What you need to know: 

• Animal health is seeing rising demand and early-stage startups are building novel products targeting the space, including AI-based solutions.
• Focus areas for emerging trends include: Diagnostic platforms for vets, advanced therapies, methane-reducing solutions, AI-driven diagnostics & monitoring, and disease prevention & treatment.

Animal health — which includes companion and livestock animals — is steadily growing as a topic of interest among executives.

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Essential resources to understand the future of healthcare:

• • The generative AI in healthcare market map — These tech companies are bringing generative AI into medical research and clinical settings.
  • Pharma AI Readiness Index: Who’s best-positioned for the AI boom? — Assess how prepared top pharmaceutical companies are to adopt and respond to rapidly evolving AI technologies.
  • 6 digital health markets gaining momentum in 2024 — We analyzed early-stage investment trends to uncover which digital health markets — from telepsychiatry to virtual & hybrid women’s healthcare — are quickly evolving and how.
• 
  • The Digital Health 50 — Here are the world’s most promising digital health startups.
  • Big Tech in Healthcare — How Amazon, Google, Microsoft, & Nvidia are looking to transform drug R&D, primary care, and more.
  • State of Digital Health Q2’24 Report — Funding in digital health drops, but larger check sizes and an uptick in exits highlight bright spots for the industry in Q2’24.
• 
  • Longevity tech market map — 64 promising startups across 12 categories aiming to expand lifespans, from human cryopreservation to cellular reprogramming.
  • Digital Health AI M&A — Every second acquisition in 2024 has been an AI company; here’s where we’re seeing the most activity.
  • 20 tech trends to watch closely in 2024 — The technology trends that will transform industries as generative AI takes center stage, including several directly impacting healthcare.

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In 2024 so far, a16z has backed more than 20 AI startups working within disruptive categories. For example, this year, it has invested in several AI-driven copilots and agents designed to automate key workflows in big industries like healthcare and finance. It has also turned its attention to multimedia generation startups expediting the creation of a wide variety of content, from images to videos to audio.

While championing AI’s advancement, the firm also acknowledges associated risks — its founders are proponents of open-source models, arguing that their transparency and accessibility will help ensure that AI is developed in a secure and ethical way. So far this year, the two largest a16z-backed AI deals have gone to open-source large language model (LLM) developers xAI and Mistral AI.

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Amid the decline, investors have shifted their focus to writing fewer, larger checks for more mature companies in the digital health ecosystem. Meanwhile, their interest in early-stage companies has cooled.

Based on our deep dive in the full report, here is the TL;DR on the state of digital health:

• Global digital health funding declines by 26% QoQ, with funding falling to $2.9B across 235 deals in Q2’24 — the lowest quarterly deal volume seen since 2014. However, the annual average deal size globally is $16.7M in 2024 YTD, up 40% from the average for full-year 2023, signaling that investors are writing fewer but larger checks.

• US deal share grows to 61%, up from 54% in Q1’24. While digital health funding in the US declined by 18% QoQ in Q2’24, the US’ proportion of the global deal volume grew, marked by an increase in mid- to late-stage deal share. Median deal size is also up in the US in 2024 so far — sitting at $7.5M vs. $4.6M in full-year 2023.

• Mid-stage deal share jumps to 26% in 2024 YTD, while early-stage deal share falls by 14 percentage points. Early-stage deals have consistently accounted for 60%+ of all digital health deals in recent years. However, in 2024 YTD, early-stage deal share has dropped to 51% as mid- and late-stage deals have captured more investor interest. In the US, early-stage deal share has fallen to 45% in 2024 YTD vs. 62% in full-year 2023.

• $100M+ mega-rounds drop off in Q2’24 but are more varied across the digital health landscape. Digital health mega-rounds dropped from 8 in Q1’24 to 5 in Q2’24. While mega-rounds were focused on biotech in Q1’24, they were more spread out in Q2’24, spanning areas like care navigation, ultrasound tech, and value-based care tools. The largest deal of the quarter ($200M Series D) went to Foodsmart — a telenutrition company focused on chronic disease management.

