The Silicon Review
Artificial intelligence (AI) in healthcare is the use of complex algorithms and software to emulate human cognition in the analysis of complicated medical data. Specifically, AI is the ability for computer algorithms to approximate conclusions without direct human input. What distinguishes AI technology from traditional technologies in health care is the ability to gain information, process it and give a well-defined output to the end-user. AI does this through machine learning algorithms. These algorithms can recognize patterns in behavior and create its own logic. The primary aim of health-related AI applications is to analyze relationships between prevention or treatment techniques and patient outcomes.
Tempus is a technology company that has built an operating system to battle cancer. It is on a mission to redefine how genomic data is used in a clinical setting. Their goal is for each patient to benefit from the treatment of others who came before by enabling physicians to deliver personalized cancer care for patients through interactive analytical and machine learning platform.It is a technology company that has built the world's largest library of clinical and molecular data and an operating system to make that information accessible and useful for patients, physicians, and researchers.
WHAT THEY OFFER
Next Generation Sequencing
It provides a broad range of DNA and RNA sequencing services, generating high quality somatic and germ line molecular data along with therapeutic context to empower physicians to make data-driven decisions. Through genomic sequencing, it is possible to identify genomic alterations. Potentially relevant therapies are reported and prioritized based on the strength of the clinical evidence, which establishes the association between genomic alterations and relevant therapeutic options.Utilizing proprietary assays, it is possible to perform a tumour/normal matched analysis by sequencing both a tumour DNA sample and a normal DNA sample from blood or saliva to ensure that your report accurately distinguishes between your patient’s somatic and germ line variants.
CLINICAL DATA STRUCTURING
Using advanced tools and technologies to convert text buried inside oncology notes, pathology reports, and radiology reports into structured data that can be used for research, analysis, quality metrics reporting and clinical decision support. The team of trained abstractors use optical character recognition (OCR), natural language processing (NLP) tools, and automation to structure, clean and standardize data.
TUMOR BOARD- Integrates structured clinical and molecular data into a consolidated view of patients that streamlines and enhances the tumor board process
RESEARCH PROJECTS- Accelerates data aggregation and structuring for research at a low cost by off-loading difficult and time-consuming chart review processes
CLINICAL TRIALS MATCHING- Utilizes clinical data structuring to power more specific clinical trial mechanisms, increasing institutional trial accrual rates
CARE PATHWAY ANALYSIS- Visualizes treatment decision patterns and associated outcomes based on defined disease phenotypes
TUMOR REGISTRIES- Simplifies data management and reporting to state and national tumour registries
The quantitative features found in radiology scans and pathology slides alone have the ability to uncover disease characteristics that are invisible to the naked eye. By combining structured radionics with other orthogonal data in the Tempus database, they hope to eventually improve the accuracy of diagnosis and enhance prognosis for patients. This integrated data also supports biomarker development and drug discovery in a research setting. Its highly-automated research image analysis is optimized around advanced pattern recognition and data characterization. The program is designed to quantify various tumour characteristics in a non-invasive and objective way. They offer complex machine-learning algorithms are constantly running in the background, which allows health professionals to improve the speed and accuracy of our insights engine in real time.
TIME TRIAL PROGRAM
To date, Tempus has worked to bring over 40 provider networks, with a force of over 1,800 oncologists, into the TIME Trial program, allowing clinical trial access to patients at scale. All Institutions in the network must pass Tempus’ rigorous qualification requirements for rapid activation and investigational-trial readiness. It pre-screens patients in the Network by utilizing proprietary state-of-the-art sequencing technology and/or clinical data structuring pipelines to identify patients matching inclusion and exclusion criteria. Tempus integrates with sites’ EMR systems to abstract relevant molecular and clinical data, yielding high quality data that is used to match patients to the best treatment options in available clinical trials.
MEET THE CEO, ERIC LEFKOFSKY
Eric Lefkofsky is the founder and CEO at Tempus, a leading provider of technology enabled precision medicine solutions. He is a founding partner of Lightbank, a venture fund investing in disruptive technology businesses. He is also the co-founder and Chairman of Groupon (NASDAQ: GRPN), a global e-commerce marketplace, and co-founder of Mediaocean, a leading provider of integrated media procurement technology; Echo Global Logistics (NASDAQ: ECHO), a technology-enabled transportation and logistics outsourcing firm; InnerWorkings (NASDAQ: INWK), a global provider of managed print and promotional solutions and a founding investor of Uptake Technologies, a leading predictive analytics platform for the world’s largest industries. He co-chairs the Lefkofsky Family Foundation with his wife Liz to advance high-impact initiatives that enhance lives in the communities served. He graduated from the University of Michigan and received his Juris Doctor at University of Michigan Law School.
“By combining our web-based pathology and radiology platforms with state-of-the-art image analysis tools, we enable pathologists and researchers to access, share and analyze images anywhere at any time.”