Solving the Life Science Industry’s Big Data Challenge

Solving the Life Science Industry’s Big Data Challenge

Travis A. McCreadyPresident & CEO, Massachusetts Life Sciences Center

The amount of health care data generated every year is growing at an astronomical rate.  According to Stanford Medicine, in 2013 there were approximately 153 exabytes of health care data generated globally (where one exabyte is equal to roughly one billion gigabytes).  By 2020, it is estimated that amount will grow over 15 times to 2,314 exabytes.  In the life sciences, by 2025 genomics data alone is expected to equal or exceed data generated by the combined totals from YouTube, Twitter, and astronomy, the three other leading data producers.

Over the past decade, a major focus in the life sciences and basic research has been accessing, creating, and leveraging new tools that will generate new data and thereby new understanding of the human body – from digital images to mechanistic data at the cellular or even molecular level.  For example, with a $5 million grant from the Life Sciences Center, the University of Massachusetts Medical School opened a facility for high-resolution electron cryo-microscopy (cryoEM), helping private companies and research institutions make discoveries on biological systems at the near-atomic level.  With over 90% uptime and 22 public and private partners, the cryoEM facility is producing over 100 datasets a year, each dataset the equivalent of about a petabyte (roughly 1,000 terabytes).  With these sorts of experiments running, it is no surprise that the size of global data centers cannot keep pace with the amount of medical data generated.

However, at the same time that researchers, scientists, and individual consumers are generating vast amounts of data, we cannot lose sight of what these data mean and the opportunities to connect data to better serve health care consumers’ needs, open up new business opportunities, drive efficiency and efficacy in health care, and, simultaneously, pull the lens back to focus on population health.  This is the true ‘big data challenge’ acutely felt by every pharma/life sciences leader in the world, especially in Massachusetts.

Silhouette

Analytics and advanced diagnostics is one of the most exciting areas we see big data transforming the life sciences ecosystem.  By leveraging connected data and employing more sophisticated algorithms and artificial intelligence, treatment of illness can be more predictive, proactive, and efficient, a boon to public health and the individual patient alike.  Imagine a late-stage cancer patient with three treatment options, each lengthy and expensive, and each only effective with 20% of the population with that particular cancer.  Which should the physician prescribe? A non-response would not only be detrimental to the patient, but it would be costly and wasteful to the system.  What enormous benefit could be derived from an advanced diagnostic that, based on available data from cancer tissue samples, biomarkers, etc., would accurately predict drug efficacy and help guide treatment decisions.

Olaris Therapeutics, and founder and CEO Dr. Elizabeth O’Day, is one of a growing number of life sciences companies answering the advanced diagnostics call.  Dr. O’Day uses a pioneering metabolomics platform and proprietary machine learning algorithms to fundamentally improve how disease is diagnosed and treated. Olaris identifies biomarkers of response to stratify patients into optimal treatment groups, increasing survival rates, decreasing adverse events, and reducing unnecessary healthcare costs.  Any patient or family member that has suffered through the guesswork of cancer treatment can immediately appreciate the promise of Olaris’ technology.

The global life sciences analytics marketplace is expected to grow from $13 billion in 2016 to $25 billion in 2021.  With companies like Olaris, there is a good chance Massachusetts can capture a significant portion of that growth.  But in order to remain a dominant global leader in this new era, we must coalesce around a statewide big data strategy, and shift away from thinking that the life sciences only happens in wet labs and academic medical centers.  We must grasp, and prepare to execute on, a simple yet profound paradox – the fundamental unit of the next life sciences revolution is not living at all; it is the inorganic byte of data.

Want to hear more? Travis will be moderating the ‘Innovation Spotlight Changemaker Presentations’ on day 1 of the AI Applications in Biopharma Summit. Click here to reserve your place and join the conversation.

All

Related Events