The advent of Big Data is ushering in a tectonic shift in the field of medical research, one scientists hope could pave the way to snuffing out deadly diseases – including cancer. Over the past decade, the cost of obtaining biological information has plummeted as technology has rapidly improved. Whereas it used to take years to map genomes, researchers can now perform the task on the fly. The changes mean scientists are confronted with near-endless information. The new task is figuring out exactly what to do with it. Specifically, how these vast pools of data can be efficiently mined to help researchers discover new treatments.
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Merging Artificial Intelligence and Medicine Berg Pharma is a microcosm of how these dreams might one day become reality. The company is leveraging big-data analytics to create an assortment of drugs targeting difficult-to-cure diseases. The seven-year-old firm currently has numerous experimental treatments in the pipeline, including ones aimed at skin cancers, solid tumors and leukemia. “The big-data analytics with the way we’re doing our biology allows us to look at what’s gone wrong, and how to fix it,” said Niven Narain, Berg’s co-founder and president. Narain said the human body is akin to the hub-and-spoke model the air transportation system uses. If there’s a snafu at, say, New York’s John F. Kennedy Airport, it can easily spark delays and shutdowns across the country. Berg’s artificial intelligence system seeks the biological equivalents that cause disease in the body. The company then looks to fix the flaws utilizing vast amounts of information, everything from genes and proteins to raw clinical data. In keeping with its business model, Berg has forged a partnership with the U.S. Department of Defense which will allow the company to access thousands of records on prostate cancer in enlisted individuals. “The Centers for Prostate Disease research at Defense Department has done fantastic work over the past 20 years and has amassed what is the most robust data set in cancer, and they’re going to use Berg’s platform to analyze that data set and illuminate the full use of that data,” Narain said. Narain hopes the use of ‘Big Data’ will dramatically speed up the drug pipeline in coming years, and also produce significantly more targeted interventions.Big Data Key to Unlocking Missing Links in R&D
Kathy Giusti is taking a similar approach to Berg’s Narain. When Giusti was diagnosed with a rare, fatal blood cancer she was given only two years to live. That was nearly two decades ago. At the time of her diagnosis, there wasn’t a single drug in the pipeline to help fight or cure multiple myeloma. She founded the Multiple Myeloma Research Foundation with hopes of finding enough resources to create a drug or treatment that would give her then one-year old daughter a chance at remembering her mother. In the years following, Giusti’s foundation has not only contributed to prolonging her own life but those of others suffering from the same diagnosis. MMRF has made significant strides and developed six FDA-approved drugs, with another 26 in the pipeline. Giusti credits the availability of massive amounts of data and the ability to combine data from many places for the advancement and rapid development of treatments for myeloma. She said one of the major areas that really helped accelerate research and development is in genomic sequencing. “You have to do that because if you don’t understand how the cancer cell is changing as they become resistant to drugs, you’ll never figure out how to cure the disease. Sequencing is critically important to identifying subtypes and identifying targets that cross multiple cancers.” Bahija Jallal, executive vice president of MedImmune at AstraZeneca (NYSE:AZ), said drug development is expanding and changing the drug pipeline in many different ways – especially in the cancer research and treatment arena. She said being able to sequence a full tumor and understanding what medications are appropriate to target and treat it is already starting to happen. “The question is: Do we understand everything for every cancer. And no, not yet,” she said. “For some cancers, there are several subsets – some with one mutation or another – that are basically defects in very important proteins, but that only exist in subsets of patents.” In addition to the ability to sequence genomes much more quickly and easily, Giusti said there’s been another shift in technology that’s made cancer research more effective. “Most of our data is going into electronic health records and everything is digitized,” she said. “Those technologies are really facilitating the ability to look at genomic and clinical data over time and figure out what drugs work for which patients.” She said the big shift has been on new drugs and the effort to extend the lifespan of those diagnosed with myeloma. The idea is to find a drug that improves the patient’s quality of life, and then have new drugs available should the cancer return. “If you understand genomics, it’s much more likely you can work toward precision medicine: Getting patients the right combination of drugs based on their specific subtypes of cancer.” Echoing Berg’s Narain, Jallal said this new era of medicine gives doctors and researchers the power to decrease the time it takes to bring drugs to market because they can “zoom in on” specific patients who are more likely to benefit from certain kinds of drugs and treatment options. Giusti believes this new arena is the key to finding a cure not only for myeloma but for all types of cancer. Jallal agrees, and says now the question becomes how to leverage the large quantities of data researchers have so that it can be used to efficiently develop new treatments. “The big hurdles are the diseases,” Jallal said. “Every time we think we understand, when we think we can (cure) it, cancer always will evolve and outsmart us. And we have to come at it with different weapons. The second challenge is bringing science as fast as we can to the patients.”