What is technology’s role in advancing or accelerating precision medicine?

Technology is transforming precision medicine on multiple levels:

• Biomedical insights and life-saving discoveries are happening because of the explosion of data made possible through lower-cost genomic sequencing and technological advancements.

• Researchers trying to make sense of this tsunami of data benefit from having industry-standard, Intel® based, high-performance computing solutions that cost-effectively ingest, store, process and analyze all of this data.

• As new discoveries enabled by genomic analytics move beyond research, they are integrated into clinical care settings to diagnose disease and tailor treatments based on the unique genetic make-up of individual patients.

What challenges has Intel been able to help research departments at healthcare providers address?

The pressure to accelerate biomedical discoveries in a predictable, reliable and cost-effective manner is key. When considering that genomic data sets double in size every eight months, that’s a big challenge. We have collaborated with researchers and partners to create solutions that result in faster processing of high volumes of data for less money.

For example, we collaborated with QIAGEN Bioinformatics, a global molecular insights solutions company, to develop a high-performance computing cluster reference architecture that could match the output of today’s fastest next-generation sequencing devices while delivering fully analyzed results for as little as $22 per whole genome.

We’ve also collaborated with the Broad Institute of MIT & Harvard to optimize the Genome Analytics Toolkit. The 54,000 registered GATK users can not only upgrade to open source GATK4 without purchasing a commercial license, but also enjoy a fivefold increase in performance and scalability when running the latest GATK4 pipeline on Intel’s latest hardware stack. We continue to work with leading commercial and open-source authors of key genomic codes to optimize those codes and ensure that genome processing runs as fast as possible on Intel-based systems and clusters.

What can hospitals do to prepare and bring precision medicine into the point of care?

Initial steps include:

• Establishing a cross-functional team. In the case of precision oncology, it could consist of pathologists, oncologists and medical tumor boards along with support from executives who can collectively look at the end game and determine the policies and processes that need to be addressed from a governance perspective.

• Picking a clear initial use case and tying it to measurable ROI. An example would be lowering the overall cost and improving outcomes for certain advanced cancer patients by using molecularly guided, targeted therapies and measuring the durable response rates or progression-free survival compared to standard chemotherapy regimens.

• Negotiating with payers under a conditional coverage agreement where the payer covers the cost of genomic sequencing for patients if the healthcare provider collects follow-up data and can show value over time.

• Determining if it makes more sense to outsource or invest in an in-house CLIA-certified lab/diagnostic test environment to do the sequencing and bioinformatics.

• Engaging with technology partners who can help integrate precision medicine technologies into clinical decision support systems.

What innovations should the health IT industry be prioritizing to help accelerate precision medicine?

First and foremost, we need data standards, meaning that everyone is speaking the same language, so all that data can actually be used to benefit patients.

We’ll need better visualization tools with simple dashboards, so doctors can make sense of the data. We’ll need new algorithms to help determine the predictive and prognostic biomarkers that best connect patients with the most appropriate combination therapies being explored today. And we’ll need data exchanges to help pharmaceutical companies with novel targeted therapies find patients who are molecular matches for their clinical trials.

Finally, we’ll need artificial intelligence and machine-learning capabilities to help researchers and doctors not only understand which mutations are important in a tumor, but also which therapies would be most effectively combined to help a patient.

What steps should a healthcare organization take to prepare for the future – i.e. “future-proof” their organization – to offer precision medicine that is both cost effective and outcome driven?

First, decide which departments will benefit the most and make a strategic, executive-level agreement to invest. Oncology should be a clear target because patients are beginning to realize the “one-size-fits-all” approach to cancer care doesn’t work. Next, look at your existing workflows and determine what needs to change, from pathology, which receives the samples, all the way to molecular tumor boards and clinical decision support tools, where a molecular diagnosis and treatment plan is brought together. Finally, articulate what success looks like in three years and consult with technology solution providers to determine how to achieve those goals. A combination of in-house capabilities and third-party resources will help you move quickly from samples to clinical insights for your patients.