Application of probability based multi - objective optimization in the preparation of drug encapsulation with a designed experiment

Keywords: probability theory, multi-objective optimization, preferable probability, test design, drug encapsulation

Abstract


Introduction/purpose: In this paper, probability based multi – objective optimization (PMOO) is employed to objectively study the optimization problems of the drug encapsulation of water-soluble chitosan (WSC) / poly – gama - glutamic acid (g-PGA) - tanshinone IIA (TA) with a response surface design and glycerosome - triptolide with an orthogonal experimental design.

Methods: In PMOO, a concept of preferable probability has been introduced to describe a preference degree of the performance utility. Each beneficial and unbeneficial utility index contributes a partial preferable probability in a linear manner, positively and negatively, respectively and all the performance utility indicators are simultaneously and equally treated. The total preferable probability of a candidate is the product of all partial preferable probabilities, which thus transfers a multi-objective problem into a single-objective one.

Results: 1. The optimal encapsulation of WSC / g-PGA - TA is for WSC of 5.755 mg×ml−1, TA of 1.0275 mg×ml−1,when  the ratio of TA to the carrier material is 1: 4.9, and the reaction time is 1.302h. 2. The optimal preparation conditions of glycerosomes – triptolide are a glycerol concentration of 20%, the phospholipid to cholesterol mass ratio of 30:1 and the phospholipid to triptolide mass ratio of 5:1.

Conclusion: The results show the applicability of PMOO in the optimization of encapsulation composites with designed tests.

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Published
2022/10/14
Section
Original Scientific Papers