Abstract
This paper focuses on solving the robust design (RD) problem that occurs in pharmaceutical studies in which output responses are measured over time. In order to handle such a situation, firstly, a customised experimental format is proposed for pharmaceutical experimental design. Using both response surface methodology (RSM) and a new inverse problem (IP) approach, a customised method of estimation also is developed to handle dynamic time-series as well as multiple responses for pharmaceutical experiments. Next, a new inverse problem-based robust design (IPRD) model is proposed based on the mean squared error (MSE) concept. For verification and comparison, a case study of a pharmaceutical experiment is conducted.
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