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Challenging the dose-response-time data approach: Analysis of a complex system.

Robert Andersson¹, Mats Jirstrand¹, Joachim Almquist¹

¹Fraunhofer-Chalmers Centre, Chalmers Science Park, Göteborg, Sweden.

European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences

|November 20, 2018

Summary

This dose-response-time meta-analysis shows that while accounting for missing exposure data introduces some bias, the nicotinic acid model remains robust. Optimal dosing strategies slightly differ, suggesting refined therapeutic approaches.

Keywords:

Adaptation Biophase functions Feedback control Free fatty acids (FFA)Insulin Nicotinic acid (NiAc)Turnover models

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Area of Science:

Pharmacology
Pharmacodynamics
Meta-analysis

Background:

Nicotinic acid is used to inhibit free fatty acids and insulin release.
Pharmacodynamic (PD) modeling is crucial for understanding drug effects.
Exposure data is often incomplete in complex PD systems.

Purpose of the Study:

To conduct a dose-response-time (DRT) meta-analysis of nicotinic acid.
To quantify the impact of missing exposure data in PD analysis.
To compare DRT modeling with exposure-driven analysis.

Main Methods:

Extensive DRT meta-analysis of nicotinic acid.
Characterization of individual and population-level response behaviors (delays, feedback, adaptation).
Comparison of DRT model with exposure-driven reference analysis.

Main Results:

The DRT model successfully characterized complex response behaviors.
Missing exposure data introduced bias and uncertainty in parameter estimates, though most were within one standard error.
Practical identifiability issues were noted for some parameters due to differing half-lives.
Optimal dosing strategies predicted by the DRT model showed a slightly lower optimal steady-state reduction of free fatty acids.

Conclusions:

DRT modeling provides a robust framework for analyzing complex pharmacodynamic systems, even with incomplete exposure data.
While bias exists, DRT meta-analysis offers valuable insights into drug behavior and optimal dosing.
Further research may refine parameter identifiability and optimize therapeutic strategies for nicotinic acid.