The consensus is 2022 was a challenging year for digital health companies. Venture capital and other startup investment in the U.S. digital health sector plummeted to $15 billion from more than $29 billion in 2021, according to Rock Health. Market analysts CB Insights similarly tracked private investment last year in U.S. digital health at $17.7 billion in 2022 — down 56% from $40.2 billion in 2021.
While this undoubtedly marked a steep decline in investments, it was by no means a signal of the end of digital health innovation or opportunities, as 2022 still marked a record funding year historically. Rather, 2022 represents an overdue correction in the midst of global economic uncertainty after a period of overexuberance and lofty expectations in digital health.
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A less-investigated aspect of the recent digital health investment downturn, however, is that not all startups were affected equally, in particular with those focused on the pharmaceutical and life sciences industry faring better in terms of funding and outlook. Investors in 2022 appeared confident that the continued transformation of drug research and development protocols and the overall life sciences industry will not only include digital health solutions, but will even depend on them for data collection, analysis, patient engagement, and even their therapeutic properties. And in the first quarter of this year, the largest Series A ever in digital health ($203M) went into a company accelerating clinical trials and drug development.
Numerous clinical, regulatory and financial factors are behind this digital shift in pharma. Regardless of the reasons, investors, pharma, and research organizations are recognizing that advanced digital health tools will be a significant competitive advantage and generate meaningful return on investment (ROI) in an industry that is becoming more personalized and specialized.
The evolution to the new normal
Given the evolving climate, Rock Health provided the apt advice as: “rather than aiming to ‘disrupt’ the entire healthcare system, focus is best placed on applying practiced skill sets to top healthcare and research problems.”
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One of the most significant research problems that pharmaceutical companies face, which pre-dated the Covid-19 pandemic by decades, is clinical trial recruiting and execution. Participant-related costs, including clinic visits, were the largest contributors to the median $19 million pharmaceutical companies and other sponsors spend per clinical trial each year and the median $48 million spent per pivotal trial.
Technology-enabled decentralized clinical trials significantly reduce or eliminate travel and associated patient management costs and site visits, which can extend beyond 150 visits per patient per trial, while accelerating the pace of discovery. The combined benefits have been estimated to increase the value of the developed therapies from 5x to 13x for Phase II and Phase III trials, according to a 2022 report from the Tufts Center for the Study of Drug Development equating to roughly $10 million and $39 million ROI respectively.
Further accelerating trial pace, artificial intelligence (AI) and machine learning data science tools are being explored to create “synthetic data” as a proxy for the control arm of randomized clinical trials to reduce the need for real-live participants. Synthetic data has already been used to obtain accelerated regulatory approval both inside and outside the U.S., accelerating time to drug availability by more than a year in one case.
Expanding access and accelerating discovery
Reducing drug R&D cost through digital health solutions also delivers several downstream benefits for trial sponsors, and more importantly, patients. Expanding the geographic scope of trials enables researchers to recruit patients who are historically under-represented and under-served by clinical trials, either based on where they live or social determinants of health that prevent them from traveling to clinical trial sites.
Trial access equity and inclusivity are important considerations for sponsors given the results of a 2021 analysis of U.S. study participants that found white individuals were overrepresented while Black or African American, American Indian or Alaska Native, Hispanic or Latino, and Asian individuals were underrepresented, with some studies completely omitting under-represented ethnic groups from cohorts.
Similarly, a 2019 study found rural residents had a five-year relative cancer survival that was 5.2% lower than metropolitan or urban residents and a 10% increase in risk of death after adjustment for multiple factors. Rural residents also tend to be older and sicker than their urban counterparts and have lower median incomes.
Access to more clinical trials, but with less of a travel burden could expand access to effective therapies and care to these under-represented populations while increasing therapeutic value, as well as helping trial sponsors adhere to new regulatory requirements to increase study participant diversity. While not a panacea, these technologies can be part of a comprehensive set of solutions that help close the gap of inequity in medicine and drug development.
Digital medicine edges forward
Another advantage of digital health solutions that is attracting pharmaceutical companies and VC investors is their potential to support — or even replace — a traditional drug. The earliest higher-profile digital therapeutic leaders focused on mental and behavioral health with some earning Food and Drug Administration approval for managing conditions such as attention-deficit and hyperactivity disorder, substance-use disorder, and insomnia using a prescription-level app alone or in conjunction with pharmacologic therapy. While this sector is undergoing its own set of challenges around reimbursement and values, culminating most recently in Pear Therapeutics’ Chapter 11 bankruptcy filing, there remains tremendous potential to develop scalable therapeutic solutions for many of these pernicious conditions.
Other digital health solutions are being developed to help improve drugs and/or help prescribers select the most appropriate, evidence-based therapy and dosage. Beyond answering questionnaires on a smartphone, these novel “companion apps” leverage the sensor, artificial intelligence and machine-learning capabilities within personal devices or wearable sensors to passively collect and analyze data.
For example, UCHealth, a health system in Colorado with 2.3 million patients, recently began offering a smartphone app made by HealthRhythms to its patients that passively measures behavior relevant to mental health and uses AI to assess changes and even predict a deterioration in a patient’s condition. The AI then initiates an intervention where patients can receive treatment through their phones. UCHealth providers are also notified of these potential changes and can intervene directly if warranted, driving the next level of tech-enabled personalized healthcare. [Editor’s Note: HealthRhythms is a portfolio company of GSR Ventures, a venture capital firm where the author is employed]
Others including Kintsugi Health are advancing novel biomarker technology, such as signals in voice and speech, to help identify patients at risk of anxiety and depression from calls made to health systems and insurers with the use of AI.
Measurable ROI and clinical validation is key
Expect the upward funding trend for pharmaceutical and life sciences digital health solutions to continue, but startups should not expect a rapid return to the spending spree witnessed during the peak of 2021. Investors are scrutinizing data behind company claims and demanding greater evidence of efficacy and benefit before funding a promising company.
That said, digital health is only going to have a greater impact and benefit on healthcare and patients in the coming years and decades. So while investment capital may not be as easy to come by as in previous years, companies with a truly transformative solution and that are poised to deliver double-digit ROI will certainly have many funding offers through their development and commercialization journey.
Photo: Danil Melekhin, Getty Images
Sunny Kumar is a Partner at GSR Ventures, where he focuses on investments in early-stage companies applying artificial intelligence and machine learning technologies to the healthcare sector. Sunny is a physician as well as a published medical researcher with a focus on applying informatics and artificial intelligence to translational medicine in the fields of neurosurgery and gene therapy. He is a serial entrepreneur and most recently founded a company to reduce readmissions for high-risk patients with chronic diseases using voice-enabled natural language processing technology. Sunny received a BS in Molecular Biology from Yale University, an MD from Stanford University School of Medicine, and an MBA from Stanford University Graduate School of Business.
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