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Signify Premium Insight: United Imaging Gives the Public what it Wants

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As 2021 drew to a close, Chinese medical imaging vendor, United Imaging, made clear its intention to list on Shanghai’s technology – STAR index in 2022. This ambition was last week realised, when the vendor made its debut on the bourse.

Demand for shares in the company was high, with the firm’s IPO massively oversubscribed, and an increase in share price of as much as 75% when the company made its debut on the index. The offering will net the vendor more than $1.6bn, with the firm stating it will use the cash to fund research and development, production and marketing.

The Signify View

Even before United Imaging announced it was going to list publicly at the end of last year, the move seemed like the natural progression. The vendor has grown incredibly quickly since being founded in 2011, and now brings in around $1bn in revenue annually. To continue to grow, raising capital was necessary as it bids to compete with the largest international imaging vendors.

To do this, the vendor will have several priorities for its newly-raised funds, chief among them is product development. In the first instance, this means investing in the development of products that will allow it to better compete with GE HealthCare, Philips and Siemens Healthineers. United Imaging has been more successful compared to its domestic peers, thanks, in part, to its focus on high-end imaging rather than just cost competitiveness as is more typical of its domestic peers. To continue its arc of success this should remain a priority.

United Imaging therefore will likely invest in products to compete with other vendors’ most premium products, such as photon counting CT. CT is, by far, United Imaging’s biggest product line, accounting for around half of all revenue. As the next generational evolution of that modality, offering a flagship photon counting CT system and, over time, enriching its lineup with photon counting detectors, enables United Imaging to continue to compete on a comparable footing. In a similar vein, other paths being trod by other vendors such as helium-free MRI, and high-Tesla MRI represent necessary product development directions if United hopes to truly be thought of a competitor to other international vendors.

Portfolio Planning

In addition to continuing the development of product categories in which United Imaging is strong, the vendor will also need to address the gaps in its portfolio. As hospitals are increasingly looking to enter broader multi-modality imaging deals, they are turning to vendors which can address the majority of their imaging requirements and offer holistic solutions. United Imaging will therefore need to address the gaps in its line-up with modalities like angiography, mammography and ultrasound, for example, which currently represent significant omissions. Developing products in these modalities and addressing these gaps in its portfolio could therefore represent an opportunity beyond sales of those modalities themselves.

Another aspect of product development, which, pragmatically at least, is arguably more important than the portfolio offered by the vendor, is integrated production. For their advanced imaging lines, the likes of GE, Philips and Siemens, make almost all components themselves. This gives them more granular control over product, enables them to react to adversity in supply chains and external shocks and helps them to control costs and quality more tightly. United Imaging on the other hand still relies on external suppliers for many core components. The vendor therefore is likely to invest some of the fruits of its listing into bringing production of those components in-house. This is particularly true for components that are produced outside of China, with trade barriers and geopolitical tensions making dependency on international supply chains risky.

Turning Away from China

Beyond the products themselves, United Imaging also needs to invest in sales and service infrastructure internationally. United Imaging’s revenues have, so far, come almost entirely from its home market. The vendor would do well, however, to prioritise international growth. Chinese policies which focus on centralised purchasing are likely to depress the average selling prices of modalities in the country, given United Imaging’s strong dependence on these Chinese market, even a relatively small decrease in selling price could have a significant impact on profitability.

Furthermore, scale is crucial for success of the vendor. Even though United Imaging spends a relatively high proportion of its revenue on research and development, its actual spend is far outstripped compared to its much larger rivals. The only way it will be able to reduce this deficit and compete at the upper echelons of medical imaging is by selling significantly more medical imaging systems. It is unrealistic for such an increase in sales to come from its domestic market, particularly given the fact that many Chinese providers purchased additional CT systems and brought forward purchasing plans during the Covid 19 pandemic. Such hospitals, which have recently acquired new CT equipment are unlikely to make additional purchases in the near future, until the installed base is ready for replacement. There will be some growth as the state continues to invest in expansion of healthcare in China, but this offers nowhere near the opportunity afforded by international markets.

International Coordination

The specifics of this international expansion do, however, present some challenges. United Imaging aspires to compete at the premium end of medical imaging with the likes of GE HealthCare, Philips and Siemens Healthineers. However, to truly compete with these vendors, United Imaging must make inroads in mature markets such as the US and Western Europe. These markets are particularly difficult for United Imaging to displace incumbents. In these markets, providers are primarily concerned with image quality, and the quality of service they receive, with promises of minimal downtime for example, a significant benefit to hospitals. Doctors in these markets will also impede United Imaging’s progress, with many professionals lacking the motivation or availability to learn how to use a different vendor’s equipment, particularly if there is no significant benefit in terms of performance. Strong brand loyalty by the end user market in such developed nations further restricts penetration possibility and market access for new vendors.

