Description
Title: USE OF COMPUTER INTELLIGENCE TO PROJECT BIOLOGICAL RESULTS OF DRUG ABSORPTION IN THE LUNGS
Abstract: The possibility of noninvasively administering macromolecules like proteins and peptides has led to a recent focus on the lungs as a route for delivering medications (active pharmaceutical ingredients, or APIs) into the bloodstream. The development of pulmonary formulation composition is challenging because the mechanisms by which chemical compounds are absorbed in the lungs are still poorly understood. The creation of an empirical model that can forecast the impact of excipients on drug absorption in the lungs is presented in this manuscript. Computational intelligence tools were used because the issue was complex and the mechanisms of absorption were not fully understood. A mathematical formula was developed and examined as a result. The model’s R2 and normalized root-mean-squared error (NRMSE) were, respectively, 4.57% and 0.83. By creating an in silico predictive model and learning how APIs and excipient structure affect absorption in the lungs, the proposed approach is useful from a practical and theoretical perspectives.
Keywords: empirical model, absorption enhancers, pulmonary drugs, genetic programming, symbolic regression, computational intelligence
Paper Quality: SCOPUS / Web of Science Level Research Paper
Paper type: Analysis Based Research Paper
Subject: Computer Science
Writer Experience: 20+ Years
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