How Machine Learning Is Identifying New, Better Drugs

As a leading mind in the field of computational biology and a pioneer of CMU's program on the topic, Murphy himself has played a strong role in this. In 2011, he penned a commentary noting that machine learning would play a role of growing importance in the drug discovery process. But his argument went a step further, advocating for the use of active machine learning, or a subset of ML in which the user offers the machine feedback on desired outcomes, improving its efficiency and accuracy over time. In the drug discovery process, the number of experiments required to screen a specific compound on a specific target while monitoring impact on other targets can quickly become unwieldy. Active ML offers researchers the opportunity to direct the experiment, supervising the computer as it iteratively chooses experiments that are most likely to improve the model.