What You Should Know:

• Quest Diagnostics has reached an agreement to acquire Haystack Oncology  an early-stage oncology company focused on minimal residual disease (MRD) testing to aid in the early, accurate detection of residual or recurring cancer and better inform therapy decisions
• Under the terms of the agreement, Quest will pay $300 million in cash at closing, net of cash acquired, and up to an additional $150 million on achieving future performance milestones.
• The acquisition will leverage Quest’s expertise and scale in oncology, genomics and pathology. Quest employs approximately 400 pathologists through its AmeriPath specialty pathology-diagnostics business and provides approximately 7,000 patient access points in the United States for blood and other specimen collection.

Adding Sensitive Liquid Biopsy Technology for Improving Personalized Cancer Care to Oncology Portfolio

MRD testing is a fast-growing category of liquid biopsy tests that identify circulating tumor DNA (ctDNA) in the bloodstream of patients following surgery and treatment for cancer. Founded in 2021, Haystack has developed a ctDNA-based technology specifically for MRD detection, based on 20 years of research and development by world-renowned luminaries from Johns Hopkins University, including Drs. Bert Vogelstein, Ken Kinzler and Nick Papadopoulos. In a prospective, multi-institution study published in the New England Journal of Medicine in June 2022, an earlier version of the Haystack technology demonstrated the ability to better identify patients with residual disease for adjuvant chemotherapy after surgery for stage II colon cancer, thereby reducing chemotherapy use in the overall patient population without compromising recurrence-free survival.

Following the close of the acquisition, Quest expects to adapt the MRD test developed at Haystack as the basis for new clinical lab services available beginning in 2024. Development efforts will focus initially on MRD tests for colorectal, breast and lung cancers.

“Combining Haystack with Quest is a major step forward in translating two decades of world-class liquid biopsy research and development into clinical laboratory services that are highly reliable and broadly accessible. Like looking for a needle in a haystack, accurately detecting MRD has been very challenging to date,” said Dan Edelstein, CEO and President, Haystack. “With Quest, we expect to increase and accelerate access to important tests that will improve the quality of cancer MRD detection and recurrence monitoring for patients. Working together, we have the potential to greatly transform the patient journey and save lives.” 

Collectively rare diseases are anything but rare – they impact 30 million people in the US and ten times that amount globally. And 1 in 3 children suffering from a rare disease will not survive beyond the age of five.

One of the biggest challenges facing clinicians is making a quick, accurate diagnosis – on average patients visit eight physicians and receive two to three misdiagnoses before being correctly diagnosed, a process that takes US patients around 7.6 years, and is often referred to as a diagnostic odyssey.

This can in part be explained by the sheer number of rare diseases – there are around 7,000 disorders, which collectively have 12,000 unique characteristics. The complexity surrounding diagnosis is compounded by the overlap of symptoms between diseases – for example, a patient may present with encephalopathy and seizures, which are features of 1,500 rare diseases. In such cases, physicians often turn to their own prior experience to inform their diagnosis, however, statistically, it is highly unlikely that the clinician would have come into contact with the patient’s particular rare disease in the past, or even heard of it. 

Shortening the Diagnostic Odyssey

For those patients presenting with severe disease – of whom 50% are children – shortening the diagnostic odyssey is a pressing challenge. For some sick babies, each minute lost before a diagnosis and precise treatment is started may increase the likelihood of permanent neurological damage or even death.

Diagnosis opens the door to potential interventions that could significantly improve health outcomes and quality of life, as well as reduce the length of stay in hospital and the cost of care. 

Going beyond whole genome sequencing

The ability to sequence the genome is the essential first step for rare disease diagnosis. DNA sequencing has undergone an astonishing revolution in the last decade, as demonstrated by the emergence of numerous consumer-focused genetic mapping tools such as Ancestry.com and 23andMe, as well as companies like Illumina which have pioneered an industrial-scale processing capability that enables a variety of rapid DNA sequencing techniques. 

The gold standard is Whole Genome Sequencing (WGS) – an incredibly powerful and thorough method that once took years to undertake but can now be performed relatively cheaply and in a matter of hours.

Most rare diseases have a genetic component and WGS is the way to detect the genetic abnormality associated with the disorder. But, it’s complicated. The same disease may have slightly different genetic variants in different patients, and a single person may be a carrier of genetic markers associated with multiple rare disorders, but actually only suffer from one. Interpreting this information, therefore, takes highly skilled geneticists, and even they still face a considerable challenge in making a diagnosis due to the potential breadth and ambiguity of the data.

The answer to this problem lies in overlying genomic information with the phenotype – the physical manifestation of the underlying disorder. It requires a painstaking comparison of an individual patient’s characteristics and clinical findings against the thousands of phenotypes associated with rare diseases.

This so-called “deep” phenotyping is laborious and highly technical, and is reliant on experienced physicians with the ability to match patient phenotype with known Human Phenotype Ontology (HPO) rare disease characteristics – all 12,000 of them. This is a manual process that takes hours to complete for each patient, even when undertaken by a few highly trained geneticists with relevant experience. In short, while huge strides have been made to scale and automate genetic analysis, the corresponding and necessary phenotype analysis is still manual and time-consuming and does not scale.

Harnessing the power of AI

This is where AI comes in. 

AI-led technologies are already improving diagnostic speed and accuracy by automating deep phenotyping to complement the broad genetic data generated from WGS. 

The technology is able to quickly analyze the lengthy, unstructured data held within a patient’s Electronic Medical Record, which comprises approximately 80 percent of the meaningful data which previously needed to be analyzed by manual reviewers. In a matter of seconds, AI is able to match patient phenotype data with potential phenotypes known to be associated with a specific rare disease. This in turn helps speed up the overall process of diagnosis from days or weeks to hours, an end-to-end process pioneered by Rady Children’s Institute of Genomic Medicine (RCIGM) and reported recently in the New England Journal of Medicine. 

The vital clinical narrative is unlocked with Clinical Natural Language Processing (CNLP), a highly specialized branch of AI that enables machines to understand human language and hundreds of thousands of detailed clinical concepts. By recognizing and analyzing the clinical and social data within this unstructured clinical narrative, CNLP-based technology can process lengthy, chronologically ordered content and make it computable at scale. This enables detailed patient information to be matched with the entire HPO library in seconds, which when coupled with rapid WGS and additional analysis helps to produce a diagnosis within hours of admission for a critically-ill newborn. 

In the case reported by RCIGM, typical of this kind of scenario, the child was born without any apparent problems but was brought back to the hospital when he was around 6 weeks old and extremely ill. Unbeknownst to his parents and the clinicians looking after him, he had an extremely rare genetic disease. Deteriorating by the hour, despite all attempts to support him, the RCIGM team used the automated AI-supported technique to establish the diagnosis for the child. 

In this particular case, the disease was treatable with vitamin supplements and when these were added to his feed, he recovered rapidly and was discharged a few days later. When reviewed in the clinic 6 months later he was a healthy and thriving baby. The authors noted that tragically his sibling, born 9 years earlier before these new technologies were available, had died at 18 months without a diagnosis – though the likelihood is that it was the same, treatable rare disease but impossible to diagnose without AI.  

AI tools thus empower physicians to make faster diagnoses, increasing patients’ chance of survival and paving the way to improved health outcomes. 

Looking ahead: improving population health

It’s not only critically ill babies and children that stand to benefit from AI-powered technology in the field of rare diseases. There are also significant numbers of undiagnosed – and therefore untreated – adults with milder forms of rare disease. 