Source: CB Insights — Foodsmart Funding Insights

• Digital health exits increase in Q2’24, rising from 26 to 32 QoQ. AI-driven platforms were the highlight here, with Tempus (precision medicine) and XtalPi (drug R&D) going public via IPO and Nuvo Group (remote pregnancy monitoring) going public via SPAC. Digital health M&A exit activity also picked up in Q2’24, especially in Europe, which saw M&A deals jump from 5 to 10 QoQ. Globally, virtual care, provider workflow tools, and drug R&D platforms were key categories for M&A in Q2’24.

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From ambient documentation to surgical tools and digital wound care, AI solutions are helping providers focus on patients, improve diagnostics, and find new ways to perform surgeries and other procedures.

To determine which health systems are most prepared for the shift, CB Insights has launched the Hospital AI Readiness Index.

We looked at the top private-sector health systems in the US (by hospital count) and ranked them based on how prepared they are to adapt to a rapidly evolving AI landscape across 2 key pillars: innovation and execution.

• Innovation: The innovation score measures a health system’s track record of developing or acquiring novel AI capabilities. This score is based on CB Insights data including patents, acquisitions, and deal-making activity. It also considers the presence of an AI-dedicated research center.
• Execution: The execution score measures a health system’s ability to bring AI-powered products and services into clinical practice as well as deploy AI internally across business and back-office functions. This score is based on CB Insights data including business relationships, product launch media mentions, and earnings transcripts.

Below, we present the 25 health systems (inclusive of subsidiaries and venture arms) most prepared for AI.

Want to dive into key data featured in this index? CB Insights customers can check out the links below:

• AI investments
• AI acquisitions
• AI patents

Leaders

Mayo Clinic leads in AI readiness primarily due to its relatively high level of AI innovation. 

Its innovative nature is reflected in part by its patent activity. For example, Mayo has filed 50+ patents across areas like cardiovascular health and oncology. It has also invested in AI-enabled companies addressing a range of use cases in healthcare, from clinical documentation to surgical intelligence.

Intermountain Health and Cleveland Clinic round out the top three. 

Notable activities for these players include Intermountain’s internal development of a real-time clinical decision support platform. Meanwhile, Cleveland Clinic stands out on the execution front due to its high volume of AI-focused business relationships, such as a partnership with PathAI focused on leveraging pathology algorithms to enhance translational research and clinical care.

Source: CB Insights — Cleveland Clinic Business Relationship Insights

Innovation

Innovation scores are based on the presence of an AI-dedicated research center and CB Insights data on AI-related patents as well as acquisitions and deal-making activity since 2019 (as of 5/29/2024).

The most active health system in terms of investment count is Mayo Clinic. Its investments highlight areas where AI is picking up steam in healthcare. For example, at the end of 2023, it participated in a funding round for Abridge — a startup that helps transcribe patient-provider conversations and create clinical notes using generative AI — alongside investors like CVS Health Ventures, the American College of Cardiology, and Kaiser Permanente Ventures. Mayo Clinic has also funded companies like Theator, which combines computer vision and AI to help surgeons draw and act on insights from videos of procedures.

Intermountain Health is the second most active AI investor among evaluated health systems. Via its venture arm, Intermountain Ventures, it backed AI-powered patient engagement platform Gyant, which has since been acquired. Most recently, its venture arm invested in Freenome, which develops blood tests for early cancer detection.

When it comes to patent count, Mayo Clinic and Cleveland Clinic lead the pack. 

One focus area for Mayo Clinic is cardiovascular health. For example, in 2022, it was granted a patent for a system that uses a machine learning model to analyze electrocardiogram (ECG) data and predict the likelihood that a patient will have a stroke. 