This reluctance to adopt United Imaging’s solutions in mature markets could force the vendor to direct its efforts towards developing markets, including countries in Africa, and members of the Commonwealth of Independent States, including Russia. However, though these markets offer a better opportunity for United Imaging to realise sales, the markets themselves hold far less potential than other mature markets. As such, even though United Imaging will find the markets fruitful, they won’t be able to offer the vendor the scale it needs to truly compete with its established international rivals.

What’s more in these lower-value markets, where cost competitiveness is more significant, United Imaging could also start to lose out to other vendors, which don’t have the same lofty aspirations and instead are focused solely on producing affordable systems. Other Chinese vendors and Indian vendors such as Triviton, for example, could squeeze United Imaging in some markets by offering even more affordable advanced imaging systems.

Shares for the Future?

Despite these challenges, United Imaging’s achievements must be acknowledged. The speed at which the Chinese vendor has grown, and the range of advanced imaging products it now offers is impressive. It has also effectively capitalised on external trends. It has benefited significantly from Chinese state support, its government’s ‘buy local’ procurement policies and increased healthcare spending. The vendor has also benefitted from Covid 19, with revenues for its CT product line, a key modality used in Covid care, increasing by more than 150% between 2019 and 2020 largely as a result of increased covid spending. It has then rode this wave to its IPO, also benefitting from investors’ willingness to put money into healthcare firms, which are seen as something of a safe haven.

Even with these advantages and United Imaging’s execution, the road ahead is still difficult. $1.6bn is a lot of money, but it will only go so far. Even with this cash, United will struggle to match its international rivals’ development, which will make it hard to compete with them in developed markets, which will make scaling at the rate needed to maintain development difficult. In the meantime, it can target emerging markets, but the longer it is seen as a cost-focused vendor servicing less technically-demanding markets, the harder it will be to make the leap to the top tier markets, and the less chance it will have of competing with the established market leaders.

These constraints mean that United Imaging will likely have to settle for less prodigious growth over the coming years. Developing additional products and bringing component production in-house will offer significant benefits, but these will only truly be realised over time. More fundamentally, United Imaging also needs to home in on its targets. Can it really stand shoulder to shoulder with GE HealthCare, Philips and Siemens Healthineers? Or should it look to strike out and ace its own, unique approach. These are issues which, even given the money raised, listing publicly can’t solve.

About Signify Premium Insights

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here

Signify Premium Insight: AI Making the Move to Maturity

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here.

Dr Sanjay Parekh, Senior Analyst

The medical imaging AI market is among the most dynamic of all the sectors in medical imaging. Its nascency, its rate of technical development and the application of the technology are combining to create a market that is changing incredibly quickly.

Despite the volatility of the market, senior analyst and author of Signify Research’s AI in Medical Imaging report, Dr Sanjay Parekh, has been able to discern several key trends in the market.

Great Growth

“The market for AI-based image analysis tools for medical imaging is set to reach $1.36bn by 2026,” Parekh states, “up from $402m in 2021.” Much of this revenue is for stand-alone AI tools, but AI-based advanced visualisation (AV) bundled AI tools are also included (accounting for 27% of the total market in 2021).

This represents a CAGR of 27% between 2020 and 2026, highlighting that the AI market is gaining momentum, many of the reasons for which are clear.

“There was for instance a large flurry of regulatory approvals in 2020 and 2021. In the US in 2020 for example, there were more approvals than in 2018 and 2019 combined. There was also the first wave of NMPA Class III approvals in China. With these regulatory approvals vendors can commercialise their tools.

“As well as having more products on the market, there has been continued progress with regards to reimbursement. There is the continued reimbursement for HeartFlow’s FFR-CT solution in the US, the UK and Japan, as well as parts of Europe. Additionally, pockets of China are already reimbursing the use of FFR-CT tools, but national reimbursement is still pending. There has also been a flurry of Category III CPT codes [for which there is no compulsory reimbursement] provisioned for quantitative image analysis tools for ultrasound, MRI and CT, which as well as encouraging the uptake of AI, could lead to reimbursement. While NTAP payments have also been renewed and expanded, such as the recent Optellum clearance, which has defied the norm and will now receive reimbursement for its Virtual Nodule Clinic solution for lung cancer despite the CPT code remaining as Category III.

“All of these factors combined will help the markets continue to grow.”

Areas of Interest

Growth will not be equal across all clinical segments, however, with four areas, which currently represent around 87% of the market, set to continue to stand out. These are cardiology, neurology, pulmonology, and breast imaging, with each having facets that mean they are likely to continue powering growth for AI vendors.

Use of AI is the most mature in the breast imaging market; however, opportunities for growth are more limited than elsewhere. “Because of the relatively limited number of use cases; namely breast nodule detections and breast density analysis, the breast imaging market will not to be as large as the other three,” continues Parekh.

