Analysis of Drug Absorption Rate Using Fuzzy Matrices, PCA, and Machine Learning

Abstract

The present study mainly focuses on calculating drug absorption in the human body by considering key physiological parameters namely gastric pH, metabolic rate, and partition coefficient. It is difficult to predict the medication absorption in human body accurately due to factors like biological uncertainty and inter- individual variability, to overcome this problem A hybrid model strategy is used which combines fuzzy theory, machine learning, and statistical analysis. The main input factors of the models are Gastric pH, metabolic rate, and partition coefficient. To lower the complexity of the data set the most important parameters are found using Principal Component Analysis (PCA), and to estimate and reduce the prediction errors, statistical techniques are used. And lastly optimization techniques are used to identify circumstances that enable more effective and regulated drug absorption.