Theoretical models in LC based bioanalytical method development

Area of Science:

• Analytical Chemistry
• Pharmaceutical Sciences
• Biochemistry

Background:

• Bioanalytical method development relies heavily on individual expertise and preferences.
• Developing selective and robust methods is crucial for accurate small molecule quantification.
• Matrix effects pose significant challenges in bioanalysis, impacting assay reliability.

Purpose of the Study:

• To review literature on mathematical models for LC-based bioanalytical method development.
• To provide equations and algorithms for modeling analytical methods.
• To discuss strategies for mitigating matrix effects in bioanalysis.

Main Methods:

• Literature review of mathematical modeling in bioanalytical method development.
• Compilation of relevant equations and algorithms for LC methods.
• Discussion of approaches to address matrix effects.

Main Results:

• Mathematical models can guide the selection of optimal conditions for method development.
• Models allow for approximate or detailed descriptions of analytical methods, incorporating variables.
• The review highlights solutions for managing matrix effects.

Conclusions:

• Mathematical modeling offers a structured approach to bioanalytical method development.
• Models facilitate the creation of robust and selective methods for small molecule quantification.
• This structured development aids in method control and future reproducibility.