Open Source Machine Learning Tool Could Help Choose Cancer Drugs Research Horizons

The selection of a first-line chemotherapy drug to treat many types of cancer is often a clear-cut decision governed by standard-of-care protocols, but what drug should be used next if the first one fails? That's where Georgia Institute of Technology researchers believe their new open source decision support tool could come in. Using machine learning to analyze RNA expression tied to information about patient outcomes with specific drugs, the open source tool could help clinicians chose the chemotherapy drug most likely to attack the disease in individual patients. In a study using RNA analysis data from 152 patient records, the system predicted the chemotherapy drug that had provided the best outcome 80 percent of the time. The researchers believe the system's accuracy could further improve with inclusion of additional patient records along with information such as family history and demographics.