Source: CB Insights — Mayo Clinic patents

Meanwhile, Cleveland Clinic was granted a patent for a decision support system that utilizes machine learning to individualize radiotherapy doses, enhancing the precision and effectiveness of cancer treatments.

The evaluated health systems are not overly acquisitive — just one has inked an acquisition in the past 5 years: Providence. In 2019, it acquired Lumedic, which uses blockchain and AI to streamline healthcare revenue cycle management.

Execution

Execution scores are based on CB Insights data including AI-related business relationships, product launch media mentions, and earnings transcripts since 2019 (as of 5/29/2024).

The majority of the health systems evaluated for this ranking have established business relationships with AI-enabled companies.

For example, in 2024 so far:

• Mayo Clinic teamed up with Techcyte to develop a platform that will help healthcare organizations harness AI in their pathology practices.
• Meanwhile, Banner Health worked with Regard to ease the administrative burden on clinicians by automating key tasks, like notetaking and chart reviews.
• Johns Hopkins Medicine partnered with Healthy.io to offer digital wound care services to patients.

Few evaluated health systems have earnings calls, as many are non-profit organizations with different financial reporting requirements than publicly traded companies. However, earnings calls among systems that do hold them reveal how AI is coming into view in a hospital setting. 

For example, Community Health Systems’ EVP of clinical operations, Miguel Benet, highlighted how AI could be deployed to streamline clinical documentation on an earnings call in Q4’23. He also discussed how CHS is using AI to provide patients with relevant information regarding local resources upon discharge — an initiative that has already yielded positive results, such as reductions in length of stay.

Source: CB Insights — Community Health Systems earnings transcripts

Four of the health systems on this list have launched AI-enabled products. 

For example, last year, Intermountain Health developed a platform equipped with real-time clinical decision support tools that leverage AI to improve patient diagnosis and treatment. Just a few months ago, CommonSpirit Health launched Insightli, an internal AI assistant capable of generating written content.

The post Which hospitals have the most AI innovation? Our AI Readiness Index shows Mayo Clinic is leading the pack appeared first on CB Insights Research.

These leaders are harnessing their existing offerings — in areas like cloud computing, AI, and hardware — to service healthcare providers and pharmaceutical companies.

While big tech players are competing with each other in this landscape, they are also carving out distinct strategies: 

• Amazon is going deeper into primary and specialized care.
• Google is amassing troves of health data, which could play a role in its biotech bets. 
• Microsoft is equipping healthcare organizations with AI tools to improve clinical research, drug R&D, and care delivery.
• Nvidia’s long-standing hardware dominance positions it to play a major role in the future of smart hospitals. 

This report uses CB Insights datasets like investments, acquisitions, business relationships, patents, buyer interviews, company scouting reports, and more. Learn more about our data here.

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As a result, femtech categories — spanning hardware, software, and tech-enabled services — have emerged to address a variety of women’s health needs, from menstruation and maternity to menopause and pelvic health. 

To help strategy teams prioritize femtech markets in their planning decisions, we plotted markets using CB Insights’ TECH framework, which scores markets across 2 dimensions:

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Digital health funding grew 48% quarter-over-quarter in Q1’24. This growth was supported by an increase in $100M+ mega-rounds, which were largely directed at biotech startups and other players leveraging AI.

Despite the increase, however, total funding still came in below pre-pandemic levels in Q1’24. Meanwhile, deal count continued to trend down.

Based on our deep dive below, here is the TL;DR on the state of digital health:

• ​Global digital health funding increases 48% QoQ to reach $3.7B in Q1’24. However, funding was still down 12% vs. Q1’23 and 63% vs. Q1’22. Meanwhile, digital health deal count declined in Q1’24, dropping to its lowest quarterly level since 2014.
  
  
• Funding to US digital health startups rises 44% QoQ. However, the US also saw deals drop to 144 — the fewest in a quarter since 2013. Despite the decline, the US still saw the majority of global digital health deals (53%) and funding (70%) in Q1’24. The US also secured 6 out of 7 digital health mega-rounds in the quarter.
• Average digital health deal size is up 38% in 2024 so far. After dropping from $23.1M in 2021 to $11.9M in 2023, average deal size is up to $16.4M in 2024 so far. This is being driven in part by the resurgence of mega-round deals. In Q1’24, these deals accounted for their second-highest share of quarterly funding since 2022.
• Digital health sees 7 $100M+ mega-rounds in Q1’24. Digital health mega-round deals rebounded QoQ in Q1’24. The largest digital health deal of the quarter went to Freenome — a biotech company focused on cancer detection. While biotech drove the top deals, Q1’24 mega-rounds were spread across the digital health industry, from biomedical NLP to robotics for microsurgery.
• No new unicorns (private companies valued at $1B+) emerge. While Freenome added $1B to its valuation following its Series F mega-round in February 2024, the company had already attained unicorn status in 2020. Among Q1’24 mega-round earners, Abridge saw the largest increase in disclosed valuation. It reached an $850M valuation — up 350% from October 2023.

The post State of Digital Health Q1’24 Report appeared first on CB Insights Research.

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Based on our deep dive below, here is the TLDR on the state of digital health:

• Global digital health funding halved for the second straight year in 2023, while deals dropped by more than a third. With just $13.2B raised across 1,397 deals in 2023, funding and deals fell to their lowest levels since 2016 and 2014, respectively. Amid the downturn, the US held its leadership position, attracting more than half of all deals.
• Despite the drops, median deal size remained at $4M — the highest on record. While median digital health deal size has trended up for more than a decade, venture deal sizes more broadly have deflated since 2021.
• Mega-rounds have all but disappeared from the digital health realm. There were just 3 $100M+ rounds in Q4’23 — the lowest count since 2016. On an annual basis, mega-round count hit 20 for all of 2023, falling well below even the quarterly average for 2021 (37 deals per quarter).
• The digital health unicorn herd started to shrink in 2023. Unicorn loss is outpacing unicorn births — a trend driven by a mix of startup exits, down rounds, and shutdowns. Despite the emergence of 4 new unicorns in 2023, digital health’s total unicorn count dropped from 97 to 94 over the course of the year. 
• Digital health M&A nearly doubled in Q4’23, indicating that consolidation is picking up in the market. If funding remains sparse and IPOs remain largely out of reach, M&A will become an increasingly attractive option for cash-strapped digital health startups.
• After falling out of the top investor rankings, Andreessen Horowitz returned to tie for the top spot in Q4. The investor backed 5 unique digital health companies in Q4’23, tying Plug and Play Ventures for the title of “most active.” Thanks to its digital health bets in Q4’23, a16z added yet another unicorn to its portfolio.
• Care delivery & navigation tech held on to its funding crown in Q4’23. With $837M raised in Q4’23, care delivery & navigation tech remained the top-funded digital health sector. It was followed by monitoring, imaging, and diagnostics tech with $501M.

Below, we’ll explore these themes across 7 charts.

Spurred by the onset of the Covid-19 pandemic — as well as the broader tech boom — digital health funding skyrocketed to unprecedented highs in 2021. However, as the pandemic has faded from public imagination, digital health startups have watched funding halve with each passing year, dropping by 52% year-over-year (YoY) in 2022 and 48% in 2023.

At $13.2B, digital health funding for 2023 stood at its lowest level since 2016. Quarterly funding levels have yet to give any indication of a recovery. Dollars to the space fell every quarter in 2023, dropping by 44% from Q1’23 to Q4’23. With just $2.3B raised in Q4’23, digital health startups saw their lowest quarterly total in 8 years.

