Development of a computer program, MDGP, for population pharmacokinetic analysis written using ANSI C language on...

Area of Science:

• Pharmacokinetics and Pharmacometry
• Computational Biology
• Software Development

Background:

• Population pharmacokinetics (PPK) analysis is crucial for understanding drug behavior in diverse patient groups.
• Existing software for PPK analysis can be computationally intensive and may have limitations in model flexibility.
• Development of efficient and versatile computational tools is essential for advancing pharmacokinetic research.

Purpose of the Study:

• To introduce MDGP, a novel computer program designed for population pharmacokinetic analysis.
• To detail the methodologies and technical specifications of the MDGP software.
• To evaluate the performance of MDGP in comparison to established pharmacokinetic software.

Main Methods:

• MDGP utilizes maximum likelihood estimation with poly-dimensional normal distribution errors.
• Optimization algorithms including variable metric, direction set, conjugate gradient, and polytope methods are employed.
• The software is developed in ANSI C, ensuring broad platform compatibility and accessibility.

Main Results:

• MDGP successfully analyzes pharmacokinetic models described by algebraic, ordinary differential, and Laplace-transformed equations.
• Partial differential equations for model parameters are not required, simplifying model setup.
• Comparative analysis with NONMEM showed comparable calculation performance in terms of parameter estimation, convergence speed, and objective function values.

Conclusions:

• MDGP is a versatile and efficient tool for population pharmacokinetic analysis.
• The program's flexibility in model description and cross-platform compatibility enhance its utility.
• MDGP is a valuable addition to the toolkit for researchers analyzing complex pharmacokinetic models.