Eric Lefkofsky has been one of the most innovative and interesting entrepreneurs to leap into the tech field out of Chicago over the past decade or so. As a specialist in data aggregation and data-enabled precision medicine, Lefkofsky has a unique set of skills that have translated into what could be one of the most momentous medical advances in recent memory. Lefkofsky has been uniquely focused on the problems that surround cancer care and cancer research and now he is addressing those issues with his new company, Tempus.
Tempus is an idea that seeks to merge several different forms of technology and data analytics into a core operating system that brings real solutions to the fold. The healthcare industry was supposed to see a huge evolution with the introduction of electronic health records. However respectable EHRs were as an improvement, they weren’t nearly enough. This is where Tempus comes to play. Tempus operates as an operating system that aggregates important data into an all-in-one accessible system that healthcare professionals, patients, and providers can all access. The goal of the program is to put important molecular and patient data into an accessible interface so that healthcare professionals around the country can access it with the press of a button.
In terms of molecular data the bulk of the conversation is revolving around information related to the human gene. Lefkofsky, as well as premier intellects in the healthcare field, understand that potential cures and treatment for cancer may lie within the human genome. Genome sequencing is exorbitant in terms of expense and cost as much as $100 million just over a decade ago. Nowadays the cost has been reduced to around $5,000 and Lefkofsky’s work might bring those costs even lower if Tempus is effective.
The goal with Tempus, and other work from people like Lefkofsky, is to unveil the mysteries and questions that have plagued cancer research and cancer care for so long. With each additional piece of data accumulated by Tempus, medical workers around the world come closer and closer to finding fundamental answers to one of the most hard fought battles in the medical field.
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Of all the incredible advancements in medicine that have taken place over the last few decades, one stands above the rest. The ability to sequence the human genome cheaply and quickly has provided researchers and doctors with more data than they can currently handle. The magnitude of unmined data that has been provided by advancements in genomics is difficult for the mind to comprehend. The vast majority of current genomic information has not been tested or used for any medical purpose.
Eric Lefkofsky, the famous co-founder of volume discount giant Groupon, is undertaking the construction of a system that will allow this vast trove of genomic data to be used in real time by oncologists and physicians. Tempus, founded in 2016, seeks to take vast amounts of genomic data, clinical trial data, patient histories and other relevant medical information and combine it into a platform that will inform oncologists and other doctors in real time what the best course of treatment, for any given patient, is likely to be.
But Tempus is no ordinary data management company. Eric Lefkofsky believes that, through the use of advanced statistical methods, including machine learning, Tempus will be able to create a platform that amounts to the ability to perform real-time, on-site meta studies, allowing oncologists to have a granular understanding of treatment phenomena that has never before been possible. Lefkofsky believes that this system will enable the complete customization of treatment regimens. Dosages, duration of administration and even the molecular construction of drugs will be able to be manipulated on the spot, yielding the precise combination of treatment elements that are likely to maximize that individual patient’s chances of survival and recovery.
The heart of the Tempus idea is to create a far more granular understanding of oncological phenomena. Today, most treatment regimens are essentially little more than a one-size-fits-all affair, with virtually every patient suffering from a certain type of cancer receiving effectively the same treatment. This is a blunt, strongly suboptimal approach, but it is the best tool that oncologists have had to work with. However, with the use of genomic data and sophisticated, real-time analysis, it may be possible to break that group of patients into 100 or more subgroups, each with a different treatment regimen designed to maximize patient survival and minimize side effects.
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