Application of Artificial Intelligence in Pharmaceutical Drug Design, Drug Development and Healthcare Research
This review examines AI applications in pharmaceutical research and healthcare, finding deep learning and neural networks accelerate drug discovery, disease diagnosis, pandemic forecasting, and personalized medicine while wearable NLP enables continuous passive monitoring.
Published Jun 4, 2026Paper ↗
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Abstract
Artificial intelligence (AI) is a branch of computer science that allows machines to be efficient and learn. There has been a significant increase in studies on AI, and its use in health care services and research is accelerating. This article explains the application of AI in medical and pharmaceutical & healthcare research. Using specific keywords such as Artificial intelligence, Pharmaceutical research, drug discovery, clinical trial, disease diagnosis, etc., literature was searched from sources such as PubMed, Science Direct, and Google Scholar, to find research and review papers published in the last ten years. This article thoroughly reviewed the application of AI in disease diagnosis, digital medicine, personalized medicine, drug discovery, and epidemic or pandemic prediction. The most common AI strategies are profound acquiring and neural networks, whereas Bayesian nonparametric models may be helpful in designing research studies. Wearable devices combined with Natural Language Processing (NLP) are transforming healthcare by enabling continuous, passive monitoring and early detection of health changes. These tools identify early warning signs of serious events and track clinical trial participants, offering a more efficient, real-time approach to patient management. Neural networks and deep learning predicted the spread of COVID-19, Zika, Ebola and influenza. As AI technologies are developed, the scientific world may get faster and cheaper medical and pharmaceutical research and improved services. It is a broad field that encompasses linguistics, computational neuroscience, neuroscience, behavioral science and computational science. The robotic nature, predictive power and the anticipated productivity gain of artificial intelligence technologies are attractive to the pharmaceutical company. Unsupervised machine learning can yield outcomes such as discovery of targets for disease and discovery of subtypes of disease through the use of feature discovery algorithms. The ability of a new artificial intelligence diagnostic device to know when to ask a human for assistance is more likely to arrive at a more accurate diagnosis. A projected growth rate of 40% between 2017 and 2024 shows that the pharmaceutical and medical industries would undergo a transformation due to artificial intelligence. The global pharmaceutical industry is working with artificial intelligence companies to conduct market research and, in addition to creating critical technologies for healthcare and therapeutic compounds for rare diseases.