How the value of data is upending traditional business models in oncology

Harry Glorikian

It’s 1990: ten years before the initial sequencing of the Human Genome Project was completed. Only ten years after the first clinical use of the MRI and still more than a decade before the Health Insurance Portability and Accountability Act (HIPAA) would be enacted. Electronic medical records (EMRs) wouldn’t be widely discussed until President G.W. Bush’s 2004 State of the Union address. The top cancer hospitals were University of Texas MD Anderson Cancer Center and Memorial Sloan-Kettering Cancer Center [1]. Patients seeking care at these or other top medical centers had to navigate a Byzantine process, sometimes lugging suitcases of medical records from their local hospital to a specialized cancer center and subjecting themselves to repeat diagnostic testing. Without a comprehensive EMR system, individual researchers often used offline files, like Microsoft Excel databases, to keep track of their patients’ outcomes and other key data. Sharing this data was practically nonexistent. Matching a patient to a clinical trial was difficult and influenced substantially by where the patient received treatment. Quality of care was haphazard. Simply put, hospitals and oncologists didn’t have the IT infrastructure needed to better compare patients, track their treatments and outcomes, and assign them quickly to clinical trials [2].

Fast forward nearly three decades later and process looks virtually identical in some ways but has improved light-years in others. Precision Medicine is no longer just a buzzword touted for marketing purposes, but an actionable way to better treat some cancer patients based on molecular biomarkers and therapeutics… Read full blog post


Harry Glorikian will be speaking at the AI Applications in Biopharma Summit, download the latest agenda here


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