Innovating Business Through Data: Part 2 – Drug Responsiveness

Part 2: Drug Responsiveness

This new series, Innovating Business Through Data, focuses on how Machine Learning, Natural Language Processing, and Robotic Process Automation are changing the face of business. Each post contain a specific use case, the business value derived, and the technology synopsis to achieve the outcome.

Clinical trials are being revolutionized by analyzing biomarker data to assess and predict drug treatment outcomes to address uncertainty about which candidates hold the most promise. This can be achieved by applying different classes of Machine Learning models including CARTs, Random Forests, Linear Models, and Support Vector Machines. Open source tools, such as R and Shiny, can be used to build the model and visualize the insights. This can overall speed the historically long process of conducting clinical trials and ensure better success in patient selection, getting drugs into the market quicker and more efficiently.

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