In the future, it is likely that AI will be used to look for tell-tale symptoms in otherwise unremarkable medical records to find adults with a partial, and therefore less severe, expression of disease. They are likely to have suffered continual, unexplained health challenges – for example, regular fractures or bone breakages – which would have impacted their lives significantly, but are unlikely to have ever received a definitive diagnosis. By automating the deep phenotyping process, AI will be able to identify patients with combinations of characteristics that suggest rare diseases as the underlying cause, opening the door to medical interventions for those individuals with treatable disorders.

Revolutionizing the outlook for rare disease patients

Patients with rare diseases face a multitude of challenges – a lack of information, the scarcity of specialist physicians and the life-changing health impact of these diseases.

The good news is that considerable progress is happening – we understand more than ever how rare diseases work, and how they then manifest. Pharmaceutical companies are investing more in drug development, thanks in part to government incentives and tax breaks, and in particular the Orphan Drugs Act passed in the US in 1983. These factors have come together to improve treatment options for rare disease sufferers, a vulnerable group of patients who, until recently, it has been very difficult to help.

These new AI-based approaches are now able to help diagnosis at speed and at scale, giving patients access to new treatments as they emerge, and disease management plans. Not only does this improve the survival rate and quality of life for patients with rare diseases, but it also reduces the amount of healthcare they need, reducing the burden on over-stretched health systems. 

About Chris Tackaberry

Chris Tackaberry is the co-founder and CEO of Clinithink, a technology company built around CLiX, the world’s first Healthcare AI capable of truly understanding unstructured medical notes.

Chris is a qualified physician and MSc Computer Science graduate who spent nine years in clinical practice in anaesthesiology and intensive care before embarking on a career in healthcare IT. His combined expertise in medicine, computer science and leadership has been the foundation for his stewardship of Clinithink’s strategic direction and growth.

What You Should Know:

– COTA, Inc., an oncology real-world data and analytics company, today announced a new partnership with Genomic Testing Cooperative (GTC), a molecular testing company.

– GTC has a very innovative approach to genetic testing, providing molecular information which is critical to determining accurate diagnoses and determining the most appropriate treatment. GTC’s tissue and liquid-biopsy testing leverages DNA and RNA sequencing, which is very rare in the industry, so together with COTA’s RWD platform (which had some biomarker data), care teams and researchers will have access to the industry’s most comprehensive suite of actionable oncology data.

The sequencing and analysis of human DNA have advanced significantly since the initial draft of a human genome that was published as part of the Human Genome Project. With DNA sequencing becoming increasingly cost-effective, the market for genetic testing is growing at an accelerating rate – the market for Next Generation Sequencing (NGS) services has an estimated annual growth of 18.3% from 2022 to 2030. AI presents a range of possibilities for this rapidly growing field, and in this article, Dr. Ansgar Lange of Nostos Genomics explores the future of AI in genetic testing.

The Tortoise and the Hare: genetic tests and their interpretation

Genetic diseases are caused by mutations or variants in the human genome, and geneticists must locate the causative variant in order to diagnose these conditions. The first draft made of a human genome, as part of the Human Genome Project of 2003, cost $300 million. Shortly thereafter the cost of sequencing a human genome was estimated to be around $20-25 million. Fortunately, as the competitiveness of the market increased and technology became more widely available, this cost has decreased significantly since then, dropping to as low as $200. This cost reduction has led to rapid growth in the Next Generation Sequencing (NGS) market, making genetic testing much more accessible. 

Although sequencing itself is becoming cheaper, interpreting the data has not and is still a labor-intensive process as it is relying on the human expertise of so-called variant scientists. The more tests are being done and the more extensive these tests are, the more challenging the interpretation becomes due to the amount of data. Looking for relevant information in this data is like looking for a needle in a haystack, as many variants are benign or of uncertain significance (VUS), which means it is not known whether they are pathogenic or not. Finding relevant variants and interpreting their pathogenicity is done by a specialist, making interpretation a bottleneck that is labor- and cost-intensive.

Applications for AI in genetic testing

There are interesting AI applications addressing the bottleneck of data interpretation in genetic testing. One, for instance, is improving the accuracy and speed of genetic testing. AI algorithms can be used to automate many of the steps involved in genetic testing, like data analysis and interpretation of results. This can support variant scientists in improving the accuracy and speed of genetic testing, making it more accessible and affordable for patients and healthcare providers.

Another application can be found in identifying novel genetic mutations and variations that may be associated with rare diseases. AI algorithms can be trained to analyse large amounts of genetic data and identify patterns and variations that may be associated with rare diseases. This can help researchers and clinicians identify potential genetic causes of rare diseases and develop targeted treatments. This is particularly interesting for identifying variants of uncertain significance as, for instance, pathogenic – which is already being done.

Personalized medicine can also benefit from AI, where algorithms support the development of treatment plans based on a patient’s genetic profile. By analyzing a patient’s genetic data, AI algorithms can help clinicians develop personalized treatment plans that are tailored to the specific mutations and variations present in a patient’s genome. This can improve the effectiveness of treatments and help to reduce the risk of adverse side effects.

As AI is becoming increasingly more powerful, new and more sophisticated applications in the field of genetic testing are continuously developed. AI-driven approaches have the potential to significantly reduce the time it takes to identify and diagnose rare diseases while improving accuracy and reducing costs. This could have a huge impact on the lives of patients and their families, as well as on the healthcare system as a whole. It is an exciting field to keep an eye on – as the sky seems to be the limit.

About Dr. Ansgar Lange

Dr. Ansgar Lange – Nostos Genomics COO Dr Ansgar Lange is a commercial health-tech leader with a Ph.D. in health economics. Prior to joining Nostos Genomics in early 2021, he served as COO of a UK startup and helped it grow from 8 to 2000 employees and $100 million in revenue. At Nostos he oversees partnerships and drives business development.

What You Should Know:

– Tempus, the $10B artificial intelligence and precision medicine company, announced their first multi-omics collaboration with Actuate Therapeutics, in which datasets of different omic groups – genomics, transcriptomics, epigenomics, and others are combined during analysis to improve research and enable new discoveries, including ones that would have been missed with a single method alone.

– This multi-omics approach is being used by Actuate Therapeutics in support of their Phase 1/2 oncology study of elraglusib, a GSK-3β inhibitor, which includes a randomized study in patients with metastatic pancreatic cancer.

– The drug has shown clinical benefit for multiple advanced cancers. Tempus’ diagnostic technology and multimodal (i.e., DNA, RNA, and imaging) data will support the discovery and validation of novel targets and biomarker profiles that will help determine which patients may respond better to the drug – demonstrating a new way in which precision medicine can be incorporated in clinical development.

Today’s relationship between payers and providers is more fraught than ever. With a history of transactional, often adversarial, fee-for-service contract negotiations, it’s no wonder that the healthcare industry has grown too comfortable pitting payers and providers against each other.

The lack of trust and transparency between the two groups has led to a perceived misalignment of vision. Across the board, the administrative staff has shouldered the brunt of this friction, which in the end affects patient care and revenue growth negatively. A recent study reported that up to 28% of administrative waste could be eliminated each year if payers and providers worked together. 

Both payers and providers have already felt the pinch of clinical staff shortages, but the shared pain points don’t end there. A Kaufman Hall report says that 2022 was the most challenging financial year for U.S. hospitals and health systems since COVID-19, with increased operating costs and a lack of staff resources to treat an increased patient volume. Similarly, payers are under more scrutiny from the Centers for Medicare and Medicaid Services, as more strict audits of Medicare Advantage plans could result in payers repaying billions of dollars. 

