Ordinary differential equation PK/PD models using the SAS macro NLINMIX.

Area of Science:

• Statistical modeling
• Computational statistics
• Pharmacokinetics

Background:

• Nonlinear mixed effects models are crucial for analyzing complex biological and pharmacokinetic data.
• Existing SAS macro NLINMIX provides a framework for these models.
• Integration with SAS/IML offers potential for enhanced computational flexibility.

Purpose of the Study:

• To describe theoretical advancements and practical enhancements to the SAS macro NLINMIX.
• To demonstrate the integration of NLINMIX with the SAS/IML language.
• To showcase the analysis of complex nonlinear mixed models, including those with no closed-form solutions.

Main Methods:

• Utilized the SAS macro NLINMIX, enhanced for integration with SAS/IML.
• Employed Laplace's approximation for nonlinear mixed effects models.
• Specified and analyzed a two-compartment kinetics model as a system of ordinary differential equations within SAS/IML.

Main Results:

• The enhanced NLINMIX, coupled with SAS/IML, provides increased flexibility and scope for model specification.
• Successfully fitted a complex two-compartment kinetics model without a closed-form representation.
• Demonstrated the capability to derive and specify models as solutions to systems of ordinary differential equations.

Conclusions:

• The integration of NLINMIX with SAS/IML significantly enhances the analysis of complex nonlinear mixed models.
• This approach facilitates the modeling of systems described by ordinary differential equations.
• The advancements offer a more powerful and flexible tool for researchers in various scientific domains.