Literature DB >> 21246315

The pharmacokinetic/pharmacodynamic pipeline: translating anticancer drug pharmacology to the clinic.

Qingyu Zhou1, James M Gallo.   

Abstract

Progress in an understanding of the genetic basis of cancer coupled to molecular pharmacology of potential new anticancer drugs calls for new approaches that are able to address key issues in the drug development process, including pharmacokinetic (PK) and pharmacodynamic (PD) relationships. The incorporation of predictive preclinical PK/PD models into rationally designed early-stage clinical trials offers a promising way to relieve a significant bottleneck in the drug discovery pipeline. The aim of the current review is to discuss some considerations for how quantitative PK and PD analyses for anticancer drugs may be conducted and integrated into a global translational effort, and the importance of examining drug disposition and dynamics in target tissues to support the development of preclinical PK/PD models that can be subsequently extrapolated to predict pharmacologic characteristics in patients. In this article, we describe three different physiologically based (PB) PK modeling approaches, i.e., the whole-body PBPK model, the hybrid PBPK model, and the two-pore model for macromolecules, as well as their applications. General conclusions are that greater effort should be made to generate more clinical data that could validate scaled preclinical PB-PK/PD tumor-based models and, thus, stimulate a framework for preclinical to clinical translation. Finally, given the innovative techniques to measure tissue drug concentrations and associated biomarkers of drug responses, development of predictive PK/PD models will become a standard approach for drug discovery and development.

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Year:  2011        PMID: 21246315      PMCID: PMC3032092          DOI: 10.1208/s12248-011-9253-1

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  69 in total

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Journal:  Nat Rev Cancer       Date:  2010-06-10       Impact factor: 60.716

2.  A combined pharmacokinetic-pharmacodynamic (PK-PD) model for tumor growth in the rat with UFT administration.

Authors:  Jong Hwan Sung; Anjali Dhiman; Michael L Shuler
Journal:  J Pharm Sci       Date:  2009-05       Impact factor: 3.534

3.  Clinical pharmacokinetics of erlotinib in patients with solid tumors and exposure-safety relationship in patients with non-small cell lung cancer.

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4.  Pharmacokinetic model-predicted anticancer drug concentrations in human tumors.

Authors:  James M Gallo; Paolo Vicini; Amy Orlansky; Shaolan Li; Feng Zhou; Jianguo Ma; Sharon Pulfer; Michel A Bookman; Ping Guo
Journal:  Clin Cancer Res       Date:  2004-12-01       Impact factor: 12.531

5.  Application of a generic physiologically based pharmacokinetic model to the estimation of xenobiotic levels in human plasma.

Authors:  F A Brightman; D E Leahy; G E Searle; S Thomas
Journal:  Drug Metab Dispos       Date:  2005-10-12       Impact factor: 3.922

Review 6.  High interstitial fluid pressure - an obstacle in cancer therapy.

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Journal:  Nat Rev Cancer       Date:  2004-10       Impact factor: 60.716

7.  The kinetics of methotrexate distribution in spontaneous canine lymphosarcoma.

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Journal:  J Pharmacokinet Biopharm       Date:  1975-04

8.  Prediction of active drug plasma concentrations achieved in cancer patients by pharmacodynamic biomarkers identified from the geo human colon carcinoma xenograft model.

Authors:  Feng R Luo; Zheng Yang; Huijin Dong; Amy Camuso; Kelly McGlinchey; Krista Fager; Christine Flefleh; David Kan; Ivan Inigo; Stephen Castaneda; Tai W Wong; Robert A Kramer; Robert Wild; Francis Y Lee
Journal:  Clin Cancer Res       Date:  2005-08-01       Impact factor: 12.531

Review 9.  The cancer genome.

Authors:  Michael R Stratton; Peter J Campbell; P Andrew Futreal
Journal:  Nature       Date:  2009-04-09       Impact factor: 49.962

Review 10.  Elimination mechanisms of therapeutic monoclonal antibodies.

Authors:  Mohammad A Tabrizi; Chih-Ming L Tseng; Lorin K Roskos
Journal:  Drug Discov Today       Date:  2006-01       Impact factor: 7.851

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  15 in total

1.  Physiologically based pharmacokinetic model for composite nanodevices: effect of charge and size on in vivo disposition.

Authors:  Donald E Mager; Vidhi Mody; Chao Xu; Alan Forrest; Wojciech G Lesniak; Shraddha S Nigavekar; Muhammed T Kariapper; Leah Minc; Mohamed K Khan; Lajos P Balogh
Journal:  Pharm Res       Date:  2012-06-12       Impact factor: 4.200

2.  Integration of Molecular, Cellular and Translational Researches in BioImpacts.

Authors:  Yadollah Omidi
Journal:  Bioimpacts       Date:  2011-06-09

3.  A hybrid model to evaluate the impact of active uptake transport on hepatic distribution of atorvastatin in rats.

Authors:  Priyanka Kulkarni; Ken Korzekwa; Swati Nagar
Journal:  Xenobiotica       Date:  2019-10-01       Impact factor: 1.908

Review 4.  Integrated PK-PD and agent-based modeling in oncology.

Authors:  Zhihui Wang; Joseph D Butner; Vittorio Cristini; Thomas S Deisboeck
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-01-15       Impact factor: 2.745

Review 5.  Array of translational systems pharmacodynamic models of anti-cancer drugs.

Authors:  Sihem Ait-Oudhia; Donald E Mager
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-10-22       Impact factor: 2.745

6.  Non-invasive, real-time reporting drug release in vitro and in vivo.

Authors:  Yanfeng Zhang; Qian Yin; Jonathan Yen; Joanne Li; Hanze Ying; Hua Wang; Yuyan Hua; Eric J Chaney; Stephen A Boppart; Jianjun Cheng
Journal:  Chem Commun (Camb)       Date:  2015-03-23       Impact factor: 6.222

7.  Combinatorial chemotherapeutic efficacy in non-Hodgkin lymphoma can be predicted by a signaling model of CD20 pharmacodynamics.

Authors:  John M Harrold; Robert M Straubinger; Donald E Mager
Journal:  Cancer Res       Date:  2012-02-20       Impact factor: 12.701

Review 8.  Musculoskeletal tumors: how to use anatomic, functional, and metabolic MR techniques.

Authors:  Laura M Fayad; Michael A Jacobs; Xin Wang; John A Carrino; David A Bluemke
Journal:  Radiology       Date:  2012-11       Impact factor: 11.105

9.  Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin.

Authors:  Dhaval K Shah; Nahor Haddish-Berhane; Alison Betts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-11-15       Impact factor: 2.745

Review 10.  Computational oncology--mathematical modelling of drug regimens for precision medicine.

Authors:  Dominique Barbolosi; Joseph Ciccolini; Bruno Lacarelle; Fabrice Barlési; Nicolas André
Journal:  Nat Rev Clin Oncol       Date:  2015-11-24       Impact factor: 66.675

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