Two big ways Eric Lefkofsky is modernizing cancer research

When it comes to medical science, things have been done the same way for a very long time. For the most part the technological changes surrounding medical research involve the manner in which we do experiments. New technology for refrigeration, extraction, visual analysis and other forms of measurement and the primary domain a development in this field.

All this is about to change. Over the past three years Eric Lefkofsky has sought to bring data-driven technology into the field of cancer research. Rather than simply have the tools to do better research and derive more accurate results, Eric Lefkofsky’s company Tempus seeks to use big data and machine learning techniques to better interpret the results. This has resulted in two major changes that cancer researchers and doctors can expect to work within the future.

Firstly, there will be a greater focus on meta-studies and combined data pools. Rather than independent experiments being the primary driver of new medical research, Tempus focuses on the real world. The data source currently used by Tempus sounds from real-world tests done on cancer patients. Typical diagnostics that are normally done on patients can be uploaded to Tempus and be shared what cancer research facilities around the country. This allows for a greater degree of collaboration as well as a greater degree of machine learning possible.

Secondly, the focus will be away from controlled experiments and instead focused machine-driven analysis. Historically cancer research has been done on a smaller scale with data and input data that a human can interpret. The scale of these experiments are normally essential; too much data no matter how good is impossible to use, there simply isn’t enough difference or change for a human being to derive any meaningful insight from a data set that is too large and similar. This problem is solved with machine learning and deep analysis; by using computer algorithms Tempus plans to eliminate the shortcomings in processing power brought on by our human minds.

Human scientists will still be at the forefront of cancer research for some time, but it is safe to say they will have new tools in the form of machine learning to work with.

Eric Lefkofsky info: