A methodical approach to the multi-criteria selection in the pharmaceutical technological research with quantitative factors

Abstract

Aim. To analyze the existing methods for solving multi-criteria optimization problems with quantitative factors and consider the expediency of their application in the pharmaceutical technological research. Materials and methods. The theoretical and empirical methods, as well as scientific data on multi-criteria optimization methods were used in the research. Results and discussion. It has been found that when conducting the research with quantitative factors the statistical methods for processing the results of experiments are used. It has been determined that the regression analysis allows us to present the dynamics of changes in the pharmacopoeial characteristics studied from variable quantitative factors in a compact form. It has been found that regression equations enable the researcher to effectively search for optimal conditions for conducting technological operations and are local criteria for finding the optimal solution. It has been proven that the need to optimize several criteria simultaneously when developing the technology of a medicinal product allows considering the tasks of multi-criteria selection in the pharmaceutical research as a special class of decision-making problems that are on the verge between the research of operations for well-structured quantitative situations and decision-making tasks, which methods of solving differ. Conclusions. To determine the optimal solution in the course of the pharmaco-technological development, a method for finding an ideal point has been proposed as a synthesis of mathematical calculations and decision-making procedures by a researcher. The search is conducted in the range of acceptable values of variables and determines their totality, which is able to provide a set of values of pharmaco-technological criteria that is closest to the optimal option determined by the researcher. This approach involves preliminary solution of single-criterion optimization problems for each individual criterion and reduction of all to a mathematical form that determines the minimum deviation of the objective functions obtained from the optimal values.