The Greatest Medical Advancements Of The Future Will Originate In Data-Driven Enterprises

October 24, 2019

Contributed Commentary by Ryan J.W. Swenson

October 24, 2019 | A cure for the common cold—both a cliché and metaphor to describe a medical impossibility—isn’t so far-fetched anymore: Researchers around the globe continue to crunch data searching for a vaccine that can neutralize an estimated 160 rhinovirus strains. When that happens, expect the news to dominate headlines for weeks.

Meanwhile, thousands of exceptionally promising healthcare milestones—particularly in the areas of bone marrow matching, disease prevention, cancer research and predictive analytics—are occurring at unprecedented rates because they’re taking advantage of: a dizzying accumulation of exploding amounts of real-time data; flexible, modern data platforms that can run anywhere—from the edge to the cloud including hybrid cloud and multi-cloud; and continuing advancements in AI-powered data analytics allowing them to ask bigger questions, gain deeper actionable insight to help save lives and deliver significant healthcare breakthroughs.

Accommodating the data explosion is critical. Data—and making use of it—resides at the center of it all. The growth of health data has increased 878% since 2016, and the market value of big data healthcare analytics is expected to reach $22.7 billion in four years. And with studies predicting the volume of healthcare data will grow faster than practically every other sector through 2025, healthcare organizations need to be innovative in how they process, store and analyze data.

Where is this data growth coming from?

  • Higher frequency of next-generation sequencing from its increased application and usage in healthcare which, in turn, produces enormous amounts of data from the ‘omics universe: genomics, pharmacogenomics, metagenomics, proteomics, metabolomics, environomics, etc.,
  • advancements in medical imaging, videoscopy technology and digital pathology, and
  • a wide range and increasing variety of real-world data from new sources such as the Internet of Things (IoT) and mobile/web applications.

The right data solutions are helping them tackle and solve the greatest variety of healthcare and life-sciences analytical use cases in the most cost-effective and secure manner, while also delivering the following benefits:

  1. Reduced costs

The costs of doing business in the healthcare sector have risen astronomically over the past two decades, with the consumer/patient bearing a large brunt of the burden. As one of many examples, bringing a drug to market averaged $802 million in 2003, and 13 years later it had exploded to $2.6 billion. That means these organizations—whether they’re clinical, scientific or pharmaceutical—are looking not only to streamline their processes but arrive at quicker actionable insight to address the many areas attributing to higher healthcare costs.

  1. More flexibility to scale

One of the greatest benefits of having a multi-cloud framework is the ability to quickly scale up and down, especially with on-demand or pay-per-use services. While the biggest cloud providers promise those capabilities, seasoned architects, DevOps and developers realize that this cannot be accomplished overnight. They also recognize the need to tread carefully into multi-cloud, especially in the cases of intellectual property issues and trust issues with new third-party vendors.

  1. More insights

Colossal amounts of ever-expanding digital information are creating greater data-driven insights, enabling healthcare organizations to support diagnostics, patient risk analysis, precision medicine, real-world evidence research, patient monitoring and alerting and more. And, of course, the right combination of data engineering, warehousing and ML enables them to act on an increasing variety of data, offering the greatest benefit of all: the ability to improve, extend, and save lives.

Just in the last year, we’ve seen dozens of examples of that, including these:

  • Bone marrow matching

The National Marrow Donor Program and its Be The Match Registry—the largest bone-marrow matching program in the world—is able to analyze potential recipients’ human leukocyte antigens (HLA) to match patients and donors. Physicians have performed 92,000 blood stem cell transplants to date and nearly 6,200 transplants every year, giving patients better hope for the future.

  • Disease prevention

GlaxoSmithKline technicians have gained a holistic view of all data within R&D, totaling more than five petabytes across 10 different domains including discovery, clinical, genomics and other data from more than 2,000 silos. They are pairing over 10 years of genotypic data for 500,000 patients with whole exome and genome sequencing, resulting in innovative methods to treat metabolic disorders, cancer, pulmonary, urologic, cardiovascular and many other types of diseases.

  • Cancer research

Researchers are analyzing patient treatment records and tumor samples in biobanks, then studying how proteins are interacting with each other and with cancer-associated mutations to find trends that can improve patient outcomes.

  • Predictive analytics

A Florida healthcare technology company has developed a machine learning-powered platform that can monitor upwards of 40 separate real-time data feeds of ICU patients to warn staff of patient deterioration as much as two days before it occurs.

  • Hybrid data management systems are the way forward

Groundbreaking healthcare advancements today require the ability to collect, store, process and analyze ever-increasing types and volumes of data. By deploying a flexible, scalable, cost-effective, hybrid data management system in a multi-cloud environment, providers and researchers will be better able to leverage the type of AI, ML and data analytics they need for innovation while ridding themselves of the burden of siloed architectures.

The healthcare organizations that do embrace flexible, open-source data management systems will be the ones solving the medical world’s greatest mysteries—and maybe even finding the forever-elusive cure for the common cold.

Ryan J.W. Swenson, Global Leader, Healthcare and Life Sciences, Cloudera, has guided healthcare and life sciences organizations globally in over 30 countries for the last 22 years, in a variety of roles spanning research, informatics, data engineering, software engineering, consulting, and business development. Ryan joined Cloudera from Dell Technologies, where he was previously the senior director for healthcare and life sciences in product management. At Dell, he was instrumental to building one of the world's largest object storage and big data services (Apple I-Cloud) and led the development of genomics, machine learning, and big data As-a-Services, precision medicine, and EMR solution and services offerings for Dell Technologies businesses, Dell EMC and Virtustream.  Ryan has also led a number of biomedical and biotechnology ventures and has served in numerous data engineering, informatics, and consultancy roles, most notably at SAS Institute, VMware Corporation, IBM, Computer Sciences Corporation, NYC Health and Hospitals Corporation, Kaiser Permanente, and Medstar Health.  Today, Ryan manages over 200 global healthcare and life sciences customers and develops healthcare and life sciences solutions as the Senior Solutions Manager in Cloudera's Industry Solutions and Partner Engineering team. He can be reached at