Literature DB >> 28918570

Mathematical description of drug-target interactions: application to biologics that bind to targets with two binding sites.

Leonid Gibiansky1, Ekaterina Gibiansky2.   

Abstract

The emerging discipline of mathematical pharmacology occupies the space between advanced pharmacometrics and systems biology. A characteristic feature of the approach is application of advance mathematical methods to study the behavior of biological systems as described by mathematical (most often differential) equations. One of the early application of mathematical pharmacology (that was not called this name at the time) was formulation and investigation of the target-mediated drug disposition (TMDD) model and its approximations. The model was shown to be remarkably successful, not only in describing the observed data for drug-target interactions, but also in advancing the qualitative and quantitative understanding of those interactions and their role in pharmacokinetic and pharmacodynamic properties of biologics. The TMDD model in its original formulation describes the interaction of the drug that has one binding site with the target that also has only one binding site. Following the framework developed earlier for drugs with one-to-one binding, this work aims to describe a rigorous approach for working with similar systems and to apply it to drugs that bind to targets with two binding sites. The quasi-steady-state, quasi-equilibrium, irreversible binding, and Michaelis-Menten approximations of the model are also derived. These equations can be used, in particular, to predict concentrations of the partially bound target (RC). This could be clinically important if RC remains active and has slow internalization rate. In this case, introduction of the drug aimed to suppress target activity may lead to the opposite effect due to RC accumulation.

Entities:  

Keywords:  Irreversible binding approximation; Mathematical pharmacology; Michaelis–Menten approximation; Nonlinear pharmacokinetics; Quasi-equilibrium approximation; Quasi-steady-state approximation; Target-mediated drug disposition; Targets with two binding sites

Mesh:

Substances:

Year:  2017        PMID: 28918570     DOI: 10.1007/s10928-017-9546-9

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  12 in total

1.  General pharmacokinetic model for drugs exhibiting target-mediated drug disposition.

Authors:  D E Mager; W J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-12       Impact factor: 2.745

2.  Dose correction for the Michaelis-Menten approximation of the target-mediated drug disposition model.

Authors:  Xiaoyu Yan; Wojciech Krzyzanski
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-01-04       Impact factor: 2.745

3.  Theoretical considerations of target-mediated drug disposition models: simplifications and approximations.

Authors:  Peiming Ma
Journal:  Pharm Res       Date:  2011-12-01       Impact factor: 4.200

4.  Target-mediated drug disposition model for drugs that bind to more than one target.

Authors:  Leonid Gibiansky; Ekaterina Gibiansky
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-07-29       Impact factor: 2.745

5.  Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition.

Authors:  Donald E Mager; Wojciech Krzyzanski
Journal:  Pharm Res       Date:  2005-09-22       Impact factor: 4.200

6.  Dynamics of target-mediated drug disposition: characteristic profiles and parameter identification.

Authors:  Lambertus A Peletier; Johan Gabrielsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-08-01       Impact factor: 2.745

7.  Nonlinear pharmacokinetics of therapeutic proteins resulting from receptor mediated endocytosis.

Authors:  Ben-Fillippo Krippendorff; Katharina Kuester; Charlotte Kloft; Wilhelm Huisinga
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-06-25       Impact factor: 2.745

Review 8.  Pharmacokinetic and pharmacodynamic properties of canakinumab, a human anti-interleukin-1β monoclonal antibody.

Authors:  Abhijit Chakraborty; Stacey Tannenbaum; Christiane Rordorf; Philip J Lowe; David Floch; Hermann Gram; Sandip Roy
Journal:  Clin Pharmacokinet       Date:  2012-06-01       Impact factor: 6.447

9.  A mathematical analysis of rebound in a target-mediated drug disposition model: II. With feedback.

Authors:  Philip J Aston; Gianne Derks; Balaji M Agoram; Piet H van der Graaf
Journal:  J Math Biol       Date:  2016-11-10       Impact factor: 2.259

10.  A Tutorial on Target-Mediated Drug Disposition (TMDD) Models.

Authors:  P Dua; E Hawkins; P H van der Graaf
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-06-15
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