Investigating the Impact of Machine Learning in Pharmaceutical Industry
S. Nagaprasad *
Department of Computer science and Computer Applications, Faculty of Computer Science and Applications, Tara Government College (A) Sangareddy, Telangana State, India.
D. L. Padmaja
Department of IT, Anurag University, India.
Yaser Qureshi
Department of Zoology, Govt. College Khertha, Distt. Balod, Chhattisgarh, India.
Sunil L. Bangare
Department of I.T., Sinhgad Academy of Engineering, Pune, India.
Manmohan Mishra
Department of Computer Application, United Institute of Management, Prayagraj-211010, India.
Bireshwar Dass Mazumdar
United University, Prayagraj -211002, India.
*Author to whom correspondence should be addressed.
Abstract
In the pharmaceutical and consumer health industries, artificial intelligence and machine learning played an important role. These technologies are critical for the identification of patients with improved intelligence applications, such as disease detection and diagnostics for clinical testing, for medicine production and predictive forecasts. In recent years, advances in numerous analysis tools and machine learning algorithms have led to novel applications for machine learning in several areas of pharmaceutical science. This paper examines the past, present, and future impacts of machine learning on several areas, including medicine design and discovery. Artificial neural networks are employed in pharmaceutical machine learning because they can reproduce nonlinear interactions typical in pharmaceutical research. AI and learning machines are examined in everyday pharmaceutical needs, industrial and regulatory insights.
Keywords: Machine learning, consumer health, business change, cost-effective solutions