Artificial Intelligence (AI) is poised to transform healthcare: there are a growing number of use cases from scheduling bed management to improving the detection of specific cancers, states a McKinsey & Company report. Reports show that nearly 62% of healthcare organizations are thinking of investing in AI technology in the near future. Pharmaceutical companies particularly stand to benefit from nascent AI technologies. In fact, the McKinsey Global Institute states that AI and machine learning across the US healthcare system could generate in the region of $100B annually. What, then, are the opportunities of using AI in the pharmaceutical industry?
Subroto Mukherjee, Head of Innovation and Emerging Technology, Americas at GlaxoSmithkline Consumer Healthcare, discusses some use cases for AI and Machine Learning (ML) technology in Forbes for the pharmaceutical industry. These include:
Drug Discovery and Manufacturing
AI and ML can assist in the initial screening of drug compounds. They can also help predict the success rates of various drugs based on biological factors. As a result, we can look forward to tailored medication for individual patients and the faster discovery of life-altering drugs.
When it comes to predictive forecasting, AI can serve a very important function for pharmaceutical companies - namely, monitoring and predicting the incidence of various illnesses worldwide. Mukherjee says, “A predictive forecast helps plan our supply chain to get the inventory at the right time and the right quantity based on the predicted intensity.”.
Helping pharmaceutical companies in understanding the local market and disease burden across the region is a key competence offered by EPCON. Due to their extensive work in finding undiagnosed, or missing, tuberculosis (TB) patients in various regions, they can transfer these models to new countries such as India. By using contextual data - such as population density, poverty prevalence, vaccination rates and access to care - in combination with their AI model, EPCON can map out demand in a particular region for pharmaceutical companies to hone their go-to-market strategies.
Using high-resolution mapping, pharmaceutical companies are able to assess where the greatest risk of disease lies.