“Cardiology is likely to account for the largest proportion. This will be driven by two factors. The first is increasing uptake and continued reimbursement for FFR-CT tools. Even accounting for its failed SPAC merger, HeartFlow, one of the success stories for the medical imaging AI market, has a relatively large install base and strong commercial traction as well as still offering an appealing value proposition. There are also opportunities for FFR-CT, especially in China, as vendors like Keya Medical, Shukun Technologies, and Raysight receiving regulatory approval for their FFR-CT tools.

“In addition, clinical guidelines recommending CT imaging as a first line diagnostic procedure will drive the adoption of AI.”

Stroke care is also set to rally.

Neurology will be a growth area mainly because of stroke imaging AI solutions. The NTAP code for stroke LVO, which was first issued in 2020 to Viz.ai and then renewed in 2021, was renewed again in 2022 and it looks set to be made permanent soon, thanks to the uptake of stroke imaging AI tools and the increased use of the code in such instances.

“Not only has the payment been created, but providers are using it and its use shows that providers value the end-to-end stroke solutions which benefit the entire care pathway as well as the radiologist.”

There are also other opportunities within neurology, with brain quantification tools, for example achieving moderate success. Some vendors offering such tools are generating revenue, but, while these will continue to be valued, other drivers such as the commercialisation of drugs for neurodegenerative disease are needed before they become a major driver of growth.

“Finally, in pulmonology, the relative value of using AI market is smaller compared to FFR-CT or head CT for example. Although there are vendors working on comprehensive solutions for both chest X-ray and chest CT that do restore that value, the most successful among them are setting a benchmark for other tools looking to gain traction. Further, the continued roll-out of screening programmes for lung cancer and TB, for example, will drive further traction in this market.”

Relinquishing a Point

There are commonalities across these clinical areas, however. It is becoming clear that the utility of point solutions across modalities and clinical areas is in general, very limited. Developers who can only offer single point solutions are looking increasingly unlikely to be selected by providers.

Instead, tools that offer the most value to providers will gain success. This value, however, can manifest in various ways. Many solutions focus on efficiency, but there are also solutions that could actually slow diagnoses, but still enhance the quality of a diagnosis by offering additional metrics, for example. This value is, in some cases, also no longer derived from incremental improvements in specificity or sensitivity that new tools might offer.

“If you offer 93% accuracy compared to 92%, is that going to make a difference,” Parekh asks. “Are you going to get a better diagnosis or is the patient going to be on a completely different treatment pathway? No. Instead value is extended beyond the analysis of the pixels in an image, to patient care and improvements to the clinical care pathway. The vendors that have started doing that are the ones that are going to succeed.

“Breast imaging tools, for example, that combine detection, quantification and classification of nodules, which are far more valuable than those which only offer nodule detection. Moreover, adding in breast density analysis will enhance the value proposition of such a solution even further. More significantly, however, are the tools that are looking at radiology more broadly and seen to offer value across the clinical care pathway (beyond the radiologist). These solutions can come from vendors which solely offer AI, or those which also offer capability to deploy and integrate AI.

“These vendors can bring in advanced visualisation capabilities, workflow capabilities and even structured reporting capabilities to address a given use case, while also offering their own native or third-party AI image analysis capabilities to create entire workflow packages. That is AI demonstrating value.”

Money to Money

Value is also forthcoming in a broader sense. Despite the turbulence in some tech markets and in some corners of the medical imaging market, investment for medical imaging AI vendors is still available, although it is becoming more discerning.

“Investors seem to be more than willing to continue to back vendors that have already shown progress,” opines Parekh, “but we are not seeing many Angel or Series A rounds.”

“Where we are seeing a lot of action is for the later-stage funding rounds, which are increasing in both size and number. This indicates that a set of market leaders are being established, such as the $100m funding club [a term coined by Signify Research including vendors that have received more than $100 million in total in venture capital funding]. Even with this greater investment in established companies we are starting to see evidence of a market shakeout.

“Last year we saw Nanox acquire Zebra Medical Vision, at the start of 2022 we have seen MaxQ-AI closing its radiology business, and Sirona acquiring Nines. RadNet, a large outpatient imaging group in the US also acquired two Dutch-based AI start-ups Aidence and Quantib to add to its portfolio after previously acquiring DeepHealth, and expand its push to deploy AI across screening for some of the most prevalent cancers. There is also some speculation about some other vendors also making pivots after not receiving funding that was expected. We have seen consolidation coming for a long time, but between the investment being focused on the largest vendors, and the difficulties for the smaller vendors, we are starting to see the shakeout take place.”

The impact of this market shakeout will be different in different regions. One area that is more difficult to make predictions for is Europe. Presently, the Western European market is starting to catch up with the US, but this growth is expected to stagnate in May 2024 when the new European Union Medical Device Regulation (EU MDR) is coming into force. There is currently a backlog of 12 to 18 months for vendors to upgrade their CE Mark to the incoming regulation, not to mention the more stringent requirements for this regulation. This raises the possibility of many vendors missing the deadline and therefore being unable to offer their products commercially in the EU.

