Cofactor Genomics Bridges the Precision Medicine Gap Using AWS and Machine Learning

Using precision medicine, researchers aim to find a new diagnostic approach for matching cancer patients with treatments and therapies based on multidimensional RNA models of immune response.

Biotech company Cofactor Genomics has developed a predictive immune modeling technology that is able to capture more comprehensive molecular information about a cancer patient’s disease. RNA sequencing and machine learning–based modeling are used to generate a multidimensional biomarker; cloud computing helps the company create individualized data for each patient and more accurately predict which therapies are appropriate.

RNA sequencing requires tremendous compute power as well as sophisticated machine learning to restructure the data and help the team at Cofactor Genomics detect biological changes in a patient and therefore predict therapy response. “Advances in technology such as RNA sequencing,” says Natalie LaFranzo, vice president of market development, “as well as cloud computing advancements with resources offered by Amazon Web Services (AWS) have enabled us to generate a bolus of data.” AWS services also enable Cofactor Genomics to run a decentralized platform, which makes it possible for the technology to be adopted by contact research organizations and other laboratories. The company is then able to build on their datasets to increase overall accuracy.