Disruption has arrived in the pharmaceutical and biotech industry. Driven by artificial intelligence (AI) and machine learning (ML) technologies, new possibilities include everything from molecular design to predictive patient reaction models. However, despite a clear connection between the science of drug discovery, ML, and business decision making, there is a disconnect between the tools that exist and the specialists utilizing them. It’s only by bridging this gap that the full potential of this technology will be realized. In the Artificial Intelligence in Pharma and Biotech online short course from MIT Sloan School of Management, you’ll discover the benefits and challenges of AI tools within this sector. Over six weeks, gain insight into the current state of technology in the industry and explore ways that it can be applied to the drug discovery and distribution processes. You’ll learn how AI can be utilized in biological and generative modeling, and examine the impact of ML on the design and management of clinical trials. With insights into the relevance, practical implications, and business impact of these technologies, you’ll be able to position yourself ahead of the curve as innovation reshapes the industry.
Over the course of six weeks, dive into the existing and potential applications of AI and ML in the pharmaceutical and biotech industry. Guided by expert MIT faculty, you’ll gain insight into the optimal AI tools for this industry and explore how they can be leveraged for early drug discovery. Unpack AI’s potential to help promote research efforts into biology and diseases on a cellular level, and how it can assist with tasks like biomarker identification and disease tracking. Finally, you’ll investigate the impact of new AI modalities on patient stratification, and assess the limitations and promises of using ML in the design and management of clinical trials. You’ll walk away from the program with an understanding of AI’s broader business implications for the pharma and biotech industry.
