Literature DB >> 20050847

On setting the first dose in man: quantitating biotherapeutic drug-target binding through pharmacokinetic and pharmacodynamic models.

Philip J Lowe1, Stacey Tannenbaum, Kai Wu, Peter Lloyd, Jennifer Sims.   

Abstract

Although the three (perhaps four) phases of clinical drug development are well known, it is relatively unappreciated that there are similar phases in pre-clinical development. These consist of 'Phase I' the initial, normally Research Discovery driven pharmacology; 'Phase II' non-good laboratory practice (GLP) dose range finding, followed by pivotal 'Phase III' GLP toxicology. Together with an array of in vitro experiments comparing species, these stages should enable an integrated safety assessment prior to entry into man, documenting to investigators and authorities evidence that the new pharmaceutic is unlikely to cause harm. Following the lessons learned from TeGenero TGN1412 and subsequent updates to regulatory guidelines, there are aspects peculiar to biotherapeutics, especially those that target key body systems, where calculations could be made for doses for human studies using pharmacokinetic and pharmacodynamic models. Two of these are exemplified in this paper. In the first, target-mediated drug disposition, where the binding of the drug to a cellular target quantitatively affects the pharmacokinetics, enables occupancy to be estimated without recourse to independent assays. In the second, assaying captured soluble target, as drug-target complexes, allows estimation of the concentration of the free ligand ensuring that in initial clinical studies, soluble targets are not overly suppressed. To support this methodology, it has been demonstrated using omalizumab, free and total IgE data that such analyses do predict the suppression of the free unbound ligand with reasonable accuracy. Overall, the objective of the process is to deliver a justification, through consideration of drug-target binding, of a safe starting and therapeutically relevant escalation doses for human studies.

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Year:  2009        PMID: 20050847     DOI: 10.1111/j.1742-7843.2009.00513.x

Source DB:  PubMed          Journal:  Basic Clin Pharmacol Toxicol        ISSN: 1742-7835            Impact factor:   4.080


  21 in total

Review 1.  Applications of human pharmacokinetic prediction in first-in-human dose estimation.

Authors:  Peng Zou; Yanke Yu; Nan Zheng; Yongsheng Yang; Hayley J Paholak; Lawrence X Yu; Duxin Sun
Journal:  AAPS J       Date:  2012-03-10       Impact factor: 4.009

2.  Properties of a general PK/PD model of antibody-ligand interactions for therapeutic antibodies that bind to soluble endogenous targets.

Authors:  Jasmine P Davda; Ryan J Hansen
Journal:  MAbs       Date:  2010-09-01       Impact factor: 5.857

3.  From target selection to the minimum acceptable biological effect level for human study: use of mechanism-based PK/PD modeling to design safe and efficacious biologics.

Authors:  Jing Yu; Helene Karcher; Adam L Feire; Philip J Lowe
Journal:  AAPS J       Date:  2011-02-19       Impact factor: 4.009

4.  Pharmacokinetic Steady-States Highlight Interesting Target-Mediated Disposition Properties.

Authors:  Johan Gabrielsson; Lambertus A Peletier
Journal:  AAPS J       Date:  2017-01-31       Impact factor: 4.009

5.  Storm forecasting: additional lessons from the CD28 superagonist TGN1412 trial.

Authors:  Christopher Horvath; Laura Andrews; Andreas Baumann; Lauren Black; Diann Blanset; Joy Cavagnaro; Kenneth L Hastings; David L Hutto; Timothy K MacLachlan; Mark Milton; Theresa Reynolds; Stan Roberts; Mark Rogge; Jennifer Sims; George Treacy; Garvin Warner; James D Green
Journal:  Nat Rev Immunol       Date:  2012-08-31       Impact factor: 53.106

Review 6.  Dose selection based on physiologically based pharmacokinetic (PBPK) approaches.

Authors:  Hannah M Jones; Kapil Mayawala; Patrick Poulin
Journal:  AAPS J       Date:  2012-12-27       Impact factor: 4.009

7.  Utility of immunodeficient mouse models for characterizing the preclinical pharmacokinetics of immunogenic antibody therapeutics.

Authors:  Maria Myzithras; Tammy Bigwarfe; Hua Li; Erica Waltz; Jennifer Ahlberg; Craig Giragossian; Simon Roberts
Journal:  MAbs       Date:  2016-09-06       Impact factor: 5.857

8.  Local versus systemic anti-tumour necrosis factor-α effects of adalimumab in rheumatoid arthritis: pharmacokinetic modelling analysis of interaction between a soluble target and a drug.

Authors:  David Stepensky
Journal:  Clin Pharmacokinet       Date:  2012-07-01       Impact factor: 6.447

9.  Qualification of a free ligand assay in the presence of anti-ligand antibody Fab fragments.

Authors:  Ryan J Hansen; Robin M Brown; Jirong Lu; Victor J Wroblewski
Journal:  MAbs       Date:  2013-02-08       Impact factor: 5.857

10.  A pre-clinical quantitative model predicts the pharmacokinetics/pharmacodynamics of an anti-BDCA2 monoclonal antibody in humans.

Authors:  Konstantinos Biliouris; Ivan Nestorov; Himanshu Naik; David Dai; Guangqing Xiao; Qin Wang; Alex Pellerin; Dania Rabah; Lawrence J Lesko; Mirjam N Trame
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-10-30       Impact factor: 2.745

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