The use of big data to provide more targeted treatments to fight cancer to improve outcomes is steadily evolving. In a bid to combat the second leading of cause of death in the U.S., companies and groups are analyzing the genetics of patients’ cancer cells to indicate which treatments could have the best outcomes and fewest side effects. Some companies are also analyzing data generated by hundreds of thousands of patients to develop treatment recommendations. Here are four companies and groups that are taking different approaches to using big data as part of an effort to improve cancer treatment outcomes.
N-of-One comes in as part of the last step in the big data analysis for oncology. The five year old company uses a decision-making platform for targeted cancer care called PrecisionWorks. It works with diagnostic companies, hospitals and cancer centers. Hospitals send biomarkers electronically to the company database. N-of-One’s team matches patient-specific tumor molecular profiling data with diagnostic technologies and therapeutic options. It identifies relevant clinical strategies for each patient’s unique cancer and sends back a report within 72 hours, according to CEO Christine Cournoyer.
Earlier this year it formed a partnership with Fox Chase Cancer Center in Philadelphia. It provides molecular interpretation and treatment strategy analysis for genome sequencing and testing through the Cancer Genome Institute at Fox Chase. It’s also working with contract research organizations to screen patients for clinical trials based on their molecular profile for MarkerMatch program.
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In addition to cancer, it sees opportunities to apply its platform to other molecularly driven diseases such as cardiovascular, neurodegenerative and metabolic diseases.
The American Society of Clinical Oncologists’ CancerLinQ project is using data from 100,000 breast cancer patients from 22 practices in the first prototype of what its developers hope will serve as a nationwide second opinion service for physicians. It is linking together open source and proprietary software to achieve a few different objectives. It wants to be able to accept patient data from electronic health records, lab data, genomic profiles and physician notes. It also wants to provide speedy feedback on physician performance against 10 quality measures. It’s also using open source reference software PopHealth to determine whether patients are getting the right cancer treatment based on their disease profile.
Flatiron Health is in the midst of a pilot to develop the best cancer treatment options using big data. It wants to give physicians access to more meaningful data from a larger patient population. The long-term goal is to give them a better sense of the best treatment options for their cancer patients depending on the type of cancer they have. It also seeks to improve participation in clinical trials. Its platform offers automatic tracking against clinical, operational and financial metrics, monitoring of adherence to national standards, custom guidelines and flexible query and visualization tools to identify trends and patterns in each provider’s cancer patient population. Institutions can see data for their own patients that they are treating but data from other institutions is de-identified.
Eviti launched its Philadelphia-based clinical decision-support program for oncologists in 2009, gaining market entry through payers. It gives oncologists free access to its digital cancer treatment library. More than 1,800 oncologists have accessed the library. It contains data from more than 9,000 federally registered clinical trials and 1,200 evidence-based treatment regimens for 120 cancer types derived from government and industry data.