Approval Ratings

This could have significant impacts, say Parekh.

“It is more likely that the larger vendors, the ones with the funds to pursue the MDR, will be the first to receive it. If you are a smaller vendor, then you may not want to, or be able to go for MDR approval. Ultimately, that will leave those that have MDR certification by May 2024 with an ‘early-to-market’ advantage over those that don’t. It could effectively level the playing field, and serve as a reset button, with only those that have been able to secure the new certification, regardless of past CE Mark approvals. This regulatory backlog is also therefore likely to hold back the market as a whole.

“It could also lead a lack of innovation, with smaller start-ups and research groups shifting their focus from radiology, keen to avoid the additional barriers they must pass, so there could also be a short-term innovation gap. This is another reason we could see more consolidation in the market.”

Despite these challenges the future is still bright for medical imaging AI vendors. The market increased by more than $60 million between 2020 and 2021, and growth is only set to continue. This shows a young market taking the first steps to maturity and a nascent technology making the first moves toward more mainstream adoption.

“Overall,” Parekh concludes, “it is growing, at a steady pace for now but with a big ramp up in the medium term, from 2024 onwards.”

“All signs are positive.”

About Signify Premium Insights

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Signify Premium Insight: The Tightrope Upon Which Lunit Must Walk

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here.

Lunit recently announced that it has received preliminary approval for an IPO on the South Korean KOSDAQ index. Following the approval, the Seoul-based AI developer now plans to submit a listing within the first half of the year.

The outfit already has partnerships with several large international imaging vendors, including GE Healthcare, Philips and Fujifilm to incorporate its AI capability into their imaging systems, but Lunit says the money from the funding round will enable it to further develop its AI product range, and expand its global commercial reach. This will entail promoting its products, which include an AI tool for analysing mammograms, an AI solution for analysis of tissue slides for cancer biomarkers, and a comprehensive AI solution for chest X-rays that detects 10 of the most common findings, in more markets across the world.

The Signify View

That Lunit has decided to place its fortunes in the hands of public investors should come as no surprise. As detailed in a recent Premium Insight discussing medical imaging AI vendors with more than $100m of venture funding, Lunit, like many of its successful peers shares some common traits. The vendor has, for instance, taken a very robust approach to product development. Instead of relying solely on one of the available training datasets, which can introduce some ambiguity and aren’t always perfectly labeled, Lunit has chosen to use training data validated against biopsy results. This helps ground the AI tool’s algorithm and minimise the likelihood of errors. A tool is only as good as the data it is fed so supplementing images with other clinical data is a prudent approach.

In a similar vein, the vendor has also been thorough with regard to clinical validation. One of the hurdles stymieing the broader adoption of AI is a lack of robust evidence. To be profitable AI vendors need to prove their solutions are valuable to providers, to warrant hospital budgets and convince policymakers that their tools deserve reimbursement. To do this these vendors must undertake strenuous, detailed clinical validation studies. These are expensive and time consuming to conduct, but they are necessary. This need is compounded as AI vendors look to grow globally, with developers obliged to prove their solutions are as effective on non-local populations. Lunit has been able to meet this requirement, and can point to a wealth of published studies open to scrutiny, as well as regulatory approvals for its Insight CXR and Insight MMG chest X-ray and mammography solutions in the USA, Europe, Japan and South Korea and for SCOPE PD-L1 in Europe.

Available Options

In addition to this technical capability, the vendor has also been commercially savvy. As well as selling its products directly, Lunit has made its products available on several AI marketplaces, allowing providers which use, for example, Sectra’s imaging IT solutions to incorporate its tools through that company’s Amplifier Marketplace.

More significantly, the vendor has also sought to utilise partnerships to target new markets. It has received $26m from liquid biopsy specialist Guardant Health. As well as boosting Lunit’s bank balance, the collaboration will help the AI vendor target the US oncology market with its SCOPE tissue analysis platform. Lunit has also looked to international imaging vendors to grow, with the company inking deals with GE Healthcare, Philips and Fujifilm helping encourage Lunit’s adoption among those vendors’ install bases.

Such endeavours are for naught, if the products themselves are inadequate. Lunit, however, has avoided this trap. While its range of products is small, comprising of three solutions, one for chest X-ray, a second for mammography and a third for pathological tissue analysis, they are focused on valuable areas. Insight CXR, for example is a solution that is on the rising tide of increasingly comprehensive AI tools which, like those from Annalise AI and Oxipit AI seek to provide greater clinical value to doctors than narrow AI solutions which are often more limited. Similarly, Lunit’s SCOPE solution is set to benefit from the growth of digital pathology and the establishment of closer ties between diagnosis and treatment.

