Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Taste masking remains a critical challenge in pharmaceutical formulation development, particularly for pediatric and geriatric populations where medication adherence is significantly impacted by palatability. This comprehensive review examines the latest advances in taste masking technologies for drug products, encompassing both traditional approaches and innovative emerging techniques. We discuss physical barriers including coating technologies and complexation methods, chemical modifications through prodrug design, organoleptic approaches using flavoring systems, and novel technologies such as 3D printing and nanotechnology-based solutions. The review provides detailed analysis of each technology with mechanistic insights, formulation considerations, and recent applications. A comprehensive compilation of commercially approved taste-masked products demonstrates successful implementation of these technologies. The future perspective highlights the integration of artificial intelligence in taste prediction and formulation optimization, personalized medicine approaches based on genetic variations in taste perception, and sustainable taste masking solutions using natural biomaterials. This review serves as a comprehensive resource for pharmaceutical scientists involved in developing palatable drug formulations.
"Recent Progress and Emerging Trends in Taste Masking Strategies for Oral Drug Delivery", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 10, page no.b401-b416, October-2025, Available :http://www.ijrti.org/papers/IJRTI2510149.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator