Artificial intelligence (AI) has developed into a powerful tool that employs human knowledge to swiftly resolve complex issues. Significant advancements in computer learning and artificial intelligence present a revolutionary opportunity for pharmaceutical formulation, drug dis-covery, and dosage form testing. AI algorithms would analyze a tremendous amount of biological reference data, such as proteomics and genomes, to assist researchers in identifying target diseases and predicting their possible interactions with proposed approaches to treatment. Just such focused and efficient drug development significantly augments the likelihood of acquiring drug approvals. AI may add, at the same time, develop costs and streamline research and development processes. Clas-sical machine learning techniques help not only in designing the experiment but also significantly in predicting the pharmacokinetics and toxicity of new drugs. This ability reduces the need for expen-sive, time-consuming animal testing by selection with optimization of lead compounds. Personalized medical strategies based on actual patient data assessments by algorithms such as those of AI may benefit patients through increased treatment adherence and outcomes. The review covers many ap-plications of AI for process optimization, testing, drug delivery dosage form design, and drug discov-ery. This study underlines the benefits brought by numerous types of techniques based on AI in phar-maceutical technology. However, there are exciting prospects to enhance patient care and medication development processes because of the pharmaceutical industry's continuous investment in and re-search into AI.
Dushyant et al. (2025) studied this question.