Clearly, it’s time to stop framing the payer-provider dynamic as foes to be conquered, and instead, consider the importance and benefits of more collaboration – what could be possible with improved payer-provider relations, and what changes we should make as an industry to help us get there.

Shared Data Views to Bridge the Divide

One of the simplest ways that payers and providers can start bridging the divide is to implement shared data-driven patient practices. 

While the amount of healthcare data is growing exponentially, it tends to be in siloed and disparate places, presenting a significant barrier to usage. For example, payers and providers each use different data sets – payers tend to have historical data driven by claims over a long period of time, while providers tend to have more granular clinical and financial data that updates in real-time.

However, it is not enough to know that informational data silos exist. In a world where faxes still reign supreme and mere “EHR” access is granted through portals – due to lack of interoperability, HIPAA concerns, and more – we must tackle data silos with technology solutions that offer more intuitive, prescriptive, and truly shared data views. 

When payers know what data providers need and vice versa, they can provide each other with what’s necessary to accomplish mutually desired outcomes – a more empathetic approach to data-sharing, if you will, in an environment that each party can equally access, as opposed to proprietary systems. Shared data views, updated in real-time, can also help identify a single source of truth that can serve as the bedrock on which to build trust and eventually payer-provider alliances.

Accelerating Alignment through Advanced Technologies

Once payers and providers establish a foundation of data sharing to lay the groundwork for collaboration, they can implement more advanced technologies. AI or machine learning-driven tools that support the work of both payers and providers can be layered on to accelerate alignment. 

For example, such tools can lessen the burden of utilization management (UM) on administrative staff, a traditionally manual process, that in many ways has become counterintuitive to the very goals UM was designed to accomplish – to ensure appropriate and judicious use of healthcare resources. Specific, but not limited to, UM, payers and providers can leverage predictive analytics within shared, trusted data views to establish agreed-upon thresholds – what is likely to be agreed upon as inpatient versus observation – to automate decision-making. If up to 90% of all services are ultimately approved, we should be using the science of data to work smarter, not harder, to remove unnecessary tasks and administrative waste associated with these processes.

The Business Case is a Clarion Call for Better Tools, Processes

Building and maintaining successful payer-provider alliances are much more than AI technology augmenting criteria-based utilization management solutions, however. Given the current healthcare landscape, as mentioned above with staff and revenue challenges, there is also a clear business case for improvement – and “working together may be the only way forward,” as Kaufman Hall suggests. 

To eliminate the zero-sum game mentality between payers and providers, we must establish new ways for them to approach problems together. And luckily, the tide seems to be turning, with the appetite for improved payer-provider relationships as strong as the need – 92% of provider executives say they desire greater collaboration with payers. 

The healthcare industry must therefore increase awareness and adoption of tools to help deliver on this need, ushering in a new era for payers and providers, where they can be united in their efforts to reduce administrative waste while improving staff productivity and the bottom line, ultimately enhancing the member’s, or patient’s, experience as well. 

About Dr. Heather Bassett

Dr. Heather Bassett has over 20 years’ experience in healthcare and has served as Chief Medical Officer for XSOLISsince January 2013. She leads XSOLIS’ team of physicians and partnered with its data science team to pioneer the Care Level Score(CLS), which combines clinical expertise and data science for a numerical representation indicating the appropriate care status for each patient.

Dr. Bassett earned her Bachelor of Science in biological sciences from Carnegie Mellon University in Pittsburgh, Pennsylvania, and her Doctor of Medicine from the University of Texas Medical Branch in Galveston, Texas, where she worked as a research associate in the field of DNA repair. She undertook her residency in internal medicine at Vanderbilt University Medical Center in Nashville, Tennessee, and worked as a hospitalist at Centennial Medical Center in Nashville for eight years. She is board-certified in Internal Medicine.

The material cost of COVID-19 has been at the center of public discourse since the early days of the pandemic. In 2020, growth in federal government spending on healthcare increased 36 percent, compared to the 5.9 percent bump in 2019. While the distribution of vaccines has allowed for a version of pre-pandemic life to resume, hospitals are still not recovered from the high rates of hospitalizations that occurred in March 2020, and the indirect costs of the pandemic continue to loom over the American population as a result of strained health systems. 

During the early days, the cost of hospitalizing a patient seemed obvious: the sheer volume of long stays, expensive ventilators, a lack of one-size-fits-all treatment solutions, and the pause of elective surgeries. Now, Covid-19 continues to wreak havoc on our health systems, but in a more covert way. With only 4% of Americans fully boosted as we move into this winter’s ‘triple-demic’ – and long covid impacting the lives of as many as 16 million people on a daily basis – it’s clear that public health officials need to do more in order to support the American population and our struggling health systems. 

The Cost of Healthcare Provider Burnout 

Across the country, healthcare providers are reporting extreme rates of burnout. It is important to underscore that healthcare providers and hospital systems were stressed prior to Covid-19, but the pandemic has exacerbated it. Employment across healthcare is down 1.3 percent, or 223,000 jobs, from pre-pandemic levels. Over 90 percent of nurses said they are considering quitting their jobs by the end of 2022 in a survey, with 72 percent of nurses stating they had already experienced burnout before March 2020. In addition, the increased stress that doctors have experienced is resulting in worse patient care – with 28% of doctors who reported burnout sharing that the quality of care they are providing has significantly declined. 

We are amid a mass healthcare provider exodus, and, according to estimates, each instance of physician turnover costs healthcare organizations at least $500,000, and each instance of staff registered nurse (RN) turnover costs $46,100. Without proper staffing, hospitals are at risk of closure and patients’ health is at risk of worsening. 

The Cost of Hospital Closures 

Before the pandemic, hospitals closed for several reasons, including insufficient staffing, lack of funding, and/or having a large uninsured patient population. Since March 2020, 21 hospitals across the United States, predominantly in rural areas, have closed. Health systems are still recovering from the significant loss of revenue from canceled appointments – according to a report from The Chartis Center for Rural Health, 82 percent of the rural hospitals surveyed said suspension of outpatient services resulted in a loss of at least $5 million per month. 

So, what happens when hospitals and health systems close? 

Rural areas experience more Covid-19-related deaths than urban communities and public health experts attribute these deaths to the rampant hospital closures, as well as a general lack of healthcare providers. It is a vicious cycle: Covid-19 strains hospital systems, healthcare professionals leave, hospitals close, and more patients will die from infectious diseases like Covid-19, the flu or respiratory syncytial virus (RSV) – not to mention the other reverberating public health complications that come as a result of these closures. Vaccinations have helped these hospitals stabilize, but to keep up with covid fatigue and the ever-evolving variants we need a variety of treatments in our arsenal. 

More Covid-19 Treatments Will Bolster Struggling Health Systems  

Increasing the number of vaccinated individuals around the world, in addition to broadening access to effective non-vaccine treatments, such as antivirals and monoclonal antibody therapies, will significantly lessen the impact of the disease on individuals and lessen the burden on the healthcare system. Antiviral treatments have proven to reduce hospitalization, but diversity in treatments is essential to keep up with the ever-evolving Covid-19 variants. Dr. Andrew Pavia, chief of pediatric infectious diseases at the University of Utah Health, was quoted on the effectiveness of antivirals: “If there is anything we know about viruses and antiviral drugs is that eventually, we will see some sort of resistance.” For the time being, antivirals are effective – this is not a call to leverage one type of therapy over another – this is a call to help patients and our health systems survive by equipping healthcare professionals with as many treatments as possible. 

