Artificial Intelligence and Data Analysis Driving the Evolution of Pharmaceutical Industry

By CIOReview | Tuesday, May 29, 2018

117

196

Today, most life science companies undertaking a project to upgrade the pharmaceutical operations and technologies have incorporated artificial intelligence and data analysis, both in the life science consulting and pharmacy operations. Due to the significant impact that artificial intelligence and data analysis have made on the operations of the pharmacies, they may very well be the major factor in reducing delays and planning strategic advances of the life science industry in the future. Pharmacies indulging in these methodologies could actually generate more money than the pharmacies which don’t.

The introduction of machine learning and big data analysis into pharmaceutics and medicine enables improved efficiency in research and clinical tests, better decision making, optimized innovation and a new creation tool for regulators, physicians, insurers, and consumers. This puts the traditional transactional-based pharmacies at a major disadvantage. Pharmacies that are looking to grow and maintain long-term relationships will have to provide more value since the patients can now simply fill their prescriptions at the cheapest place of their convenience. Life science just got its personalized treatment along with a range of new services, supported by artificial intelligence.

Prevention, personalization, and precision - the three fundamentals towards which life science industry has shifted today with artificial intelligence as the key factor in uniting the life science industry and the patients. Thorough insights of data, like patient information, supply chain data and insurance can be gathered and analyzed to study and update customer’s shopping habits. This allows organizations in restocking of the items and cutting acquisition costs. With access to supply chain’s data, budgeting and efficiencies throughout the organization can be improved by streamlining supply chain processes, predicting future needs of a patient and negotiating better rates.