CPhaMAS: An online platform for pharmacokinetic data analysis based on optimized parameter fitting algorithm

Area of Science:

• Pharmacology and Drug Development
• Computational Biology and Bioinformatics
• Biostatistics

Background:

• Clinical pharmacological modeling software is crucial but often has a steep learning curve.
• Existing algorithms struggle with individual differences and measurement errors, hindering accurate pharmacokinetic parameter estimation.
• There is a need for user-friendly tools with robust parameter fitting for drug development and personalized therapy.

Purpose of the Study:

• To develop an optimized parameter fitting algorithm that is less sensitive to initial values.
• To integrate this algorithm into a user-friendly online platform called CPhaMAS for pharmacokinetic data analysis.
• To evaluate the performance and accuracy of the CPhaMAS platform compared to existing software.

Main Methods:

• An optimized Nelder-Mead method was developed, featuring reinitialization of simplex vertices to avoid local solutions.
• The optimized algorithm was integrated into the CPhaMAS platform, which includes modules for compartment model analysis, non-compartment analysis (NCA), and bioequivalence/bioavailability (BE/BA) analysis.
• The CPhaMAS platform was evaluated and compared against the established WinNonlin software.

Main Results:

• CPhaMAS demonstrated ease of use, requiring no programming knowledge.
• The optimized Nelder-Mead method in CPhaMAS showed superior accuracy (lower mean relative error, higher R²) compared to WinNonlin in two-compartment and extravascular models, even with abnormal initial values.
• NCA parameter calculations in CPhaMAS had a mean relative error <0.0001%, and BE calculations for various drug types showed mean relative errors <0.01% for key parameters (Cmax, AUCt, AUCinf) compared to WinNonlin.

Conclusions:

• CPhaMAS is a user-friendly and accurate platform for pharmacokinetic data analysis.
• The integrated optimized algorithm enhances the reliability of parameter estimation.
• CPhaMAS serves as a valuable tool for drug development and precision medicine.