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Theoretical models in LC based bioanalytical method development.

G Hendriks1

  • 1PRA international, early development services, P.O. box 200, 9407AE Zuidlaren, The Netherlands. HendriksGert@PRAintl.com

Journal of Pharmaceutical and Biomedical Analysis
|November 11, 2008
PubMed
Summary
This summary is machine-generated.

Mathematical models can optimize bioanalytical method development for small molecule quantification using liquid chromatography (LC). This approach enhances method selectivity, robustness, and addresses matrix effects for reliable analysis.

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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.