth W Witwer; Marianne C Verhaar; Dirk Strunk; Bas W M van Balkom
Journal:  J Extracell Vesicles       Date:  2020-11-29

4.  Semi-PBPK Modeling and Simulation to Evaluate the Local and Systemic Pharmacokinetics of OC-01(Varenicline) Nasal Spray.

Authors:  Xiaofei Wu; Fan Zhang; Mengyang Yu; Faming Ding; Jinghui Luo; Bo Liu; Yuan Li; Zhiping Li; Hongyun Wang
Journal:  Front Pharmacol       Date:  2022-07-07       Impact factor: 5.988

Review 5.  Pharmacokinetics and Pharmacological Properties of Chloroquine and Hydroxychloroquine in the Context of COVID-19 Infection.

Authors:  Melanie R Nicol; Abhay Joshi; Matthew L Rizk; Philip E Sabato; Radojka M Savic; David Wesche; Jenny H Zheng; Jack Cook
Journal:  Clin Pharmacol Ther       Date:  2020-09-01       Impact factor: 6.903

Review 6.  Two heads are better than one: current landscape of integrating QSP and machine learning : An ISoP QSP SIG white paper by the working group on the integration of quantitative systems pharmacology and machine learning.

Authors:  Tongli Zhang; Ioannis P Androulakis; Peter Bonate; Limei Cheng; Tomáš Helikar; Jaimit Parikh; Christopher Rackauckas; Kalyanasundaram Subramanian; Carolyn R Cho
Journal:  J Pharmacokinet Pharmacodyn       Date:  2022-02-01       Impact factor: 2.745

  6 in total

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