Using big data to predict the best course of cancer treatment

For years marketers have used big data to predict what ads someone is most likely to respond to, but in cancer treatment, standards of care have largely followed a mass market approach. To arm oncologists with the same predictive power as advertisers, Dr. Robert Huether and his team at Tempus develop computational tools to provide personalized treatment recommendations to cancer patients.

Tell us about your research…

In clinical sequencing, we want to provide the most relevant molecular information to an oncologist to help them make the best treatment decision for the patient.  This starts with being able to interpret, classify, and categorize the sequenced variants. The focus of my research is on developing diverse evolutionary, structural, and population based methods to provide insight into the clinical relevance of both somatic and germline variants. We computationally apply the methods on data from many areas of science and medicine allowing a broader interpretation of the molecular contribution to disease.

In clinical sequencing, we want to provide the most relevant molecular information to an oncologist to help them make the best treatment decision for the patient.

Can you explain that to a non-scientist?

Rare hereditary disease and somatic cancers can result from changes in our DNA. Genomic sequencing can identify these changes or variants; however, not all variants are equal in terms of the change or the effect. One mechanism for understanding the effect of a variant is to bucket them into groups. My team’s research focuses on novel analyses and tools used to bucket these variants which informs clinical diagnosis or treatment.

My team’s research focuses on novel analyses and tools used to bucket these variants which informs clinical diagnosis or treatment.

How could it someday impact patient lives?

My teams methods and analyses on a patients molecular data have contributed to the understanding of what drives somatic cancers and causes hereditary diseases. Supported by larger molecular and clinical datasets our research impacts patients by helping them make more informed and targeted treatment decisions.

Our research impacts patients by helping them make more informed and targeted treatment decisions.