Eric Lefkofksy is a giant of the tech startup world. After having co-founded Groupon, a highly innovative firm that uses the power of volume purchasing to extend deep discounts to buyers, who are located all across the world, Lefkofsky has gone on to create a half-dozen other startups that have proven him as one of the top entrepreneurs in the country.
But in 2013, Lefkofsky’s wife received terrible news. She had been diagnosed with an advanced case of breast cancer and would need to begin aggressive treatment immediately. As shocked as Lefkofsky was at his wife’s sudden plight, he was even more taken aback by the apparently lackadaisical approach that the entire oncology profession apparently took towards the collation utilization of data. Lefkofksy noted that many of the oncologists, who were helping his wife fight to stay alive, had lower quality data to work with than many of the country’s truck drivers.
Fortunately, Lefkofsky’s wife made it through the ordeal fine and, today, is a cancer survivor. But one other good thing came from the Lefkofsky family’s cancer travails. In 2016, Eric Lefkofsky founded Tempus, an organization dedicated to bringing state-of-the-art data collection and analysis techniques to oncologists across the country.
Tempus uses many sources of data. These range from electronic medical records to high-level meta-studies of large research cohorts and everything in between. However, the most daunting source of new data for the company’s software solutions is the human genome itself. Today, it is not just possible but economically viable to sequence virtually anyone’s genome. This is a recent development and one that Lefkofsky says will only become cheaper and easier in the coming years.
With the vast trove of data that knowing full patient genomes can bring, Lefkofsky says that oncologists will be able to attain a level of granularity in their understanding of both cancer types treatment responses that has never before even been imagines.
They will be able to break patient cohorts into nearly infinite subgroups, tailor-making treatment regimens that are most likely to succeed for the individual patient, not a crudely defined group of 100,000 people.