One such treatment that has proven highly effective when applied properly are neutralizing monoclonal antibody therapies. Like antivirals, monoclonal antibodies reduce hospitalization, the risk of death, and shorten the length of the infection – resulting in better patient outcomes and stronger health systems. 

According to Yale Medicine, it is estimated that about three percent of the United States population, or up to 25 million individuals, is considered moderately-to-severely immunocompromised, making them more at risk for serious illness if they contract Covid-19, or other viruses. Monoclonal antibodies are a highly safe and efficacious treatment, which is extremely important for this vulnerable population, especially as a complement to vaccines for prevention. An infusion can reduce the risk of hospitalization by 80 percent or more in a high-risk person, and unlike antivirals, monoclonal antibodies target specific parts of the virus spike protein leading to fewer side effects and interactions with other drugs. 

Collaboration between the government and the biotech industry will be essential for creating a portfolio of therapies to treat a variety of patient profiles who experience a range of Covid-19-related health issues. With our healthcare systems in such a precarious state, investing resources in the development of these treatments will prepare hospitals for future variants that threaten the health of our nation. The hope is that by bulking up our Covid-19 hospital response strategy, our already volatile health system will have a chance to recover, increase individuals’ access to quality healthcare, and ensure a healthier population. 

About Eugene Y. Chan, MD 

Dr. Chan is a physician-inventor. He is currently Chairman, Co-Founder of Abpro, CEO of rHEALTH, and President, CSO of DNA Medicine Institute, a medical innovation laboratory.  He has been honored as Esquire magazine’s Best and Brightest, one of MIT Technology Review’s Top 100 Innovators, and an XPRIZE winner. His work has contributed to the birth of next-generation sequencing, health monitoring in remote environments, and therapeutics. Dr. Chan holds over 60 patents and publications, with work funded by the NIH, NASA, and USAF.  Dr. Chan received an A.B. in Biochemical Sciences from Harvard College summa cum laude in 1996, received an M.D. from Harvard Medical School with honors in 2007, and trained in medicine at the Brigham and Women’s Hospital.  He is one of few individuals who has been in zero gravity. 

What You Should Know:

– In a downtrodden market climate, things don’t need to feel doom and gloom, according to Rock Health’s Annual 2022 digital health funding report. 2022 was a necessary reminder that investment is cyclical and that strong players build resilience in weathering funding climate changes.

– Analysts expect that 2023 will be built up on slow, steady, and maybe even boring strategies for healthcare startups and enterprises alike: managing cash, restructuring to accommodate revenue volatility, and investing in technology infrastructure.

Learning From A Turbulent Year – Trends and Insights Regarding Digital Health Funding in 2022

As the year 2022 draws to a close, many will remember it as being notorious for inflation, stock drops, 7 interest rate hikes that seemed to be shaping up into a possible recession. In this period of extreme economic uncertainty, the digital health sector suffered quite a bit, closing in on what is now widely believed to be the tail end of a macro funding cycle centered around the COVID-19-era investment boom.

Rock Health report key insights from the past year in the sphere of digital health funding are as follows:

– A Recap: 2022’s total funding among US-based digital health startups amounted to $15.3B across 572 deals, with an average deal size of $27M. Not only did 2022’s annual funding total come in at just over half of 2021’s $29.3B2, but it also just squeaked past 2020s $14.7B sum. Notably, 2022’s year’s Q4 $2.7B total was less than half of last year’s Q4 raise ($7.4B). Analysts will most likely look back on the last few quarters as a macro funding cycle, one that was governed by COVID. Between Q3 2019 and Q2 2021, investors continuously increased investments in digital health quarter-over-quarter for seven straight quarters, with one dip in Q2 2020. On the way down from the Q2 2021 peak to the present day, investors steadily decreased the flow of capital every quarter, excluding two quarterly upticks: one in Q4 2021 and a smaller notch in Q4 2022. Looking back, the influence of the COVID-19 pandemic can not be understated – COVID catalyzed digital health innovation, investment, and regulatory reform throughout 2020 and 2021. Intertwined with the public health emergency, government stimulus measures contributed to an artificially depressed cost of capital in 2020-2021, encouraging investors to make bigger and riskier bets in emerging areas like digital health.

2. Reluctance to Invest: A major factor that contributed to 2022’s downhill funding trajectory was the reluctance exhibited by investors to invest in late-stage deals. This led to a lack of mega-deals, especially relative to prior years. In 2022, 35 digital health startups raised rounds of $100M or more. While this may sound like a hefty cohort, it pales in comparison to the volume of mega-rounds raised in 2021 (88) and even 2020. Some of 2022’s “missing” mega deals stemmed from growth-stage digital health companies’ reluctance to raise in this market environment for fear of the dreaded down round. Additionally, startups that once expected to mega-raise their way into the unicorn club were faced with investors who were less willing to take flights of fancy on $1B valuations; as a result, they may have chosen to delay big raises. “A few months ago, it was detrimental for a digital health startup to say it was profitable—it implied the company wasn’t growing fast enough. Now, startups with strong financials and balanced valuations are attracting investor and acquirer interest.”

— Ulili Onovakpuri, Managing Partner, Kapor Capital

3. Valuation Risks: A shift was noticed two quarters ago in investors’ attention from growth-stage players to early-stage digital health companies being perceived as less likely to carry inflated valuations from 2020-2021. In a market where late-stage transaction volume has plummeted, it would be safe to anticipate that 2022’s cohort of larger Series A deals may experience above-average value attrition, risking down rounds at their Series B raises or later.

4. Health Systems and Innovation: In a year saturated with roadblocks, health systems struggled in particular. Excluding COVID-19 and behavioral care visits, patient encounters were 6.2% lower compared to early 2019, suggesting that some patients permanently forwent pandemic-delayed care. Staffing crises and wage inflation hiked up operating costs faster than CMS-influenced rate adjustments, squeezing health system margins rather than allowing hospitals to pass costs through to payers. As a cherry on top, burnout pushed record numbers of clinicians to retire or work fewer hours, which kept health systems in crisis mode…and paying crisis wages. With all these forces compounded, several hospitals across the U.S. recorded losses of over one billion dollars in 2022. Furthermore, health systems also took initiative to make a paradigm shift toward care models that lower operational burden. This facilitated the launch of ambitious hospital-at-home initiatives to free up hospital beds, allow the top-of-license practice, and reimagine care pathways. Additionally, the year also saw key health systems continue to expand and explore new business ventures that would diversify revenue streams in the upcoming years. Lastly, Health systems’ 2022 innovation “grace under pressure” is noteworthy and sets a precedent for other major healthcare companies facing less difficult, but nonetheless challenging situations.

5. The Role of BigTech in Reorienting Healthcare Initiatives: Due to volatile active user numbers and a largely declining profitability due to weak advertising revenue, Big Tech had to face deeply depressed stock prices whereas last year’s efforts were meant to diversify revenue streams saw Big Tech players building up businesses in data infrastructure, analytics, and finance. The key takeaway here is that the best healthcare entry points exist where teams already hold expertise (fertile ground remains in these familiar pastures). Rather than aiming to “disrupt” the entire healthcare system, the focus is best placed on applying practiced skill sets to top healthcare and research problems.