A Time for Temerity?

Despite these strengths, however, listing publicly also represents a risk for the vendor. Reports suggest the listing offers Lunit a valuation of around $500m. This is a far cry from the valuations of the likes of HeartFlow and Viz.ai, which saw valuations as high as $2.4bn and $1.2bn respectively in their recent fundraising endeavours, however it is still a significant sum for a vendor that, according to Signify Research’s AI in Medical Imaging report, achieved just over $1 million in revenue and a loss of $16.5 million in 2020. While the IPO will furnish the vendor with ample capital, it also adds considerable pressure. It risks facing many private investors necessitating consistently strong quarterly performances, rather than sympathetic private investors au fait with the medical imaging AI market, which are likely to be understanding of more modest returns in the name of sustainable long-term progress.

There are other hurdles too. The enormous valuations that some medical imaging AI vendors have been able to achieve through the high availability of funding for AI firms over recent years, have, in some instances proved a hindrance to these AI firms when they have looked to list. The likes of HeartFlow and Keya Medical both sought to go public, before being forced to postpone their plans, in part due to the inability of public investors to match these lofty valuations. Furthermore, in many instances, vendors that did go on and list publicly have seen their share prices fall as they were unable to meet the high expectations of their public investors. This has been true of all Lunit’s closest South Korean peers.

Vuno listed at an initial price of KRW32,150 in February 2021, and is now trading at around KRW10,500. DeepNoid shares initially traded at a price of KRW25,200 in August 2021 but now sit languishing at an all time low of KRW11,400. JLK, meanwhile went public in December 2019 with an initial price of KRW8,330, rallied to KRW14,150 in September 2020 but now trades at KRW6,220. The market as a whole has suffered, with the KOSDAQ falling 13% year-to-date, but JLK, DeepNoid and Vuno have all underperformed even relative to this benchmark, falling 20%, 38% and 44% respectively.

A Hard Market

Making headway amidst these underperforming peers will prove difficult. This challenge will also be compounded by market complexities facing its products. While the tools themselves are sound, they are competing in difficult markets. Mammography for instance has well-established incumbent vendors such as Hologic and iCad, as well as a plethora of breast imaging AI start-ups each trying to eke out a share of the market. Similarly, Lunit’s Insight CXR product will not only face stiff competition, but even when used it will be fighting for a small percentage of the limited reimbursement available for chest X-rays. Both could be successful products, but could be slow to return sizable revenues. Lunit SCOPE is likely to be similar. There are considerable opportunities pertaining to digital pathology AI, clinically as well as in other areas such as drug discovery. However, the digital pathology market is so nascent, it is unlikely to significantly contribute to Lunit’s bottom line for several years.

These weaknesses do point to one area in which Lunit should prioritise following its IPO. As well as commercialisation efforts, building sales and support networks in new markets, Lunit must also spend heavily on the development of new tools. The vendor must channel its expertise into targeting new areas that offer high potential returns, whether for better-reimbursed modalities, high-value use cases, or care coordination tools that expand beyond image analysis itself, Lunit needs to supplement its current strength with tools that will be lucrative into the long term.

Don’t Look Down

Ultimately, Lunit’s growth up to this point has positioned it in a difficult spot. While the vendor must move forward, doing so requires overcoming considerable adversity. This is not a problem that is unique to Lunit, but each medical imaging AI vendor that makes it to this pivotal moment, must navigate it in its own way. Balancing the needs of its investors while continuing to invest in product development and market creation, will be tough. The need to create significant revenues and profits to justify its lofty valuation, while not neglecting the robust way it has approached algorithm training and clinical validation, which helped establish its credentials, means walking a tightrope, where one slip can send a share price tumbling.

Lunit will see a future in which the company is successful. Consistently generating revenues, with sustainable growth, a secure user base and an innovative roadmap. The vendor can lead its investors to this future, but its challenge will be in ensuring they don’t lose faith and fall along the way.

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Signify Premium Insight: VC’s $3.6bn in a Quickly Maturing Market

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here.

Co-written by Dr. Sanjay Parekh

In our recently released analysis of venture capital funding for medical imaging AI vendors (download free report here – note this report was published prior to Viz.ai’s very recent $100m series D funding round), Signify Research found that venture capitalists’ appetite for medical imaging AI is yet to be satisfied. Total VC investment in medical imaging AI has reached almost $3.6bn since 2015. What’s more, despite a dip in 2019, overall levels of funding have continued to rise making 2021 a record year in terms of investment raised at $815m.

This record-breaking year also saw the emergence of the ‘$100m club’ of vendors which have raised more than $100m in capital funding. Many of the vendors also highlight another trend detailed in the report; the eastward transition of funding, with companies from Asia and especially China accounting for an increasing and significant proportion of investment.

