Response Surface Analysis and Nonlinear Optimization Algorithm for Maximization of Clinical Drug Performance: Application to Extended-Release and Long-Acting Injectable Paliperidone

Journal of Clinical Pharmacology
Roberto GomeniMaurizio Fava

Abstract

Model-based approach is recognized as a tool to make drug development more productive and to better support regulatory and therapeutic decisions. The objective of this study was to develop a novel model-based methodology based on the response surface analysis and a nonlinear optimizer algorithm to maximize the clinical performances of drug treatments. The treatment response was described using a drug-disease model accounting for multiple components such as the dosage regimen, the pharmacokinetic characteristics of a drug (including the mechanism and the rate of drug delivery), and the exposure-response relationship. Then, the clinical benefit of a treatment was defined as a function of the diseases and the clinical endpoints and was estimated as a function of the target pharmacodynamic endpoints used to evaluate the treatment effect. A case study is presented to illustrate how the treatment performances of paliperidone extended release (ER) and paliperidone long-acting injectable (LAI) can be improved. A convolution-based approach was used to characterize the pharmacokinetics of ER and LAI paliperidone. The drug delivery properties and the dosage regimen maximizing the clinical benefit (defined as the target level of D2 recepto...Continue Reading

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Citations

Mar 5, 2016·Expert Opinion on Pharmacotherapy·Larry AlphsIbrahim Turkoz
Feb 20, 2021·Journal of Clinical Pharmacology·Roberto Gomeni, Françoise Bressolle-Gomeni

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