eng Oriental Scientific Publishing Company Biosciences Biotechnology Research Asia 0973-1245 2026-03-30 23 1 17 26 10.13005/bbra/3477 58441 article Shanti Sagar 1 Mukthinutalapati Sowjanya 1 Boyapally Maheshwari Reddy 1 Rajeshwar Vodeti 2 Basavaraj Nanjwade 3 Department of Pharmaceutics, Joginpally B R Pharmacy College, Moinabad, Hyderabad, India Department of Pharmaceutics, School of Pharmacy, Anurag University, Hyderabad, India Research and Development, Wexford Laboratories, Tumkur, Karnataka, India The spur growth of the pharmaceutical industry took a digital transformation face with help of artificial intelligence (AI) machine learning (ML). These technology is not only taken keen role in analytical tool but also help in developing drug formulation manufacturing aspects.  A tremendous shift was observed between 2020 and 2025 AI and ML have taken rapid role in application enabling in developing predictive model right from the primary physical chemical properties optimization of pharmaceutical parameters and technology driver of automation of process control. This review article put emphasis on recent existing advances alongside highlighting the technology in making more neural connections in network and support the vectors system in machines.  The generated models were helped in redefining the design and quality.  These technologies help in innovation in predicting excipient compatibility developed a simulator resolution profile finally helping to develop robust formulation part improving overall reproducibility and efficacy. The other technology such as Quantum machine learning federal learning and twin technology have made their own place in creating a new era of collaborative and autonomous formulation development. https://www.biotech-asia.org/vol23no1/role-of-artificial-intelligence-and-machine-learning-in-pharmaceutical-formulation-recent-advances-existing-challenges-and-future-prospectus/ Artificial Intelligence (AI); Drug Development; Formulation; Machine Learning; Technology