While no major global region was spared from the downturn, Asia was hit the hardest. In 2023, the continent saw greater YoY drops in funding (-55%) and deals (-46%) than both the US and Europe. While US funding didn’t fare much better — nearly halving last year — the country continued to lead digital health funding by a significant margin, securing nearly 70% of global equity dollars to the space. Unsurprisingly, US-based startups also led on a quarterly basis, even grabbing all 10 top digital health deals in Q4’23. 

While funding has been falling at an even pace since 2021, the downturn in dealmaking is only accelerating with the pandemic in the rearview mirror. Deals to digital health startups dropped by 19% YoY in 2022 and 38% in 2023. Over the course of 2023, digital health startups raised just 1,397 deals — the lowest annual count in 9 years. Quarterly deal count in Q4’23 (243 deals) also hit its lowest level since 2014.

Although digital health investors may be more hesitant to strike a deal now than in 2021, they are putting even more skin in the game where they do see value. Median equity deal size remained steady at a record high of $4M in 2023, representing an 8% increase from the heady days of 2021. This stands in stark contrast to venture at large, which saw a 22% decrease in median deal size over the same period. In digital health, the rise in deal size is particularly pronounced among Asia- and Europe-based startups — both groups have watched median deal size climb over the past 2 years.

Digital health investors may be willing to bet more cash on promising startups, but the upper dollar limit for many has dropped. Mega-rounds (deals worth $100M+) have all but disappeared from the digital health landscape. In Q4’23, just 3 of these deals were inked — the lowest count since 2016. Alongside deal count, quarterly mega-round funding also dropped to an 8-year low of $400M.

Digital health mega-round funding has fallen even further than funding to the space at large. It was down by 96% from its Q2’21 peak in Q4’23, while broader digital health funding decreased by 85% over the same period. So while mega-rounds regularly contributed more than half of the market’s funding in 2021, that share dropped to just 17% in Q4’23 — the lowest since 2019.

The post State of Digital Health 2023 Report appeared first on CB Insights Research.

On the drug R&D front, pharma players are using the tech to design new drugs in a fraction of the time. For instance, Insilico Medicine has brought an AI-generated drug for idiopathic pulmonary fibrosis to Phase II human clinical trials — in about half the time it would take without AI. Startups here saw a flurry of exit activity in 2023 as incumbents race to get involved.

Meanwhile, in the hospital setting, genAI is helping summarize complex doctor-patient interactions, make EHR entries more precise, and enhance diagnostic imaging. Cloud giants like Microsoft and Amazon have announced clinical documentation services that allow providers to automatically create medical notes, while EHR leader Epic has partnered with Microsoft to integrate genAI tools into its EHR system. 

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Healthcare isn’t an entirely new sector for Nvidia. It invested in healthcare-focused computer vision startup Zebra Medical Vision, for instance, back in 2017.

In the past few years, however, its investments and partnerships have coalesced into a clear strategy, as the chipmaker builds on its work in advanced computing to lay the foundation for next-gen AI applications in health IT. For instance, it has redoubled efforts in areas like edge computing, which makes it easier to deploy AI in care settings where broadband internet connectivity is limited or nonexistent.

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And increasingly, RPM tech is getting a boost from AI. AI systems and machine learning (ML) algorithms are helping make RPM solutions — like at-home ECG monitoring and remote fall detection — more effective and efficient, thereby improving patient outcomes.

Just 2 years ago, during 2021’s venture funding boom, roughly a quarter of all RPM funding went to companies building AI solutions. This year, in a sign of AI’s growing presence in RPM, AI companies account for three-quarters of funding. 

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Over the last few years, Bayer has forged business relationships with other organizations to help prevent, diagnose, alleviate, and cure diseases.

One goal unifying Bayer’s activity is that it is looking to expand beyond traditional drug discovery and development. To do so, the pharma giant is rapidly tapping into a variety of emerging technologies, including digital therapeutics, real-world data, and artificial intelligence.