In this more nuanced analysis for Premium Insights clients, we dig deeper into these findings.

The Signify View

These headline figures only tell half the story, with large numbers of vendors choosing not to reveal the levels of funding they have secured. Circle Cardiovascular Imaging, for example, has reported raising almost $20m in funds, however, their latest undisclosed funding is estimated to be in the range of $75m-$100m, pushing the Canadian vendor’s total funding above $100m. This is a trend that is mirrored across the world. China’s Infervision raised $70m in series B funding, and $140m in series D funding, but did not disclose the results of its series C round. If this undisclosed round is taken into account, it is likely that the vendor has raised upwards of $300m in total, far higher than the $225m disclosed. Other vendors also share this dynamic, with Shukun Technology and Deepwise both harbouring far higher sums than publicly disclosed.

These high figures show the strength of these vendors and the emergence of prominent market leaders. Already members of the ‘$100m club’, these vendors are sitting on cash piles while also having NMPA Class III approvals, allowing commercial operation within China. This makes them formidable competition in the market, especially given that their lack of disclosure makes them difficult to accurately assess and limiting most international vendors from targeting the Chinese market.

Had these rounds been disclosed, we would be discussing a group of unicorns (those estimated to be worth more than $1 billion). However, other vendors have been more transparent. Viz.ai is an example of one vendor that can lay claims to this status, having confirmed its series D funding round of $100m itself earlier this week. This funding round took the total the company has raised to over $250 million, valuing it at $1.2 billion.

Chinese Action

More broadly, these funding rounds for Chinese vendors evidence the trend identified in Signify Research’s 2021 report, which showed that China is increasingly the hotbed of medical imaging AI VC funding. This is expected to continue, with 2022 likely to surpass other years as more vendors mature and secure larger, later-stage funding rounds. As detailed in a recent Premium Insight which addressed trends in regulatory clearances, more solutions are receiving Class III NMPA approval in China, a factor that is likely to encourage investment, with approved solutions often a more attractive investment target than those with no approvals. This growth in funding will also be compounded by the possibility that the Chinese market offers. As well as its insular nature, which makes penetration difficult for non-Chinese vendors, limiting competition, the market is also the world’s second-largest.

AI uptake has, so far, been very regionalised, with vendors targeting specific patient cohorts in certain areas. In China, where there are 15 provinces with populations of more than 40 million, sub-regionalisation is likely, with vendors targeting specific diseases based on provincial priorities, providing VC investors with plenty of viable targets, even if they are, individually, unlikely to become global powerhouses.

However, investment will peak, potentially as soon as 2022. In the US, VC investment peaked in 2018, at over $400m, after which it slipped backwards, plateauing around $150m. This is a result of market leaders emerging, securing later stage funding, increasingly growing revenues, and then receiving undisclosed private equity investments or attempting to list publicly. The Chinese market is approaching a similar scenario, with market leaders being established and some reaching the end of their VC funding journeys.

Lapping the Shore

These dynamics in funding, show that so far, there have been two waves of funding for medical imaging AI. The first peaked in 2018 (total funding of $772m; average deal size of $16.4m), but the second peak in 2021 was far greater (total funding of $875m) with an average deal size more than double ($33.6m) that of 2018.

The quantity of deals was higher in 2018 (47 deals), as a higher number of vendors looked to secure their initial rounds of funding, fostering the creation of the market for radiology AI. Since then, some tools have matured, and in a bid to increasingly add value to clinicians, become more sophisticated. The vendors who have developed these tools have grown and are facing significant costs in the commercialisation of their products. Resultantly, they have needed to raise more capital to fund this expansion and commercialising, spurring the recent second wave.

One indicator of this current wave is the growth in the number of vendors entering the ‘$100m club’. As vendors have matured and sought out later-stage rounds, the number of deals has declined (26 deals in 2021). However, these deals are frequently for very sizable amounts, taking increasing numbers of vendors past the $100m mark (ten vendors to date), a barrier that, until recently had only been broken by a very select few vendors, which met a very demanding criteria.

Vendors that have entered the ‘$100m Club’ of VC funding raised

These dynamics are, of course, not immune to wider influences, with the Covid-19 pandemic also playing its part. Part of the second peak rebound in 2021 was due to the market emerging from the pandemic, and investors were once again able to confidently invest in medical imaging AI start-ups. After husbanding cash throughout the pandemic VC investors could once again seek opportunities and take on more risk. Healthcare technology would also have been an attractive sector in which to invest, given the Covid-induced excitement around digital healthcare. Investors, with available cash and looking for companies in which to invest, bought into the story of AI helping radiologists become more efficient and deal with the backlogs they were left with. The pandemic had created a problem, which radiology AI could aid in solving.