6. D2C Predictions: Analysts ended 2021 reflecting on the rise of digital health solutions selling direct-to-consumer, and predicted an upward trajectory of D2C in 2022. The year, however, did not go too well for D2C digital health players, with only 37% of the digital health companies that raised in 2022 selling directly to consumers, as opposed to 43% in 2021. “D2C businesses that have established strong consumer DNA and proven unit economics could be well-positioned to add more healthcare services under their brand umbrellas.” — David Kopp, Executive Chair, Oar Health

What You Should Know:

– C2i Genomics, a cancer intelligence company, today announced a strategic collaboration with AstraZeneca, a global life sciences and pharmaceutical leader. 

– The two companies have collaborated to evaluate the potential of whole-genome minimal residual disease (MRD) testing across solid cancers.

– Expanding on a completion of AstraZeneca’s accelerator BeyondBio SCALE program for start-ups and successful technology validation, C2i Genomics and AstraZeneca will work together on the integration and validation of the C2i Genomics platform at the AstraZeneca lab. with the goal of enhancing oncology treatment and supporting clinical trial recruitment and monitoring.

C2i Genomics Announce Successful Validation of Whole Genome-Based Residual Disease Monitoring Across Multiple Solid Cancers

 Founded in 2019, C2i Genomics has created the world’s leading cancer treatment intelligence platform that uses low-input blood and whole-genome sequencing to provide up to 100x more sensitive detection than competing liquid biopsy companies.

The industry is continuing to transform the way cancer is detected with the recent developments of cheaper, more accessible WGS technologies. With the convergence of reduced prices of whole-genome sequencing, the increase of capacity and throughput of global cloud infrastructure, and the combined technological developments in machine learning and signal processing, C2i Genomics is at the forefront of an inflection point that will profoundly change cancer treatment monitoring and clinical decisions.

What You Should Know:

– WellSpan Health and Helix, the nation’s leading population genomics and viral surveillance company, announced today a partnership to create a comprehensive population genomics program designed to improve patient healthcare outcomes by integrating genetic insights into clinical care and research.

– Patients who are interested can have a DNA sample collected to generate genomic data. Once obtained, with their consent, the results from their sample will be integrated into their electronic medical record (EMR), providing them and their physicians valuable insights into their personal health. The genetic reports made available by this program may allow patients and their health providers to develop precision health care plans to proactively mitigate serious health risk conditions and take a more preventative and individualized approach to their care.

– Additionally, the genomic data, which removes any information that may directly identify an individual, from consenting participants may help WellSpan better understand the health of its overall population and assist researchers to learn the root causes of certain diseases and the most effective treatments for them.

What You Should Know:

– Exai Bio and researchers at UCSF released data demonstrating that Exai’s novel, RNA-based liquid biopsy platform accurately detected breast cancer at the earliest stages and smallest tumor sizes.

– Earlier detection of breast cancer is crucial for optimal patient outcomes but cannot always be achieved based on symptoms or mammography.

Non-Invasive Blood-Based Platform Delivers Promising Data on Detecting Breast Cancer At It’s Earliest Stages

Exai Bio is a next-generation liquid biopsy company. Its mission is to enable a world where cancer can be detected early, diagnosed accurately, treated in a personalized and targeted way, and ultimately cured. The company’s proprietary RNA and artificial intelligence-based liquid biopsy technology delivers clinical insights into cancer biology to enable the earliest, most accurate diagnosis of cancer.

Exai’s technology uses RNA sequencing to identify a novel category of cancer-associated, small non-coding RNAs, termed orphan non-coding RNAs (oncRNAs). In a poster entitled, “Early-stage breast cancer detection using orphan noncoding RNAs”, presented at the 2022 San Antonio Breast Cancer Symposium, Exai demonstrated that oncRNA biomarkers in blood, combined with deep machine learning, detected breast cancer with high accuracy overall, including across all cancer stages and tumor sizes. The poster further demonstrates that even at the earliest stages and smallest tumors, sensitivity was greater than 80%. These findings suggest that Exai’s liquid biopsy test for earlier detection of cancer could meaningfully improve care and outcomes for cancer patients.

With this study, we again demonstrate that oncRNAs can be used as a biomarker for earlier cancer detection from a blood draw. oncRNAs are secreted from cancer cells and are abundant in the blood of cancer patients. Exai has created a catalog of hundreds of thousands of oncRNAs found in all major cancer types. This vast catalog gives the Exai platform several scientific and practical advantages over tests that rely on circulating tumor DNA.

These 2022 SABCS results also complement and build on the breast cancer data presented at SABCS 2021 where changes in oncRNAs reflected breast cancer treatment response, predicted overall survival and added significant information to other clinical endpoints such as tumor tissue pathology.

“Our results presented at SABCS 2022 represent another important step in establishing the role of oncRNAs in addressing the unmet need of detecting cancer at its earliest stages from a simple blood sample,” said Patrick Arensdorf, Chief Executive Officer of Exai. “The oncRNA-based liquid biopsy technology will be compatible with standard sample requirements enabling easy integration into conventional clinical workflows. Exai’s goal is to improve patient care with a variety of liquid biopsy tests for early cancer detection and monitoring of residual disease and recurrence in multiple types of cancer.”

Repetitive behavioral disorders such as obsessive-compulsive disorder (OCD), Tic Disorder and Tourette Syndrome have been challenging to treat because they involve considerable complexity. For example, the symptoms of one disorder can vary among individuals as does the coexistence or non-existence of other behavior disorders such as anxiety and depression. Further, the treatment of OCD, Tic Disorder and Tourette Syndrome varies depending on the disorders present in an individual patient, how long the disorder’s traits have been present, how individual patients respond to treatment dosages and the efficacy of treatment.

Historically and even modernly, medical professionals have found themselves faced with an array of potential treatments that may or may not work alone or in combination with other drugs. Compounding the frustration among healthcare providers is the poor level of R&D investments governments are making which stalls progress. Rather than inventing a new drug that would take years to hit the market, it’s possible to use artificial intelligence (AI), and specifically deep learning, to discover how existing drugs with regulatory approval can be repurposed for other applications.

One such example is clemastine, an antihistamine, which has proven to prevent and reduce the occurrence of repetitive behaviors.

Repetitive disorders have been difficult to treat

OCD is a disorder in which unwanted thoughts and behaviors are repeated. The compulsive behaviors mainly appear in the form of cleaning, confirmation, delay, ordering and other repetitive behaviors. Typically, serotonin uptake inhibitors such as clomipramine, fluoxetine, and fluvoxamine are used to treat OCD, but the side effects may include anxiety, diarrhea, insomnia, vomiting and weight gain. OCD-related disorders include, but are not limited to, storage disorders, hair pulling disorders and skin-picking disorders, for example.

Tic disorders include chronic motor or vocal tics, provisional tic disorders and Tourette Syndrome.  They are characterized by vocal tics or sudden rapid, repetitive, rhythmic or sterotyped movements that persist for more than 1 year, while Public Tic Disorder is characterized by the presence of one or more motor or vocal tics that are present for less than 1 year.

Tourette Syndrome is a neurological abnormality that repeats unconscious and uncontrolled sounds or actions and is characterized by multiple motor and vocal tics for more than one year. Tics are uncontrolled and appear in a wide variety of forms and have repetitive characteristics. In this case, dopamine receptor antagonists such as haloperidol, fluphenazine and pimozide are used for treatment, but the side effects can include cognitive decline, discomfort, and extrapyramidal symptoms.