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Mental health tech solutions have emerged to meet the skyrocketing patient demand. These range from tele-psychiatry solutions — which aim to expand access to therapy and medication — to workplace wellness platforms that address issues like stress and burnout.

For payers and providers, mental health tech opens up opportunities to provide cost-efficient and preventative care, driving down the cost of treating each patient in the long term.

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At-home lab testing vendors, for instance, allow patients to perform diagnostic tests across a wide range of specialties and follow up online with physicians. Meanwhile, more targeted solutions like smartphone-based skin testing give patients the ability to take pictures of their skin for remote evaluation by dermatologists or AI algorithms.

RPM has proven crucial in reducing hospital readmission rates. For example, the University of Pittsburgh Medical Center reported a 76% decrease in patient readmission rates after implementing remote chronic and post-acute illness monitoring. 

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To fight this disease, tech companies are supporting patients, providers, and pharma players by developing tools to improve cancer care, diagnosis, and drug discovery. 

Solutions like liquid biopsy screening are less invasive, faster, and more cost-effective than traditional biopsies, while cell behavior simulations can model tumor behavior to speed up drug R&D.

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Its venture arm, Mayo Clinic Ventures, has backed nearly 100 deals and invested almost $300M since its inception. Furthermore, Mayo Clinic has an internal innovation lab, the Center for Innovation (CFI), which brings tech inventions to market that Mayo Clinic Ventures funds and commercializes.

Mayo Clinic’s tech bets span across hospital functions, from surgical intelligence to diagnostics to care delivery. For example, in 2022, Mayo Clinic invested in Endiatx, which makes a pill-sized endoscopy robot. A recent partnership, meanwhile, integrates Mayo Clinic data into K Health‘s AI algorithm for hypertension treatment planning.

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For example, Amazon announced its acquisition of primary care platform One Medical in July 2022. Just a few months later, it launched Amazon Clinic, a chat-based virtual care platform. In January 2023, it opened up RxPass, a subscription add-on for Amazon Prime members that offers unlimited medication delivery for a flat monthly fee.

Amazon has also been forging strategic partnerships and investing in companies to support its expansion across digital therapeutics, remote monitoring, and health data services. In 2021, Amazon released Amazon HealthLake, a HIPAA-eligible service that uses machine learning to support the collection and analysis of health data.

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One of the earliest applications of AI in healthcare was in diagnostic imaging, where big tech companies and startups alike developed computer vision algorithms to detect anomalies from MRIs, CT scans, X-rays, and ultrasounds. 

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Over the last several years, Novartis has acquired, partnered with, and invested in companies that support its mission to leverage artificial intelligence (AI) and other technology to improve its processes and create new products.

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Genomic profiling solutions provide genetic patient data that help physicians determine the appropriate course of treatment. Many solutions in this space also include a software portal that enables physicians to navigate data and make easier, better decisions.

Genomic profiling platforms also allow pharma companies to gather deep data across potential and existing patient populations.

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Medical imaging AI technologies use machine learning and computer vision to detect, characterize, and monitor diseases through the analysis of CT scans, MRIs, ultrasounds, and other medical imaging systems.

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Remote monitoring platforms offer transparency into patient health outside of the clinic. Most platforms include analytics and integrations to provide exception-triggered alerts and actions before a patient’s condition deteriorates.

Connected wearables and medical devices are the most common types of remote monitoring systems, but the category also includes ambient sensors, analysis of vocal biomarkers, and other non-device methods.

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Computer-aided diagnostic imaging utilizes artificial intelligence (AI)-algorithms to detect, extract, and communicate data from medical images with more efficiency and accuracy than the human eye.

Health professionals deploy this technology across several imaging modalities to improve the triaging, detection, diagnosis, and prognosis of various medical conditions. The technology is expanding the possibilities for diagnostic imaging by enabling the detection of previously undetectable conditions and providing earlier detection of diseases typically caught too late to be treated effectively.

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