A growing need for seamlessness in big data research is drawing a wide range of industry and academia entities closer together to accelerate genomically driven precision medicine breakthroughs in oncology. Diverse organizations from teaching hospitals to health IT companies have realized the challenges being faced in healthcare today are too big for any one organization.
Collaborations that amass resources across multidisciplinary researchers have become a top priority for harnessing diverse expertise with minimal administrative, bureaucratic, clinical and technical barriers to increasing the rate of medical advances that can deliver highly targeted and effective treatment.
When the human genome project first began 25 years ago it took nearly 15 years and close to $3 billion to sequence the genome of a single individual. Today it can be done in a few days for less than $3,000, and now, this technology is used to test cancer DNA in precision oncology. Tumors are driven by a variety of DNA changes that make them an ideal model for evolving individualized therapeutics and disease prevention.
Treatments tailored to a patient’s unique genetics have produced numerous success stories in oncology in recent years. The approach can help pinpoint treatment strategies most likely to produce desired clinical outcomes quickly and accurately. At the same time, this approach can also help eliminate treatments most likely to fail. Precision medicine identifies changes in genes or characteristics of cancer cells that signal when an individual’s disease is unlikely to respond well to a given strategy. This alone can save precious time and limited financial resources.
A highly individualized approach, like genetic analyses of patients and their tumors, makes traditional statistical analyses of large randomized trials and clinical endpoints difficult, but essential. It takes time that is often in short supply to go over all the material, make a diagnosis and choose the best therapy.
The rapidly emerging state of this field has also produced a need for ways to deal with large, complex and often still siloed data sets in order to determine consistent guidelines for patient care.
To tackle this growing need, GE Healthcare recently announced a new alliance with Roche Diagnostics that will leverage each of their strengths to create the industry’s first data-driven software that marries in-vivo and in-vitro diagnostics. The new cloud-based applications will integrate a wide range of historically siloed clinical data to help doctors and researchers visualize a solution and provide actionable insights from multiple datasets that previously was not possible.
New immune therapies and combination regimens are becoming available for oncology treatments that require comprehensive diagnostic approaches using new and established biomarkers for patient screening, diagnosis, and monitoring. Advanced analytics tools like the software in development by GE Healthcare and Roche Diagnostics that will arrange this information side-by-side for a comprehensive view can help facilitate more accurate and timely critical decisions.
Integrating genomics data into the clinical workflow using advanced decision support tools are expected to produce learning health systems that follow an evolutionary path similar to those of electronic health records systems.
Given the extensive and far-reaching collaborations, alliances, and other business partnerships such as joint ventures, mergers and acquisitions well underway, state-of-the-art tech to leverage the data that will be produced couldn’t come at a better time.
The large-scale National Institutes of Health (NIH) population genome sequencing project All of Us is a million person biobank expected to provide an abundance of quantitative and qualitative data including individual differences in lifestyle, environment, and biology. Dozens of researchers across industry and academia have agreed to collaborate and share data publicly in pursuit of a common mission to accelerate health research and medical breakthroughs needed to achieve personalized prevention, treatment, and care beyond cancer for everyone.
Another collaboration designed to achieve success faster is the NIH’s $215 million five-year, public-private Partnership for Accelerating Therapies (PACT) with 11 biopharmaceutical companies and inspired by the national Cancer Moonshot initiative. PACT brings together leaders in the field to collaborate on systematic and uniform research into biomarkers in order to identify, validate and develop biomarkers that may lead to innovative immunotherapy treatments for a wider variety of cancers.
Coordinated systematic approaches enabled by the pooling of resources across universities, labs, health IT companies, and other industry members that allow organizations to generate and share data consistently create an environment that makes it easier to replicate trial results, compare data of disparate studies, and ensure a high degree of quality that no one organization or sector could achieve on its own.