The Looming Threat

These trends could contribute to the growing spectre of consolidation that is hanging over the medical imaging market, with a distinct gap between the minority of vendors that have secured sizable funding rounds and the long tail of vendors which have not. Since 2015, the top 10 vendors have, after all, raised an overwhelming 55% of all funding, while the top 25 vendors account for almost 80% of funding. These larger, better-funded vendors look set to increasingly take control of their specific market segments, making life difficult for smaller vendors to gain any traction and increasing the risk of casualties in this market.

Life could yet be difficult for larger vendors too, though, with higher VC investment rounds representing greater pressure on these vendors to start delivering the sizable revenues that they have promised. Reimbursement for medical imaging AI also remains limited and sporadic; the question of who will pay for AI, in many instances, is still unanswered. This may prove more of a challenge than expected, leaving many investors disappointed.

As these problems are worked through, vendors will go on to list publicly, as some including Keya Medical and HeartFlow have already unsuccessfully attempted; some may also be bought out by private equity, giving early VC investors the sizable returns they were hoping for. As this happens, there could be another wave of VC investment in medical imaging AI, given the technology’s transformative potential. However, the next cohort of start-ups backed by VC funding is unlikely to be in any of the established clinical segments (e.g., breast imaging, neuroradiology, cardiac imaging, chest imaging) as the opportunity for a start-up to break into these well-catered segments is negligible. This future wave of funding, as VC firms look to find the next stalwarts of medical imaging AI, could catalyse interest in tools targeting different clinical specialities or different regions. Tools for liver imaging, for example, could blossom, as drugs to manage fatty liver disease become increasingly available and backing from VC firms looking to capitalise is forthcoming. Additionally, the use of MR imaging as a first-line diagnostic imaging procedure for prostate cancer may create an opportunity for vendors with prostate imaging AI tools, a niche segment targeted by advanced visualisation incumbents today. The small wave of regulatory approvals for prostate AI solutions in the past 12-18 months may be indicative of this trend.

In the more immediate future however, funding in the US and Europe should continue its plateau, while funding in Asia is expected to continue to grow, with the country accounting for an ever-greater share of imaging AI funding. The size of these deals is also set to grow, albeit there will be fewer of them, as VC investment continues assist in the forging of medical imaging vendors. From this, vendors will be able to establish clear market leadership positions, and, assuming vendors live up to their own ambition drive significant revenues. At this point, the VC’s job will be complete, and the medical imaging AI market, established.

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Signify Premium Insight: Just Getting Started? Harrison.ai Raises $100m

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here.

In recent weeks Australian AI developer Harrison.ai joined an exclusive club. After securing AUD129m ($94m) in Series B funding, the outfit has become one of the handful of well-funded medical imaging AI vendors that have raised more than $100m.

The funding, which brings Harrison.ai’s total raised in the last two years to over $120m, was led by returning investor Horizons Ventures and also saw participation from Blackbird Ventures and Skip Capital. These investment firms were also joined by Sonic Healthcare and I-MED Radiology network two Australian providers which have deployed Harrison’s AI offering, lending the round an unusual level of consumer, as well as financial, weight.

Beyond merely investing in the firm, these provider partners will also help Harrison.ai target new areas of healthcare, with the vendor announcing plans to target pathology, among others.

The Signify View

As medical imaging AI success stories go, HeartFlow’s is hard to beat. As discussed in a previous Premium Insight when the heart health developer listed, it set a new financial benchmark. When it first launched on the New York Stock Exchange, the vendor had a pro forma enterprise value of $2.4bn, becoming medical imaging AI’s first unicorn.

Another of medical imaging AI’s financial flyers is Infervision. This Chinese vendor was itself the subject of a Premium Insight when it received $139m in Series D funding in July, bringing its total funding to more than $210m (despite an undisclosed Series C funding round).

Look back a few years however and these vendors’ series B funding rounds pale in comparison to Harrison.ai’s with Infervision securing $47m in 2018, while HeartFlow’s series B was only $20.4m in 2011. Of course, changing markets and changing VC strategies mean that these figures aren’t directly comparable to the nigh-on $100m that Harrison.ai has just secured for itself, but it does indicate the kind of rarefied company that the vendor is joining. It also begs the question of how such a sum has been achieved.

Comprehensive Valuation

There are a number of factors that have gone into establishing its valuation, but at the core is Harrison.ai’s central product, its Annalise.ai diagnostic imaging AI. Key to this product is its comprehensive approach to diagnostic radiology. Most solutions automatically identify a number of findings on an X-ray, but still rely on a radiologist to identify those not covered. AI vendors are addressing these gaps using various methods including partnering with other developers to add additional capability or creating platforms and bundling individual algorithms into suites which address particular clinical requirements.

Annalise.ai instead aims to ‘solve’ a particular scan type (its focus so far has been chest x-ray) and automatically identify all possible findings on any given image. So far, its solution identifies over 125 findings. In doing so it aims to make the selection, deployment and use of AI easier for providers. Further value could also be added to the solution in future as additional workflow tools are included, such as structured reporting, for example.