Practitioners often find themselves frustrated because they are unable to achieve a satisfactory therapeutic effect using individual drugs or even a combination of drugs that are available today. In addition, some of those drugs are restricted due to their side effects. Quite often, doctors find themselves in continuous trial-and-error mode, trying this treatment, that treatment, or a combination of treatments, or adjusting drug dosages to reduce a patient’s unwanted repetitive behavior.

Recently, many gene mutations involved in the generation and function of nerve cell synapses have been discovered in patients with neuropsychiatric diseases and synaptopathy. These gene mutations are being recognized as one of the key mechanisms of neuropsychiatric diseases.

Clemastine, an antihistamine also referred to as meclastine, is used to treat allergic rhinitis, sneezing, dermatitis and itching. However, its therapeutic effect on repetitive behavior disorders has not been reported previously. Using artificial intelligence (AI), and specifically deep learning, it is possible to discover that clemastine effectively reduces repetitive behavior patterns in mice. In humans, it could prove to be the missing piece necessary to prevent or reduce OCD, Tic Disorder and Tourette Syndrome.

Why clemastine holds promise as an active ingredient

A pharmaceutical composition comprising clemastine or a pharmaceutically acceptable salt thereof can be used as an active ingredient for the prevention or treatment of repetitive behavioral disorders.

Clemastine is a first-generation antihistamine of the amino alkyl ether class that binds to the histamine H1 receptor and blocks the action of endogenous histamine. It has been approved by the United States Food and Drug Administration (FDA) and is currently a generic drug (e.g., tabegil).

Clemastine is a pharmaceutically acceptable salt that includes inorganic and organic acids and bases that are acceptable physiologically. Specifically, AI has identified that the pharmaceutically acceptable clemastine sale is clemastine fumarate. The pharmaceutical composition is formulated in the form of aerosols, capsules, emulsions, external preparations, granules, sterile injection solutions, suppositories, suspensions, syrups and tablets. Clemastine or other pharmaceutically acceptable salts can also be used in food including beverages, gum, health supplements, tea and vitamin complexes.

The pharmaceutically effective clemastine dosage is preferably 0.1mg/day to 5 mg/day, with the latter administered once to several times per day by dividing the dose. How much an individual patient requires depends on the person’s administration route, age, concurrent drugs, condition, severity of symptoms and sex. The clemastine or a pharmaceutically acceptable salt thereof and one or more drugs, can be administered simultaneously, sequentially, or in reverse order, such as serotonin reuptake inhibitors for OCD and dopamine receptor antagonists for Tourette Syndrome, for example.

Lab experiments with mice have already proven that the that an SH3 and multiple ankyrin repeat domains (SHANK3) scaffolding protein deficiency is a factor that induces repetitive behavior and that clemastine alleviates the repetitive behavior increase caused by SHANK3 deficiency.  It is our hope that AI-based discovery equates to a step-change in treatment that is beneficial to patients and their prescribing doctors.

Why AI-based drug repurposing is wise

Drug discovery is a long, drawn-out process because traditional research takes considerable time and so does regulatory approval. In the meantime, patients suffering from a disorder or malady may be suffering unnecessarily. Drug repurposing is a faster alternative. However, the chemical details of the drug, its potential interactions with other drugs and side effects must be considered when navigating the universe of possibilities. AI can do all that at scale.

For drug repurposing, AI analyzes the original purpose and chemical composition of a drug as well as a universe of diseases and/or disorders to find correlations and perhaps even causation. Deep learning helps identify the “unknown unknowns” such as clemastine can be used to prevent or treat OCD and other repetitive behavior disorders.

Bottom Line

AI is a powerful tool that can be used for patentable drug discovery and repurposing. Given the scale and speed at which AI can operate, it has the potential to advance the state of the art of drug discovery and repurposing at a much faster pace than has been possible using traditional tools and humans. Moreover, this improved efficiency has the potential to shrink drug discovery and repurposing time frames required to treat patients in new and improved ways.

About Jin Han Kim
Jin Han Kim is the Co-Founder, Chairman, and CEO of Standigm, a workflow AI-driven drug discovery company headquartered in Seoul, South Korea and subsidiaries in Cambridge, U.K. Standigm has proprietary AI platforms encompassing novel target identification to compound design, to generate commercially valuable drug pipelines.. Kim is an expert in developing AI platforms to identify new drug candidates and has led the company since its inception in May 2015.

Before founding Standigm, Kim worked as a Senior Research Scientist at the Samsung Advanced Institute of Technology, where he developed an AI algorithm for DNA damage and recovery mechanisms. He previously worked as a software developer for NCSOFT and for Namo Interactive. He also served as the Director of Drug Informatics at the Korean Society of Medical Informatics from January 2017-January 2020. Kim earned his Ph.D. in Artificial Intelligence at the University of Edinburgh, his M.S. in Artificial Intelligence at Seoul National University, and his bachelor’s degree in Applied Biology and Chemistry from Seoul National University. Kim speaks Korean and English.

The early 2020s will be studied by historians as a time of global uncertainty when an unknown pathogen caused a public health emergency that brought the world to the brink.

It may also be remembered as a time of unparalleled cooperation and advancement in technologies, prompted by the Covid pandemic, that provided enduring benefits for generations to come.

Just as the two world wars of the 20^th Century were the deadliest and most attritional in history, they also triggered developments in medicine, jet propulsion and cryptology that ultimately led to the general prescribing of penicillin, mass air transit and the dawn of the computer age.

The quickest and most obvious legacy of Covid was mass vaccination programs around the world which has already led to a step change in public perceptions of diagnostics and population-wide inoculation.

The profile it gave to the industry has since led to greater investment in methods and devices for detecting a wide range of conditions, most notably for sexually transmitted infections.

In addition, we can expect established, over-the-counter tests for things like fertility and pregnancy to become more informative. Diagnosing serious illnesses, including cancers and heart disease, is likely to become simpler and quicker, because of advances in diagnostic technology created by interest in the sector generated by Covid.

Some people are now wearing wristwatches that tell them their blood pressure, average altitude, and their heart rate and the routine of carrying a test and being tested has become deeply ingrained in the public consciousness. 

Are we getting to the stage where people will regularly be testing themselves for cholesterol, blood pressure and heart rate? 

In the 1960s the medical profession promised there would be a pill for every ill. No matter what you got, they would be able to cure it. They quickly realized however that just because you could test patients for something didn’t mean they could do something about it. Far better not to have it in the first place. 

Also, by improving testing and diagnoses, we need to ensure that we are not widening health inequalities. Those who push for better and earlier treatment tend to be educated, middle-class people with a bit of money who are used to dealing with systems and being heard. There’s a whole other class of poorer, particularly older people, who are less likely to push and more likely to accept what they are told.       

So, what other than advances in diagnostic technology, has the experience of Covid given us? Here are just a few examples.

 1. Artificial Intelligence 

AI has changed the way disease outbreaks are monitored and managed, saving lives. During the pandemic, applications included tracking people with novel strains by detecting visual signs of the virus on computerized tomography (CT) lung scans and monitoring changes in body temperature through the use of wearable sensors.

AI has also been applied to open-source data to track the spread of the disease allowing public health planners to predict potential new case numbers by area as well as identify most at-risk populations.

Other applications include delivering medical supplies by drone, disinfecting patient rooms, and scanning approved drug databases for medicines that might work against the virus. 

2. Blockchain

Blockchain technology – normally associated with the production of cryptocurrencies – emerged as a key technology to help decision-makers produce fast, robust, transparent, and inexpensive solutions during an unprecedented public health emergency.

