Vol. 51 No. 1 (2026), Articles
Innovative method of learning in technology of soft medical forms using elements of artificial intelligence
Articles
Published
31.03.2026
Keywords
soft dosage forms
pharmaceutical education
artificial intelligence
Quality by Design (QbD)
critical process parameters
pharmaceutical education
artificial intelligence
Quality by Design (QbD)
critical process parameters
Abstract
This article explores the implementation of innovative teaching methods using artificial intelligence (AI) elements in the training of students in soft dosage form technology in pharmaceutical education in the Republic of Kazakhstan. It examines modern approaches to integrating AI into the educational process, including virtual laboratories, predictive models, and machine learning algorithms for analyzing process parameters and predicting drug quality. Using a laboratory session on the development and optimization of an anti-inflammatory ointment as an example, it demonstrates how students apply AI to model homogenization, temperature control, mixing time, and cooling rate. The article describes in detail the relationship between critical process parameters (CPPs) and critical quality attributes (CQAs), as well as AI tools that can improve the accuracy and efficiency of the educational process. It emphasizes the importance of using such methods to develop students' professional, research, and digital competencies, thereby enhancing their analytical abilities, decision-making skills, and digital literacy. The authors demonstrate that integrating AI into the educational process reduces errors in laboratory experiments, improves the quality of theoretical material acquisition, and brings the educational process closer to the real-world conditions of pharmaceutical production. These results highlight the effectiveness of integrating innovative technologies into specialist training and confirm the relevance of using AI as a tool for enhancing the competence of future pharmacists.
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