There are two parts of Tempus’ business model which we find compelling. The first is its vast database of millions of clinical oncology records obtained through agreements with nearly three-quarters of the US National Cancer Centres. In its ‘raw’ form, this data is largely unstructured and consequently of little use to practitioners. Using a combination of machine learning, natural language processing and a team of abstractors, Tempus has been processing these records to make them structured, searchable, and, therefore, insightful. The second important aspect is its testing business which generates revenue by charging pharmaceutical companies to access the library to understand how their drugs are working and seek new drug targets. The overall penetration of Tempus’ tests remains low, leading to a persuasive long-term growth opportunity.

Tempus sits at the intersection of two exciting trends – genomic profiling and artificial intelligence-driven health data. By advancing precision medicine through the practical application of AI in healthcare, Tempus enables physicians to make near real-time, data-driven decisions to deliver personalised patient care. The goal is for each patient to benefit from the treatment of others who came before by providing physicians with tools that learn as the company gathers more data.

Eric Lefkofsky, a Chicago entrepreneur, founded Tempus after his wife was diagnosed with cancer. He was amazed at how little data was used as part of her therapy, largely because the healthcare system makes it hard for doctors to access data when making real-time, clinical decisions. It became clear to Lefkofsky that he had to tackle this problem, and Tempus was born soon afterwards.

in August 2018.