As well as helping to track the spread of the disease, it was also used to manage insurance payments and maintain medical supply chains and donation tracking pathways. 

Blockchain technology was particularly useful in monitoring outbreaks by creating ledgers that were both secure and could be updated hundreds of times per day. It also improved diagnostic accuracy and treatment effectiveness, streamlined isolation of outbreak clusters, tracked drug supply chains and supplies, managed clinical data, and identified patterns of symptoms.

3. Telehealth technologies

In the face of extraordinary restrictions on population movement and contact, new and more creative uses of existing telehealth technologies were required to permit clinicians to continue treating patients while complying with contact and travel rules and stay-at-home orders.    

Because of the high virulence of the disease, especially within hospitals, telehealth technologies became a cost-effective means of slowing transmission rates, reducing pressures on hospital capacity by filtering out those with moderate symptoms and keeping them at home.

Telehealth technologies permitted physicians to continue consulting by using audio-visual, real-time, two-way interactive communications including video ‘visits’ through webcam-enabled computers, tablets, and smartphones, chatbots and automated algorithms. 

Remote delivery of clinical care services continued through audio-visual conferencing technology that allowed hospitals to be kept clear of confirmed cases.

4. 3D Printing

Travel and contact restrictions coupled with a need for new and previously little-used medical hardware – including ventilator valves, breathing filters, test kits and face mask clasps – to help treat Covid-19 also posed a novel, logistical problem.

The use of 3D printing as a disruptive technology came into its own, keeping costs down and saving lives.

It allowed hospitals and public health authorities to use computer-aided design (CAD) and locally sourced materials to produce often small numbers of critical products. One area in which 3D printing was crucial was in the development of entirely new products, including plastic door handle adaptors that enable easy elbow opening to prevent the further spread of the virus.

5. Gene-editing technologies

From public health officials reporting the Covid outbreak to the World Health Organization (WHO), it took scientists only a fortnight to isolate the virus and figure out the full sequence of its genetic material. 

The disclosure of the genetic code went a long way to pinpointing the origins and the spread of the disease, and also to pharmaceutical targets for drug development. 

Advancements in gene-editing technologies – in particular of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas9 (CRISPR-associated protein 9) – was instrumental in developing a vaccine.

6. Nanotechnology
Νano-based products were developed and deployed to assist in the containment,
diagnosis and treatment of Covid-19. Nanotechnology is a multi-disciplinary field that utilizes nano-sized particles and devices for different applications, including diagnostics, targeted drug delivery and the production of therapeutic materials. 

Nanoparticles of gold and silver have been used in biomedical and diagnostic applications, for the detection of viral particles. Nanotechnology has been shown to help treat viral infections through various mechanisms. Nanoparticles can act as antiviral drug delivery systems, interacting and binding to a virus, thereby preventing it from attaching and entering a host cell.

7. Synthetic biology

Covid presented an ideal, real-world test case for scientists to use biology, engineering, genetics, chemistry, and computer science to substantially alter the genotype of the virus.  In the context of the pandemic, synthetic biology is seen as the next phase in the progress of vaccination development. Because it is being utilized as a design tool, it is helping to make vaccines more effective than ever.

The Bill and Melinda Gates Foundation and the National Institutes of Health invested in synthetic biology to help engineer vaccines that would be scalable to a level of billions as well as being able to work without refrigeration.

The synthetic biology body Ginkgo Bioworks gifted $25m of resources to public and private teams to help cure, prevent and treat novel coronaviruses. In addition, several companies worked to develop experimental vaccines containing synthetic strands of RNA or DNA that code for protein molecules on the surface of the virus. 

8. Drones
Throughout the pandemic, drones have been deployed on the front line to help contain the spread of Covid.

As well as being used for purposes of disinfection, street patrols and food and medicine delivery in quarantined districts, the Chinese government adopted and co-opted industrial drones to help improve disease detection and crowd management.

Devices were used to monitor quarantine measures, facilitate aerial broadcasting, conduct aerial thermal sensing, monitor traffic, and deliver medical supplies in infected areas, often replacing helicopter patrols for law enforcement and transportation.

9. Robots

Robots were also used to help contain the spread of Covid, including disinfecting hospitals, decontaminating public and private spaces and handling biohazardous waste as well as delivering food and medication.

Robots continue to be used for a range of clinical functions, including taking patients’ temperatures and substituting as medical assistants to help minimize person-to-person transmission.

Self-navigating, ultraviolet, disinfection autonomous robots were deployed to decontaminate hospitals, isolation wards, intensive care units and operating rooms by spreading UV light to destroy pathogens. 

In China, robots were adapted to provide security, inspection, and delivery services. In Hong Kong and South Korea, the Israeli Temi robot was used in nursing homes to allow families to communicate with quarantined residents through video calls, as well as being utilized in hospitals, airports, and offices.

About Ivor Campbell
Ivor Campbell is the CEO of Snedden Campbell, a UK-based recruitment agency for the global medical technology industry. IvorIvor has been in candidate search for more than 30 years. Prior to launching Snedden Campbell, in 2001, he held senior roles for some of the UK’s biggest recruitment companies. Fed up with men in grey suits, pointless KPIs and sharp practice, he decided to launch a new kind of retained medical technology search consultancy that would bring approachability to headhunting, where clients and candidates would be treated equally, and where nobody ever said ‘touching base’. He now spends his time meeting clients and delivering on projects around the UK, Europe and worldwide.

DispatchHealth, a provider of in-home medical care raises $330M led by Optum Ventures with support from current investors such as Humana (NYSE: HUM), Oak HC/FT, Echo Health Ventures and Questa Capital. New investors included Adams Street Partners, the Olayan Group, Silicon Valley Bank, Pegasus Tech Ventures and Blue Shield of California. Patients and their care partners can request DispatchHealth medical care via phone, mobile app, or website, and a medical team arrives within two hours equipped with tools and equipment needed to perform high-acuity medical care.

Haystack Oncology Launches with $56M for Post-Op Cancer Detection Tech

Haystack Oncology (“Haystack”), an oncology company that applies the next generation of circulating tumor DNA (ctDNA) detection technology raises $56M in Series A financing led by Catalio Capital Management (“Catalio”), which co-founded Haystack through its private equity and structured equity investment vehicles. Additional investors include Bruker, Exact Ventures, the venture arm of Exact Sciences and Alexandria Venture Investments. The funding will be used for the continued development and planned 2023 commercialization of its best-in-class personalized cancer diagnostic test that can detect as few as one mutant molecule in a million DNA molecules, positioning it as the most sensitive ctDNA-based MRD test for use in solid tumors.

DexCare Announces 50-state Project with Kaiser Permanente

Providence spin-out, DexCare, announced an expanded partnership with Kaiser that’ll make health system care accessible in all 50 states, including those where Kaiser doesn’t have a physical location. DexCare will now handle all of Kaiser’s clinic bookings, virtual care scheduling, phone care and health system load-balancing. The partnership is a case study in creating health system sustainability through digital modernization, which is pivotal during a time where the volatile market, low margins and external competition are forcing health systems to double down on growth and innovation to survive. Despite the current financial climate, DexCare CEO Derek Streat has seen an accelerated interest in their platform – proving there is appetite from health systems to invest in sustainable, scalable solutions. 

Babylon to Provide Fitbits for Eligible Members

Babylon Health will offer Fitbit devices and services to a subset of members that doesn’t currently have access to wearables and that fit health program criteria to promote proactive management of care and improve accessibility through its digital-first offering. Eligible members in select markets will be able to use Fitbit’s health and wellness features to track their activity levels, sleep patterns and more, and can sync this data with Babylon’s app where it will be available to them and their care team.

