A place to exchange ideas and perspectives, promoting a thriving innovation economy through public policy
645 Discussions

Getting to the next step with Personalized Medicine

0 0 120
By: Eric Dishman, Vice President and Intel Fellow for Health and Life Sciences for Intel

My story is a unique and lucky one. I have had the benefit of personalized medicine well before its potential was widely understood and certainly well before it is widely deployed. After 23 years, 57 diagnosis codes, 36 rounds of trial-and-error treatment, 3 near-death experiences and more than $6M in cost, it took one round of Personalized Medicine to get to the root of my cancer and ultimately become cancer free. The need to scale Personalized Medicine to everyone is not lost on me.

At the time of my whole genome sequence, many of the analytic tools that help researchers quickly identify variants, the compute power to do such analytics, and the ability to share such massive data sets were simply not widely available. As a result, it took 7 months from sequencing to customized treatment plan —three months of compute time and 4 months of nights-and-weekend dedication of clinicians trying to fax, phone, and FedEx data to each other around the country. Wrestling the big data challenge of Personalized Medicine is a significant hurdle to overcome. Despite those hurdles, through open architectures and standards-based approaches for interoperability, Intel strives to create vibrant ecosystems where data can be secured, stored, analyzed and applied to the world’s biggest problems.

Even today, years after I was cured and brought back to health with a kidney transplant, Personalized Medicine is not available to most newly diagnosed cancer patients in the United States, let alone to those with other diseases where genomics is likely to have a big impact. Less than 1% of cancer patients receive advanced genetic sequencing. Additionally, only 4% of available data on cancer patients is available to researchers. The other 96% is held closely in institutions who are either unable or unwilling to share. As we look to technology to help facilitate sharing data and ultimately insight, we are confident that we can help accelerate the research and get to Personalized Medicine for all much faster.

Today, I am in Washington, D.C., attending the Precision Medicine Initiative Summit led by the National Institutes of Health (NIH) to share my story and describe the work Intel is doing to advance Personalized Medicine. This is a step toward creating the 1 Million cohort, as set forth by the Precision Medicine Initiative (PMI), which aims to better understand genetically driven diseases and to accelerate cancer research through much-needed additional funding.

Intel believes that within the next 5 years each person suffering from disease should be able to receive a personalized diagnosis based on their ‘molecular self’ and then receive a targeted treatment plan. Intel believes this personalized diagnosis and treatment plan should happen ‘All in One Day’. We are committed to accelerating Personalized Medicine throughout the United States. To do that, we are taking the following steps in 2016 to support the U.S. Precision Medicine Initiative that President Obama has put into motion for decades to come:

  • Intel will provide a proof of concept and reference architecture for data center hardware infrastructure based upon an open architecture for use at the data cores of each PMI coordinating center, to process, store and analyze PMI cohort data.

  • We will share novel open-source genomic database technology that allows researchers to easily manipulate, retrieve and conduct in-database computing of large scientific data sets – at unprecedented speed.

  • We will grant access to the open source ‘Trusted Analytics Platform’ that can simplify the development and deployment of analytical applications on behalf of the PMI cohort.

  • We will hold 4 week-long training sessions for computational biologists and bioinformaticians, so they can use Intel-developed open-source tools to perform workload characterization.

  • To help drive Machine Readable Consent, we will convene an industry and stakeholder group to create a single set of standards for machine readable electronic consent for patients to donate their data to the PMI database.

  • And we will fund a national workshop bringing  together technology companies, healthcare providers, non-profits and policy leaders to identify and commit to actions to address the top barriers to achieving ‘All In One Day’ precision medicine.

As the 1 Million Americans of the PMI cohort engage to better understand their health and potential genetic drivers of diseases, all Americans will start to benefit from these biggest of big data insights. The life-changing experience I had with Personalized Medicine will start to become the norm and the experience of disease will change as we know it. When researchers and doctors have the data, tools, and training to create a personalized treatment plan based on an individual’s data, life goals, and needs, we will have ushered in a new era that is vital for our families, economy and future. Let’s work together to make that kind of medicine possible by 2020 and make it possible to happen All in One Day.