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Mathematical Modeling of Bioassays.
D V Sotnikov1, A V Zherdev, B B Dzantiev
1Bach Institute of Biochemistry, Research Center for Biotechnology, Russian Academy of Sciences, Moscow, 119071, Russia. dzantiev@inbi.ras.ru.
Biochemistry. Biokhimiia
|March 11, 2018
Summary
This review classifies bioassays and compares mathematical models for ligand-receptor interactions. It emphasizes immunochemical analysis systems and provides recommendations for assay conditions and minimum detectable concentrations.
Area of Science:
- Biochemistry and Analytical Chemistry
- Biomolecular Interactions
- Assay Development
Background:
- Biological receptors' high affinity and specificity drive demand for analytical systems.
- Understanding theoretical concepts and quantitative parameters of ligand-receptor interactions is crucial.
- Existing mathematical models for bioassays lack comparative analysis and insights into their assumptions.
Purpose of the Study:
- To establish criteria for classifying various bioassay formats.
- To review and compare classical and contemporary bioassay models, focusing on immunochemical analysis.
- To discuss analytical and numerical modeling, minimum detectable concentrations, and optimal assay conditions.
Main Methods:
- Literature review of bioassay publications, emphasizing immunochemical systems.
- Development of a classification system for bioassays.
- Analysis of mathematical models, their assumptions, and predictive capabilities.
Main Results:
- A framework for classifying bioassays based on defined criteria is proposed.
- A comprehensive review highlights the strengths and limitations of various bioassay models.
- Discussion on the utility of analytical and numerical modeling in optimizing bioassays.
Conclusions:
- Comparative analysis of bioassay models is essential for selecting appropriate techniques.
- Understanding model assumptions aids in interpreting results and optimizing assay performance.
- Recommendations are provided for choosing assay conditions to achieve desired sensitivity and specificity.
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