Paper Contents
Abstract
ABSTRACTAI stands as a Bureau of Change in Disruption in the pharmaceutical industry. In this way, it speeds up the process and optimization across drug discovery, development, and formulation. The article studies how AI applications like ML, deep learning, and NLP will shape a pharmaceutical life cycle. AI enables rapid identification of biological targets, efficient lead compound optimization, and innovative drug design through such techniques as quantitative structure-activity relationship modeling and molecular docking. AI-driven predictive analytics on ADMET can also reduce late-stage failures in drug development and create cost-effective clinical trial designs based on real-world data. Applications of AI in drug formulation include the development of new drug delivery systems such as nanoparticles and liposomes, with strong quality assurance by real-time monitoring and predictive modeling. AI promises improvement in the delivery of drug formulation incorporating superior pharmacokinetic and pharmacodynamics properties by solving solubility, permeability, and stability problems. It aids drug repurposing, thus having potential new applications for available drugs, saving time and money. AI promises to transform healthcare for millions, but still faces hurdles for adoption in quality of data, regulatory compliance, and model interpretability among others, making researchers, industry stakeholders, and regulatory bodies work collaboratively to overcome these barriers. This review studies the AI role in revolutionizing pharmaceutical innovation, personalizing medicine, and revolutionizing healthcare delivery globally. As advances in AI technologies become available, these applications will be increasingly integrated to resolve any unmet medical needs and create solutions for personalized healthcare.
Copyright
Copyright © 2024 HARI KISHAN SHUKLA. This is an open access article distributed under the Creative Commons Attribution License.
