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Mediterranean Journal of Medical Research
http://www.mjpe.periodikos.com.br/article/doi/10.5281/zenodo.17945149

Mediterranean Journal of Medical Research

REVIEW

Artificial Intelligence in pharmaceutical sciences: Transforming drug discovery, formulation, and manufacturing

Syed Faizan Syed Nizamuddin, Maazuddun Ikramuddin, Nakul S. Dhore

http://dx.doi.org/10.5281/zenodo.17945149 Mediterr J Med Res, vol.2, n4, p.269-275, 2025
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Abstract

Artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence, a major feature of machine learning and deep learning, is changing the way pharmaceutical research and development are done by speeding up drug discovery, formulation, stability prediction, and manufacturing processes. Artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence enables more rapid target identification, chemical space exploration, and de novo molecule design with fewer iterative experimental cycles, lead selection being optimised, and formulation behaviour and stability predicted. Machine learning and generative models are extensively used in early drug discovery for virtual screening, activity prediction, ADMET profiling, and multi, objective lead optimization resulting in development timelines being reduced drastically. In formulation and preformulation, artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence models are used to predict physicochemical properties, excipient interactions, and process effects leading to a dose form getting designed more efficiently even if it is complex. Stability prediction models are used to identify degradation pathways, moisture, induced changes, and biologics' aggregation thereby helping the formulation to be done early and the regulatory risk to be assessed. Artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence, assisted process analytical technology and digital twins in manufacturing lead to enhanced real, time monitoring, predictive control, and continuous manufacturing, thus quality and throughput are ensured. The main issues faced are data quality, model explainability, regulatory acceptance, and workforce readiness although the benefits have been demonstrated. The next steps will be the multimodal artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence integration, foundation models, or self-driving laboratories that will, without any doubt, speed up the process of pharmaceutical innovation even further. Together, artificial​‍​‌‍​‍‌​‍​‌‍​‍‌ intelligence is no more a supplemental tool but rather the main driver of efficiency, quality, and predictability in pharmaceutical ​‍​‌‍​‍‌​‍​‌‍​‍‌sciences.

Keywords

Deep learning, drug discovery, formulation development, machine learning, stability prediction

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Submitted date:
10/27/2025

Reviewed date:
12/09/2025

Accepted date:
12/15/2025

69408c04a9539541ee53a1b3 mjpe Articles
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