AI supports the development of prediction models to estimate the risk of diabetes and its related complications. This will help to bring in an element of personalized care in the management of diabetes.

Artificial intelligence (AI) uses personified knowledge and learns from the solutions it produces to address not only specific but also complex problems. Remarkable improvements in computational power coupled with advancements in AI technology could be utilised to revolutionise the drug development process. At present, the pharmaceutical industry is facing challenges in sustaining their drug development programmes because of increased R&D costs and reduced efficiency. In this review, we discuss the major causes of attrition rates in new drug approvals, the possible ways that AI can improve the efficiency of the drug development process and collaboration of pharmaceutical industry giants with AI-powered drug discovery firms.

Taking into account the powerful capabilities of AI when paired with innovation and the potential outcomes of a better collaboration between technology, healthcare professionals, and patients, the future seems bright and full of opportunities.

It is expected that AI-informed methods will continue to be explored and gradually integrated into practice. Imagining how the field will mature risks exacerbating the decades of criticism that has counterbalanced its frequently audacious predictions; however, it is necessary to foresee how incremental development can lead to the common goal of true precision oncology.

As is the case in many other fields of healthcare, the integration of AI in cancer care is expected to reshape the existing scenario in the future.

Artificial Intelligence (AI) is expected to be a lucrative technology in the healthcare industry. The implementation of AI reduces R&D gap in the drug manufacturing process and helps in targeted manufacturing of drug. Hence, biopharmaceutical companies are turning to AI to enhance their market share. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure.

The increase in research activities for incorporating AI in chemotherapy further accelerates segment growth.

In the future, the adoption of AI could open the avenue for the development of personalized nutrition and the enhancement of the support care system that could lead to better health at the individual and national levels.

Review of the fied and trends