Strengths and weaknesses of current and future prospects of artificial intelligence-mounted technologies applied in the development of pharmaceutical products and services

Abstract

Starting from drug discovery, through research and development, to clinical trials and FDA approval, artificial intelligence (AI) plays a vital role in planning, developing, assessing modelling, and optimization of product attributes. In recent decades, machine-learning algorithms integrated into artificial neural networks, neuro-fuzzy logic and decision trees have been applied to tremendous domains related to drug formulation development. Optimized formulations were transformed from lab to market based on optimized properties derived from AI Technologies. Research and development in pharmaceutical industry rely upon computer-driven equipment and machine learning technology to extract data, perform simulations, modelling, and optimization to get optimum solutions. Merging AI technologies in various steps of pharmaceutical manufacture is a major challenge due to lack of in-house technologies. In silico studies based on artificial intelligence are widely applied as effective tools to screen the market needs of medications and pharmaceutical services through inspecting scientific literature and prioritizing medicines for specific illnesses or a particular patient. Specialized personnel who excel in scientific and data science with analytical knowledge are essential for transformation to smart manufacturing and offering services. However, privacy, cybersecurity, AI-dependent unemployment, and ownership rights of AI technologies require proper regulations to gain the benefits and minimize the drawbacks.