The genomics industry has tremendous potential to move the needle in health. Delivering on the promise of genomics depends on three main factors—many of which are within the purview of digital health.
The genomics industry has tremendous potential to move the needle in health. Thanks to a number of high-profile investments and initiatives—such as President Obama’s Precision Medicine Initiative (and the launch of its 1 million participant Cohort Program this past month)—consumers are becoming increasingly aware of genomics and its role in healthcare.
The value of the genetic code remains an untapped opportunity in healthcare, and a formidable challenge to the physicians, scientists, and technologists responsible for driving the industry forward. In this report, we explore an industry at a critical inflection point. Despite an unprecedented drop in sequencing costs and technological advancements, genomics has not yet achieved mass consumer appeal or seamless integration into clinical workflows. Delivering on the promise of genomics is dependent upon three main factors, most of which are within the purview of digital health: (1) ensuring broad access to diverse data sets used to deliver insights (2) removing barriers to clinical workflow incorporation, and (3) advancing technology, both in the lab and in the cloud.
The field of genomics has incredible promise for improving and personalizing health. But, just as the genome itself has remained relatively elusive for decades since its discovery, so too are the solutions for integrating genomics into healthcare at scale. We hope to shed some light on the challenges and exceptional opportunities of genomics for healthcare and technology.
The clinical opportunity for genomics is extensive, however consumer engagement is necessary for this potential to be realized
One of the primary aims of genomics is to generate personalized and actionable insights that lead to better health. Because much work is still needed to understand how genes influence and interact with a person’s health, scientists need greater amounts of diverse genetic and phenotypic data (e.g. personal information)3 and unfettered access to those linked data sources.
Genetic data in the ecosystem increases when consumers buy direct-to-consumer genomics products, opt in at the physician’s office to get a genetic test, or participate in clinical research trials. The genomics industry can and should encourage participation at these touch points. Currently, this is being achieved in three ways: (1) Awareness around the field of genomics, (2) Better consumer genomics products, and (3) More relevant consumer use cases. The US government is increasing awareness by funding well-publicized initiatives, such as the Precision Medicine Initiative, while companies, like 23andMe, are providing better consumer products that are easier to order and understand. Lastly, diagnostic companies and research institutions like The Broad Institute are uncovering novel associations and use cases that spur interest in consumer-facing products.
Consumer genomics use cases fall into three categories; applications vary in their ability to offer clinical and personal utility.
Consumers and patients derive two types of benefits (or utility) from a genetic test—clinical utility and personal utility. Clinical utility is relatively straightforward: Does this test change my potential course of treatment? Does knowing that I am at increased risk of a disease change how I make decisions with my doctor? Personal utility is more nuanced and depends in large part on how the consumer processes and makes use of the genetic information. For example: Does learning about my personal genealogy bring me happiness? Will sharing this data with family members or a physician be meaningful to me, even if there is little reward in terms of clinical actionability?
Currently most genomics companies provide value to pharma, enabling drug discovery and personalized medications.
Genomics companies not focused on pharma currently have fewer opportunities to sell their solutions; only a handful directly sell to consumers.
Although genomics companies still overwhelmingly serve the life sciences sector, this is subtly shifting as technology powers use cases outside of the research lab. For example, of the roughly forty venture-backed genomics firms selling to the care delivery ecosystem, many focus on enabling a more personalized ecosystem. Syapse, for instance, accomplishes this by providing clinical workflow integration tools, while others, such as InformedDNA, provide an end-to-end genetic testing solution that spans patient matching to counseling. Other companies provide diagnostic solutions, most often related to prenatal testing and oncology drug matching. The vast majority sell to physicians who intermediate between the test and the consumer. Of the few companies selling genetic tests directly to the consumer, most are focused on the ancestry and genealogy market, highlighting the many regulatory challenges in the direct-to-consumer market4.
Only a few genomics companies sell directly to payers or employers5, primarily on the premise that their products deliver healthcare cost savings via improved predictive power. For example, BaseHealth’s platform allows payers and employers to understand population-wide risk factors, using genetic data as one input to mitigate risk. These types of tools are still relatively nascent, likely because of the dearth of evidence needed for large systematic changes.
Data ownership and corresponding payments are complex; multiple stakeholders extract and produce value from data throughout the cycle.
Data comprises the backbone of many genomics business models. In genomics, just as in healthcare, data ownership (which we define as having control over when and how data is used) often exists in a gray zone. Although the Obama administration has issued guidance that patients should have access to their medical records (including genetic test results), the stakeholders that “own” genetic data are not necessarily the entities that interpret or digest that data or are involved in its creation.
As an illustrative example, let us assume that a health system wants to better understand (“comprehend”) the impact of oncology interventions within a given population. To do so, the system may pay a third party vendor to help compile various data sources (“aggregation”) and may rely on its physicians to ask patients to opt into genetic tests or research studies (“creation”). The role of these three stakeholders is critical for the data flow; yet, it is often ambiguous who owns the sample, the deidentified data, or the identifiable data. The health system? The aggregator? The consumer? This case, like many others, would depend on the specifics of the research study and patient consent forms, which may not be salient to the consumer. In addition, the DNA and data itself takes many forms and may be stored physically in gene banks, in the cloud on health system servers, or across multiple sites.
More work is needed to clarify ownership policies not only for consumer privacy and protection, but also for companies whose business model relies on the assumption that they can extract value from owning consumer data6. Companies who enter the genomics space with a data acquisition strategy need to be prepared for the complexity in how data and money are transferred (and need to get comfortable with nebulous regulations that may change).
Consumers’ interactions with genomics companies are likely shifting from one-to-one to one-to-many.
The business models of many genomics companies rely on proprietary consumer data (both phenotypic and genetic). Two future data ownership business models could emerge. Today, most consumers are relatively monogamous with a single genomics company and submit a sample only once. However, as tests become cheaper and companies expand and differentiate the value they provide, consumers are likely to share their samples or their processed-DNA with multiple companies. Helix promises a third model, in which a consumer shares a sample once but has access to an infinite number of use cases.
Digital health funding has made up a small, yet steady portion of overall genomics funding due in part to the complexity of the space.
Testament to the potential of genomics is the influx of capital from both private and public funders. We looked specifically at venture funding over the past five years and found an upward trend, with total funding of genomics companies amounting to just over $2.2B7. The recent uptick in 2015 and Q1 2016 was driven by a handful of large deals (Helix and 23andMe both received over $100M in 2015; Grail and Guardant both received $100M in Q1 2016).
While genomics has always had strong life science roots, it has only recently become more integrated with technology and cloud solutions at scale. Funding for digital health genomics companies (genomics companies with an essential technology component8) comprised half of overall genomics funding in three of the five years. Technology continues to drive consumer, provider, and health system engagement by enabling easier-to-comprehend products, more relevant use cases, and better clinical workflow integration. While technological advances in life sciences enable more efficient research, digital health has the potential to facilitate the integration of genomics into healthcare.
Liquid biopsy technology (which promises non-invasive cancer detection) has recently gained attention due to a number of large clinical trials in place and substantial funding events (e.g. Guardant and Grail). Actual clinical adoption is relatively nascent but is expected to expand pending favorable results.
Lastly, although we do not delve deeply into the investors behind genomics, it is important to note that Illumina has been instrumental in propelling the industry forward. Beyond its role as an industry leader, it has spun out two potentially transformational companies (i.e. Grail and Helix), funded a number of early stage startups through its business accelerator program, and plans to do more via its recently announced $100M venture fund (Illumina Venture).
Many niche, fragmented point-solutions have emerged across the genomics value chain.
In order to better understand how companies package their tools and services into products, we analyzed five elements of the genomics value chain: sequencing, analytics, interpretation, aggregation, and the marketplace. Nearly forty percent of venture-backed genomics companies offer a pure-play solution, focusing on only one element of the genomics value chain, while none provide solutions across the entire continuum. One reason for this is that researchers and labs have dozens of highly specific needs, and many vendors choose to meet a specific use case, often only for a handful of clients.
There is substantial demand for a completely outsourced diagnostic solution, and many companies (39% of venture-backed firms) provide a bundled sample-to-insight product for providers and health systems. The majority of firms tackling sequencing are providing ‘sequencing-as-a-service’, often relying on Illumina’s Next Generation Sequencing (NGS) technology for the process itself. No other combination of services exceeded 10% of the sample, suggesting that other offering models fail to capture value or are not currently feasible.
A new element of the value chain has emerged recently: the marketplace. A marketplace is a centralized repository of data that provides broad data access across multiple stakeholders. Marketplaces make it possible for consumers to provide a sample only once, and to continue to derive value from that sample over time as companies provide new use cases and as research emerges on correlative relationships. Helix, which is funded by Illumina and other investors, is the only venture-backed firm at the time of writing to promise a marketplace-like product.
All of these things (sequencing, data aggregation, sophisticated analytics, reaching patients) have been done before, but they haven’t been wrapped up into one before. It’s a matter of bringing things together, not reinventing the wheel.
Novel partnership models have emerged because comprehensive end-to-end solutions have not been feasible.
As most companies do not offer end-to-end solutions, genomics is often propelled forward by partnerships. To better understand these dynamics between and across companies, we built a database of roughly two hundred genomics company partnerships (launched between January 2015 and April 2016).
The largest category—capturing nearly half of all partnerships analyzed—consists of a product partnership (i.e. a genomics company partnering with another firm). For example, in March 2016, 23andMe announced that its software integrates with Apple’s ResearchKit app, allowing consumers to share their genetic information with researchers. With consumer consent, researchers can analyze participants’ behavioral/phenotypic data (captured via iPhone or Apple Watch through ResearchKit) and genetic data from 23andMe to identify novel genetic correlations10. (Read more on this trend in our The Emerging Influence of Digital Biomarkers on Healthcare report.)
Partnerships between various government organizations and private companies (10% of our database) have largely been spurred by President Obama’s Precision Medicine Initiative, announced in 2015. Initial efforts will focus on expansion of cancer research, followed by research on other common diseases such as diabetes and Alzheimer’s. The White House has agreed to fund the NIH $130M, the NCI $70M, the FDA $10M, and the ONC $5M to facilitate precision medicine in partnership with private companies. For instance, the FDA is working with DNAnexus on precision FDA, which will create a platform for centralizing genetic testing results and ensuring high quality standards.
Pharmaceutical companies have allied with genomics companies to discover new therapeutics or identify genotypic and phenotypic correlations. One of the largest of these partnerships (as measured by the expected length of partnership and number of genomes sequenced) is a ten-year deal announced in April 2016 between Human Longevity Inc. (HLI) and AstraZeneca, in which HLI will sequence 500,000 genomes from AstraZeneca’s clinical trial populations. AstraZeneca plans to use the data to identify new drug targets and add insights to HLI’s Knowledgebase, which HLI claims is the most comprehensive of its kind. AstraZeneca will also have access to the proprietary Knowledgebase to inform clinical trials, augment biomarker discovery, and facilitate drug development.
Lastly, we identified roughly 60 relationships in which health systems and vendors have joined forces (often simply as customer/vendor) to deliver precision medicine effectively. Syapse’s efforts with Intermountain Healthcare and IBM Watson’s work with Columbia University Medical Center highlight two examples in which health systems are leveraging actionable insights from genomic data to personalize oncology treatment plans.
It’s a gold rush into data, and there’s the question of how much value can we add? Let’s make it useful for the patient, first.
Consumer adoption of genetic testing is key to extracting insights and value from genomics by increasing the amount of information available to researchers. Although interested parties have painted a partial picture of consumer preferences for genomic data, we wanted to provide novel data regarding adoption, willingness to pay for specific use cases, and general trust of companies in the space to help inform company products and offerings.
We surveyed over one thousand individuals who were representative of the US adult population11 in an effort to answer the following: (1) How does adoption of genetic testing differ by use case? (2) What are individuals’ attitudes toward data sharing, ownership, and privacy? (3) Do individuals think about genetic data differently from traditional health data? and (4) How much are individuals willing to pay for knowledge about themselves and their health?
Most consumers had not previously taken a genetic test. Those who had, did so mainly for clinical reasons.
At least half of consumers were open to taking a genetic test in the future; most sought to satisfy personal curiosity but half wanted to know more about potential disease risk.
The survey suggests that consumers are willing to pay for knowledge about themselves, especially for information that is otherwise opaque.
Consumers are much more willing to share genetic data with their physicians and families than other entities; some concerns remain about sharing data with insurers.
Consumers wanted to be stewards of their genetic data; contributing to the greater good was a stronger motivator than receiving money to share data.
A successful $100M revenue genomics company will be one that creates a solution that consumers understand and allows the consumer to be in control of all of their tracked and collected health data. But, how does that exist when data isn’t centralized or interoperable? Interoperability and APIs are the key.
In order to obtain broad consumer utilization, genomics companies need to consider three primary adoption challenges.
Despite technological advances in genomics, human talent is in high demand and required for continued progress in the field.
Due to a reduced regulatory burden, companies are more likely to go after wellness use cases first.
Companies that can overcome regulatory, reimbursement, and data hurdles will ultimately provide tremendous value to patients and see big gains. Consumers want and will have access to their genetic data. It remains to be seen whether physicians and experts will continue to serve as intermediaries in making sense of the genome, or whether we will reach a point in which consumers can be stewards of their own data. For now, it is clear that health systems are well positioned to move the needle in genomics, as they collect data and increasingly rely on evidence to drive clinical decisions. As science continues to make sense of the three billion base pairs that comprise the human genome, we’re excited to see its impact on the healthcare sector and on people’s health and well-being.
Informatics tools will become more standardized and the FDA will help push that along. Testing will become a commodity. And interpretation of genetic variants will also become a commodity as free public data sources proliferate.
Source: Survey by Rock Health (rockhealth.com)