Data: Medtech’s Emerging Asset. Is Acqui-Data to become the new Acqui-Hire?
For decades, the medtech industry has been seeking to capitalize on the value of data with limited success, but with improving data capture and the use of AI, the promise is turning into reality.
In the 1990’s Medtronic introduced its Reveal implantable loop recorder that traced cardiac data. The concept behind the business was to charge physicians for the information and use it as a tool to identify patients who could benefit from the company’s pacemaker technology, driving primary demand. Without reimbursement for physicians accessing the information, the stand-alone data capture device did not take off. Yet, the data captured in existing implanted pacemakers and defibrillators was of immense value to clinicians as they optimized the ongoing cardiac stimulation protocols for each patient. As a venture capitalist, I met with dozens of companies that envisioned tapping into various data sources to mine them to develop treatment paradigms, but the companies never quite achieved success.
In the early 2000’s a frequently proposed business idea involved mining through records for the best treatment protocols. One Philadelphia company had access to a huge database of images, and their plan was to tie the image data with clinical data such as patient longevity, tumor progression, and treatments to develop better care pathways. Those businesses did not achieve success for a variety of reasons with the largest challenge being the inability to standardize data and effectively tie it to the images.
But over time advancing science, investment sentiment and computational technology continued to evolve. These three factors changed the paradigm around data driven business models.
Scientifically, the advent of whole-genome-sequencing exploded the amount of data available to researchers and clinicians. The genetic information contained in the 20,000 protein coding genes in the human body provided a treasure trove of fodder for analysis. The relative concentrations of certain genes in a tumor or patient’s DNA signature could guide clinicians to the best drug regimen, the patient’s prognosis, the likelihood of recurrence and even susceptibility to a certain type of cancer. Since then, research has identified a host of additional genetic factors around the basic gene profile that influence disease.
Investment sentiment around diagnostics changed in the late 1990’s as the sector blossomed to an area of opportunity from a venture capital pariah. Under the leadership of Brook Byers, the venture capital firm Kleiner Perkins catalyzed the change through the development of Genomic Health. The innovative company created a successful test that used a genetic profile to determine whether a breast cancer patient could benefit from drug-based chemotherapy. The pharmaceutical regimens are expensive with a nasty side effect profile, so avoiding ineffective use spared patients discomfort and saved thousands of dollars. The significant savings made the cost of $3400 per test, money well spent. This pivotal company started the ball rolling as the investment community realized that genetic information could answer expensive and important questions. Genomic Health was the first domino in a series that includes today’s Care DX, Guardant Health, Natera, and a host of others.
Finally, technology advanced to capture, store and analyze enormous amounts of data at ever faster rates with lower costs. In the early days of genetic sequencing, managing the data associated with the three billion base pairs was a huge logistical challenge. But over time the technologies managing those processes have improved many times over.
Companies who are building data repositories are creating a sustainable competitive advantage.
In neurology, Neuropace has a growing cohort of epilepsy patients with their implantable RNS devices that are actively tracking EEG activity as they remain on alert for signs of an impending seizure to interrupt its formation through selective targeted stimulation. Importantly, this data can help company engineers refine their algorithms to improve the device’s performance. The Neuropace business enjoys protection from a six-year long moat for completing clinical trials. But now a hypothetical competitor would be hard pressed to produce equivalent performance without access to the knowledge contained in that data.
Another emerging epilepsy data player is Epiwatch, which uses an AppleWatch to track seizures in patients suffering from the condition. Remarkably, a sizable portion of these patients cannot provide their physicians with accurate data on seizure frequency. For example, if a seizure occurs at night while asleep, the patient may be completely unaware of it but have a sense that something might have occurred due to morning soreness or fatigue. As Epiwatch builds its database, the company’s product development team will be able to adjust the watch’s sensitivity to further improve performance. Other important insights may emerge such as objectively quantifying the effectiveness of treatment regimens.
Another exciting company, Cerebell, detects previously unrecognized seizure activity in medicated ICU patients. The company’s headbands feed brainwave data into its software system to identify seizures, helping physicians determine appropriate medication levels. The company is evaluating data from thousands of patients, and this will inevitably lead to algorithm adjustments that will improve their system’s performance, making it difficult for others to follow.
In the diagnostic world, cancer screening and recurrence monitoring companies are creating enormous value in their data stores. Investor attention focuses on Natera and Guardant Health who work with solid tumors, but the smaller player Adaptive Biotechnologies developed clonoSEQ to focus on blood-based cancers such as Myeloma and Adult Lymphoblastic Leukemia. The company has rich growing data stores and working relationships with most major pharmaceutical companies who are developing therapies for liquid cancers.
GeneDX Holdings uses genetic profiles to identify rare diseases in children. The company has built the most comprehensive knowledge around the genetic signatures of rare diseases that may affect 1 in 20 families. Clinicians can draw blood from infants in the neonatal intensive care unit (NICU) to send to the company for analysis. From my work with the diagnosis of infant hearing disorders, I know that the early interception of these problems can make a tremendous difference by improving the child’s health and development while reducing costs. Importantly, the knowledge in this company rises as their database of patient profiles grows.
One other medtech company building value through data is Intuitive Surgical, which is tracking a host of parameters and metrics through its robotic systems. It is hard to say exactly how they will monetize this information in refining their product development and customer retention efforts, but I am sure there are very smart people pondering this question.
Artificial Intelligence (AI) adds value to the data stores held by these companies by making it possible to find patterns that are not discernable in conventional correlation studies. Typically, these insights are simply too small and multifactorial for Excel analysis to find.
In the software world, companies acqui-hire buying companies to get talented employees. In the medical world, acqui-data may be the new thing. In 2018 Roche acquired Foundation Health because Foundation was on the leading edge of cancer genomic sequencing and that information could be relevant to Roche’s pharmaceutical oncology effort. Now 23andMe a consumer gene profiling company, is in bankruptcy. However, it holds an intriguing asset in the genetic data from the millions of users who have not deleted their information. The 23andMe auction will shed light on industry’s value of data (even if it is a damaged asset.) Within the next two years, we could see access to valuable data stores as being a key motivator for an increasing number of acquisitions.