Tempus, a leader in artificial intelligence and precision medicine, today announced the launch of its cloud-based data and analytics platform, Lens. The all-in-one platform will provide scientists and researchers across biotechnology and pharmaceutical companies with short term, on demand access to more than 35 petabytes of de-identified clinical and molecular datasets, along with the latest artificial intelligence analytical tools to accelerate drug discovery and development.
The Lens platform enables users to access, analyze, and build upon Tempus’ library of data in an optimized environment equipped with the tools needed to extract insight in minutes. Lens provides multiple ways for both researchers and physicians to leverage one of the world’s largest libraries of clinical and molecular data – including Tempus’ tumor/normal matched DNA, RNA, and H&E data – from creating targeted patient cohorts and simulating clinical trials in silico, to renting or licensing the underlying data to test hypotheses. Through Lens, users can also collaborate with Tempus’ computational biologists and data scientists to analyze datasets to uncover unique insights. Users can analyze data within the Lens platform through a combination of tried-and-true open source and purpose-built Tempus visual analysis tools or a cloud-based data science environment. They can also apply their own proprietary tools to the data.
“Never before has real-world data played such a major role in guiding care and accelerating drug discovery and development. Our data library has reached such a significant scale that it was critical we develop Lens to help our partners navigate and utilize our vast dataset in real-time, helping them mine unique insights that can only be found in a library like ours,” said Eric Lefkofsky, Founder and CEO of Tempus. “The option for scientists and analysts to only pay for data when they need it, on a short term usage basis, is revolutionary and we expect it will not only save the healthcare system money, but will also unblock research and accelerate the very pace of innovation itself.”
The platform serves partners’ drug discovery and development needs by validating targets with one of the market’s largest multi-modal datasets, characterizing diseases in more granular ways, analyzing RNA expression signatures, designing trials for precise patient populations, and working with Tempus’ AI team to launch a multi-scale modeling approach.
“Visual data exploration in Lens is key to exploring ideas in minutes on large datasets. It helps lower the bar to access the data, and having this capability up front makes it easy to then move to deeper analysis,” said Markus Bauer, Principal Scientist at Boehringer Ingelheim.
Lens also provides additional utility to administrators and clinical researchers within academic cancer centers by enabling quick, seamless assessment of patient prevalence across key clinical and molecular characteristics. Whether to evaluate and analyze a candidate population for research and publication, identify a subset of patients at the institution who may be considered for a newly approved therapy, or to understand mutation trends within a set of biomarkers relative to the general population, Lens empowers users with the tools to rapidly answer their important questions.
“Lens has advanced our research and allowed us to easily leverage Tempus resources in the platform to characterize the genomic landscape of advanced prostate cancer in African American men with the goal to understand the mechanisms behind the disparities seen in clinical outcomes between patients of different ancestries, the findings of which we recently presented at two national meetings,” said Dr. Nicholas Mitsiades, Associate Professor of Medicine at Baylor College of Medicine and Oncologist at the Dan L Duncan Comprehensive Cancer Center. “The ability to filter patients and mutations in Lens offers a more precise look at patient populations and their genomic landscapes. By adding Lens to an arsenal of other products and services, Tempus has made it easy to interact with large datasets and quickly extract meaningful insights.”
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