Taehong Kim, Jaeyun Cha, Hyeseon Jeon, Hwi-Yeol Yun, Dongju Lim, Jae Kyoung Kim
{"title":"Exact Formula of the Total Quasi-Steady State Approximation in Competitive Target-Mediated Drug Disposition.","authors":"Taehong Kim, Jaeyun Cha, Hyeseon Jeon, Hwi-Yeol Yun, Dongju Lim, Jae Kyoung Kim","doi":"10.34133/csbj.0223","DOIUrl":null,"url":null,"abstract":"<p><p>Competitive target-mediated drug disposition (competitive TMDD) arises when 2 drugs compete for the same target receptor. The full competitive TMDD model characterizes these dynamics; yet, its complexity motivated the use of a reduced model, which is invalid under high receptor concentrations. While this problem can be resolved by using the total quasi-steady state approximation, which remains valid for broad parameter regimes, the exact formula of the total quasi-steady state approximation-based reduced model-competitive qTMDD-remained unknown for 15 years, as it requires solving a cubic equation and identifying a biologically meaningful solution. Consequently, researchers have relied on computationally expensive numerical approximations, limiting practical applicability. Here, we derive-for the first time-a real-valued exact formula for competitive qTMDD by leveraging analytic properties of cubic equations and geometric characteristics of their roots in the complex plane. This formulation improved computational speed by approximately 18-fold compared to numerical approximation methods, enabling competitive qTMDD-based Bayesian inference that was previously impractical. Applied to clinical trial data for anakinra and rhIL-7-hyFc, competitive qTMDD estimated pharmacological parameters comparable to those from the full competitive TMDD model while requiring only approximately 28% of the computation time. Importantly, it maintains robust accuracy even at low sampling density, whereas previous reduced models exhibit bias. By ensuring precise biological interpretation of drug systems even in complex real-world scenarios, the exact formula of competitive qTMDD has the potential to streamline the drug development and clinical testing process. Our exact formula also consists entirely of real-valued terms, allowing seamless integration into existing pharmacometrics software.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"35 1","pages":"0223"},"PeriodicalIF":4.8000,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13646460/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and structural biotechnology journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.34133/csbj.0223","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Competitive target-mediated drug disposition (competitive TMDD) arises when 2 drugs compete for the same target receptor. The full competitive TMDD model characterizes these dynamics; yet, its complexity motivated the use of a reduced model, which is invalid under high receptor concentrations. While this problem can be resolved by using the total quasi-steady state approximation, which remains valid for broad parameter regimes, the exact formula of the total quasi-steady state approximation-based reduced model-competitive qTMDD-remained unknown for 15 years, as it requires solving a cubic equation and identifying a biologically meaningful solution. Consequently, researchers have relied on computationally expensive numerical approximations, limiting practical applicability. Here, we derive-for the first time-a real-valued exact formula for competitive qTMDD by leveraging analytic properties of cubic equations and geometric characteristics of their roots in the complex plane. This formulation improved computational speed by approximately 18-fold compared to numerical approximation methods, enabling competitive qTMDD-based Bayesian inference that was previously impractical. Applied to clinical trial data for anakinra and rhIL-7-hyFc, competitive qTMDD estimated pharmacological parameters comparable to those from the full competitive TMDD model while requiring only approximately 28% of the computation time. Importantly, it maintains robust accuracy even at low sampling density, whereas previous reduced models exhibit bias. By ensuring precise biological interpretation of drug systems even in complex real-world scenarios, the exact formula of competitive qTMDD has the potential to streamline the drug development and clinical testing process. Our exact formula also consists entirely of real-valued terms, allowing seamless integration into existing pharmacometrics software.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology