ArticleJournal of pharmacokinetics and pharmacodynamics2017
Target mediated drug disposition with drug-drug interaction, Part II: competitive and uncompetitive cases.
Article in Journal of pharmacokinetics and pharmacodynamics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Exact Formula of the Total Quasi-Steady State Approximation in Competitive Target-Mediated Drug Disposition.Computational and structural biotechnology journal · 2026Article
- Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.Journal of pharmacokinetics and pharmacodynamics · 2021Article
- Population pharmacokinetics and covariate analysis of Sym004, an antibody mixture against the epidermal growth factor receptor, in subjects with metastatic colorectal cancer and other solid tumors.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Target-Mediated Drug Disposition Model for Bispecific Antibodies: Properties, Approximation, and Optimal Dosing Strategy.CPT: pharmacometrics & systems pharmacology · 2019Article
- Asymptotic analysis of a TMDD model: when a reaction contributes to the destruction of its product.Journal of mathematical biology · 2018Article
- New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.The AAPS journal · 2018Article
- Target-mediated drug disposition with drug-drug interaction, Part I: single drug case in alternative formulations.Journal of pharmacokinetics and pharmacodynamics · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
We present competitive and uncompetitive drug-drug interaction (DDI) with target mediated drug disposition (TMDD) equations and investigate their pharmacokinetic DDI properties. For application of TMDD models, quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are necessary to reduce the number of parameters. To realize those approximations of DDI TMDD models, we derive an ordinary differential equation (ODE) representation formulated in free concentration and free receptor variables. This ODE formulation can be straightforward implemented in typical PKPD software without solving any non-linear equation system arising from the QE or QSS approximation of the rapid binding assumptions. This manuscript is the second in a series to introduce and investigate DDI TMDD models and to apply the QE or QSS approximation.
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Registered trials
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