Uber Health Expands into Employer Market

Uber Health announced its plans to expand its healthcare offerings into the employer market.

Edifecs Partners with Empowered-Home to Deliver Automated Prior Authorizations

Edifecs and Empowered-Home announced a partnership to provide automated prior authorizations to medical associations, Accountable Care Organizations (ACOs), Independent Physician Associations (IPAs), medical groups, and home healthcare agencies. The Edifecs prior authorization solution combined with the clinical decision support system of patient management software company, Privis Health, forms the backbone of Empowered-Home’s ecosystem.

MEDITECH, SeamlessMD Collaborate on Digital Health Integration

MEDITECH announced that its Expanse customers in Canada can now integrate directly with digital care journey platform SeamlessMD. The collaboration will enable providers to monitor and engage their patients before, during, and after hospitalization using digital, evidence-informed pre-and post-care plans – such as for surgery, cancer, maternity, mental health, and chronic care.

Evangelical Community Hospital Switches from Allscripts to Epic

Evangelical Community Hospital switches from Allscripts to Epic’s enterprise EHR. The Hospital will go-live on Epic on December 4, 2022. This strategic move by the Hospital modernizes the patient process creating a seamless, safe, and more consistent healthcare delivery system for all patients in the community.

Cipher Skin Launches Pilot Program for Tech-Enabled Physical Therapy Rehab

Cipher Skin and Parker Health launches a new pilot program to help bring tech-enabled physical therapy to Medicare and Medicaid patients. With plans to pilot the program in Austin, San Francisco, Los Angeles, and Kansas City, the partnership will bring Cipher Skin’s wearable motion and biometric-tracking technology to select orthopedic clinics that use Parker Health’s platform. This collaboration will help accelerate physical rehabilitation by improving patient engagement and care plan completion. 

Vivalink Integrates with Garmin, Other Wearables to Address RPM Interoperability

Vivalink is addressing these RPM interoperability challenges by announcing today that leading wearables and medical-grade devices are integrating with the company’s Biometrics Data Platform. Now, leading pulse oximeters, blood glucose monitors and sleep monitors by companies like Garmin and Roche are available alongside the Platform to accelerate development and deployment of novel healthcare applications and research.

Validic Raises $12M for Healthcare IoT Platform 

Validic, a healthcare IoT platform raises $12M in funding led by Kaiser Permanente Ventures. The investment will further Validic’s mission of improving the quality of life by making personal health data actionable and accelerate the full integration of personal health device data into the electronic health record.

ResMed Launches Sleep Platform, Primasun

ResMed and Verily, an Alphabet precision health company launches Primasun, an end-to-end, clinically-supported solution for addressing complex sleep disorders, The clinical sleep care solution aims to reduce untreated sleep disorders’ impact on chronic disease and people’s lives. Through its preventive care model, Primasun works with employers and healthcare providers to identify populations at risk and connects patients to certified sleep physicians who guide them from diagnosis to treatment in a matter of weeks.

Ariadne Labs Announces Clinton Global Initiative Commitment

Ariadne Labs, a joint center for health systems innovation at Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health launches a Clinton Global Initiative (CGI) Commitment to Action called “Trusted, Equitable, Open Access Humanitarian Health Education.” Ariadne Labs is collaborating with UNHCR, the UN Refugee Agency, International Medical Corps, and the Harvard Humanitarian Initiative. The Clinton Global Initiative (CGI) convenes global and emerging leaders to create and implement solutions to the world’s most pressing challenges.

Suki Releases Mini-Doc on Physician Burnout Challenges and Solutions

Suki, a voice artificial intelligence (AI) technology company for healthcare, announced the release of a mini-documentary that features the real-life challenge of a family physician facing burnout and how a voice assistant helped alleviate the negative impact of administrative burden. “From Burnout to Balance” is an intimate view into Dr. Elizabeth Goff’s struggles with work-life balance and how the use of a voice assistant provided the margin needed to keep her in practice full-time.

OpenLoop Health Partners with BlueJeans by Verizon to Expand Access to Quality, Reliable Virtual Visits

OpenLoop Health has signed a teaming agreement with BlueJeans to provide its clients access to BlueJeans Telehealth, an intuitive, HIPAA-ready virtual care platform designed to help drive better patient interactions from beginning to end.  The partnership will also give BlueJeans customers access to unrivaled provider staffing services through OpenLoop’s NCQA-certified network of clinicians in all 50 states, with payer coverage across 250 million patient lives.

What You Should Know:  

– Haystack Oncology (“Haystack”), an oncology company that applies the next generation of circulating tumor DNA (ctDNA) detection technology raises $56M in Series A financing led by Catalio Capital Management (“Catalio”), which co-founded Haystack through its private equity and structured equity investment vehicles. Additional investors include Bruker, Exact Ventures, the venture arm of Exact Sciences and Alexandria Venture Investments.

– The funding will be used for the continued development and planned 2023 commercialization of its best-in-class personalized cancer diagnostic test that can detect as few as one mutant molecule in a million DNA molecules, positioning it as the most sensitive ctDNA-based MRD test for use in solid tumors.

Transformative Precision Oncology

Haystack was co-founded in 2021 by Drs. Bert Vogelstein, Ken Kinzler and Nick Papadopoulos, and Mr. Joshua Cohen of Johns Hopkins University, alongside CEO Dan Edelstein and CTO Dr. Frank Holtrup. Drs. Vogelstein, Kinzler and Papadopoulos head the Ludwig Center at the Johns Hopkins Kimmel Cancer Center, where they are developing novel methods for early cancer detection. Previously, Drs. Vogelstein and Kinzler were scientific co-founders of Exact Sciences, and later Drs. Vogelstein, Kinzler and Papadopoulos co-founded Thrive Earlier Detection Corp., which sold to Exact Sciences in January 2021. Mr. Edelstein and Dr. Holtrup have both held C-level roles in other liquid-biopsy-based diagnostics companies, including Inostics, a liquid biopsy testing company also co-founded by Drs. Vogelstein and Kinzler.

Haystack leverages over two decades of pioneering research in liquid biopsy technologies to detect with high sensitivity and specificity the presence of any traces of MRD – small numbers of residual tumor DNA molecules left in the body following initial treatment. These ctDNA molecules are a marker of the presence of cancer and indicate that the disease will recur. Haystack’s testing is designed to help inform clinical interventions by creating personalized diagnostic panels to customize optimal treatment plans for each patient, independent of a tumor’s origin.

Research/Outcomes

A version of Haystack’s technology was utilized in the landmark DYNAMIC clinical study of stage II colon cancer patients post-surgery. Results from the study were reported earlier this year at the American Society of Clinical Oncology (ASCO) annual meeting and published in the New England Journal of Medicine1, demonstrating that applying Haystack’s ctDNA-guided approach to the treatment of stage II colon cancer significantly reduced the use of adjuvant chemotherapy without compromising recurrence risk or survival at two years.

Expansion Plans

The company plans to use the proceeds to expand accessibility to its groundbreaking ctDNA-based MRD testing platform, Haystack Duo™, a low-error rate, next-generation chemistry that enables ultrasensitive and personalized MRD testing. Haystack’s tumor-informed liquid-biopsy-based test begins with tissue-based whole-exome sequencing to identify patient-specific tumor mutations. A personalized MRD test is then developed to detect ctDNA from residual, recurrent or resistant disease.