Turning genomic challenges into opportunities
About 14 years ago, the Human Genome Project completed a high-quality sequence of essentially the entire human genome. While the subsequent knowledge and technology has progressed at a rate previously unseen in science, many of the original challenges and opportunities still exist today.
Nothing has diminished the unstoppable force of consumer demand in this arena, but healthcare providers and policy-makers remain woefully ill-equipped to deal with the massive amounts of patient-driven and growing clinical data. There remain many obstacles to wide-spread adoption of genomics at the point of care, including:
Challenge: Cost of testing
Opportunity: Value of early detection and intervention
Cost of testing is often cited as a barrier to entry, even as the prices for exome testing continue to fall dramatically. But focusing on the initial cost is short sighted, and diminishing cost of diagnostic testing will not be the rate-determining step in the adoption of this essential new technology.
Return on investment in genomics seems quite clear in many instances. For example, avoidance of genetically determined ineffective drugs or adverse reactions, or early treatment of newborn diseases. There is growing evidence that earlier detection of genetically-influenced illnesses will result in decreased morbidity and mortality (which translates to cost avoidance).
Challenge: Exchange of genetic information
Opportunity: Access to actionable data
Healthcare data must flow between systems in a meaningful way to be impactful. Consider genetic risk factors for bleeding tendency or certain anesthetic reactions found incidentally. These may only be relevant (even crucial) at the time of emergency surgery.
Standards of interoperable use of genomic data is only the first step. The ability for electronic health record (EHR) systems to consume this data is a necessary first step, but much more needs to be done. A necessity to meaningfully display appropriate information where and when it is needed will create many new opportunities in the field of information technology.
Challenge: Knowledge gaps in genomics
Opportunity: Education and real-time access to research findings
Many highly competent physicians, who maintain their Continuing Medical Education requirements, continue to have knowledge gaps in the ever-expanding field of genomics. And, as diagnostics moves away from individual tests and panels to full exome or even full genome, providers will need to understand and deal with the huge number of incidental Variants of Unknown Significance (VUS).
Interpretation of complicated and often ambiguous reports will require new ways of presenting and visualizing data. As science progresses and some of these variants become known, cloud-based repositories of genomic data will be essential. Continual updates of these data sets along with tools to notify providers and patients will be crucial. Clearly there is much to be done both in education and applied science.
Challenge: Expert interpretation of results
Opportunity: Point-of-care resources to support clinicians
Traditionally, physicians have relied on highly trained genetic counselors to help them navigate complex reports, suggest follow-up studies and assist in communication to patients. Unfortunately, there is a current paucity in genetic counselors, and the shortage of these specialists is increasing at a potentially alarming rate.
This shortage will place increasing demand on both primary care physicians and specialists to guide patients in interpreting genetic reports. They most certainly will demand point-of-care resources to help them order and assess genetic tests. With an increasing burden on patient-facing clinicians, there is an opportunity to create both automated and virtual genetic counseling.
Challenge: Uncovering phenotypic data
Opportunity: Predictive tools for modeling outcomes
Phenotype is formally defined as the set of observable characteristics of an individual resulting from the interaction of its genotype with the environment. There is much work to be done in describing phenotype as we compare it a patient’s known genetic makeup.
We will also need to contend with data derived from the much larger umbrella of omics, such as the evolving fields of proteomics, epigenetics, viromics and the impact of the microbiome. This will demand better tools for collecting and modeling other types of information such as family history, psychosocial factors, occupational and environmental exposures.
This an exciting time in medicine. Advances in immunotherapy and targeted genome editing, such as CRISPR/Cas9, are racing forward in parallel with unprecedented commercial and consumer opportunities.
The mapping of the human genome is now old news. It’s time for clinicians and healthcare delivery systems to have the proper tools to use this knowledge. By defining the challenges and opportunities that exist in this evolving field of medicine, we can work together to overcome these barriers so genetic information can be integrated meaningfully into everyday practice.