Lexicographical dynamic goal programming approach to a robust design optimization within the pharmaceutical environment

Vo Thanh Nha, Sangmun Shin and Seong Hoon Jeong

European Journal of Operational Research, 2013, vol. 229, issue 2, 505-517

Abstract: The primary objective of this paper is to develop a new robust design (RD) optimization procedure based on a lexicographical dynamic goal programming (LDGP) approach for implementing time-series based multi-responses, while the conventional experimental design formats and frameworks may implement static responses. First, a parameter estimation method for time-dependent pharmaceutical responses (i.e., drug release and gelation kinetics) is proposed using the dual response estimation concept that separately estimates the response functions of the mean and variance, as a part of response surface method. Second, a multi-objective RD optimization model using the estimated response functions of both the process mean and variance is proposed by incorporating a time-series components within a dynamic modeling environment. Finally, a pharmaceutical case study associated with a generic drug development process is conducted for verification purposes. Based on the case study results, we conclude that the proposed LDGP approach effectively provides the optimal drug formulations with significantly small biases and MSE values, compared to other models.

Keywords: Robust design; Response surface methodology (RSM); Time series response; Lexicographical dynamic goal programming (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:229:y:2013:i:2:p:505-517

DOI: 10.1016/j.ejor.2013.02.017

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