This approach looks to be effective, with the vendor’s own validation studies, which were published in The Lancet Digital Health in July, showing that radiologists assisted by the tool performed better in the vast majority of cases than those that weren’t assisted. What’s more the model’s AUC was also found to be statistically superior to unassisted radiologists for almost all findings.

Beyond published research, however, real world indications also show the value of the tools, with several providers choosing to use the tools in their own hospitals, including Sonic Healthcare, and I-MED, which have gone on to invest in Harrison’s Series B funding round. The fact that customers have quickly become investors is quite the endorsement.

The company’s ambitions, however, do not stop at chest x-ray, and they are looking to develop comprehensive solutions to other high turn-over scan types. In the long run, the company wants to address most of the high turnover scan types via its potential portfolio of comprehensive AI solutions. Early on, this was viewed as a potentially risky approach, such is the breadth of competition that has homed in on higher-volume scan types like chest X-ray. However, the comprehensive findings approach in a singular offering has allowed Harrison to stand-out from the crowd of aspirant vendors, most of which are offering a singular or a limited number of findings.

Ambitions in Pathology

The performance of Harrison’s radiology AI offering is only half the story, however, with the vendor’s stated ambition in pathology also having an impact on its prospects.

AI applications in pathology do, after all, hold significant potential, but the conditions for this potential to be realised are not yet in place. The most significant challenge is the general under adoption of digital pathology. However, this is starting to change with several factors such as regulation changes in the US, and the turbulence created by Covid-19 highlighting the lack of digitisation in pathology and giving impetus for change.

As these and other catalysts continue to grow in significance, the adoption of digital pathology will increase. As evidenced at RSNA, this is also a trend among imaging IT vendors which will increasingly incorporate pathology into enterprise imaging platforms. Against this backdrop, pathology AI will be able to find a footing.

The quantitative nature of many tasks in pathology as well as the shortage of pathologists (which is even more acute than the shortage of radiologists) means it is an opportune discipline for AI to have a significant impact, especially as the breadth and complexity of pathology diagnostic findings is a multitude higher than in radiology. This could be particularly true for a vendor such as Harrison, which has been especially thorough with its approach to its comprehensive chest X-ray solution. Frankly, singular point applications will have limited traction in pathology.

Cohesive Competence

Harrison.ai is looking to take this cohesive approach further, expanding out of radiology and addressing another slice of the diagnostic workflow. Longer term this digital pathology tool, the chest X-ray tool and potential future tools could all be integrated, leaving solutions that are more complete in both individual areas, but also along the entire workflow. This cohesion could be particularly useful in areas like oncology, as the broader remit of such solutions would see the vendor providing a service rather than a technology solution. This would enable it to prompt purchasing decisions to be made at a more executive level (e.g., C-suite), tapping into a larger budget pool. However, multi-disciplinary convergence in diagnosis is only just gaining traction in care settings, so in the near and mid-term, Harrison should remain focused on serving each individual diagnostic sector to ensure continued success.

The fact that Harrison is also looking to develop its pathology tool alongside recent customer Sonic is also an advantage. Data is obviously one of necessities for vendors looking to develop AI solutions, but, for pathology in particular, this data is scarce. By partnering with Sonic, Harrison will have access to an abundance of clinical data for algorithm training and refinement, as well as a large user base on which to conduct pilot deployments and validation studies. These are all essential for the successful development of a digital pathology AI tool, and having a route to achieve these already in place will give Harrison an edge over some of its competitors.

Looking to develop a pathology solution was also shrewd from a commercial, as well as a clinical, perspective. While increasing numbers of medical imaging AI vendors are securing ever higher funding rounds, pathology vendors have recently tended to fare better as investors have noted that a surge to adoption is pending, with for example Paige securing $100m in a series C round in January, and PathAI netting $165m for series C in July. This disparity is in part a result of the applicability of some solutions to drug discovery, a market which harbours the greatest returns near-term, but also relates to the relative upside of tackling a pathology market that is still heavily analogue and therefore ripe for disruption.

Of Value and of Worth

In receiving $94m in series B funding, Harrison AI has joined a very exclusive group of medical imaging AI vendors funded over $100m. What’s more impressive is that it has achieved this at an earlier stage than any of its peers. The road ahead is long, and the money will be quickly allocated to address its often quite expensive priorities. Continued commercialisation of its chest X-ray solution will be the first order of business; securing US-FDA regulatory approval and selling into and supporting providers will also require significant funds. Looking further ahead, investing in product development for comprehensive solutions that address other high volume scan types will undoubtedly follow. In pathology, Sonic will provide a short-term commercialisation base, but in the more analogue pathology sector, the firm will also have to take on a degree of market education and evangelism, a process that can have a substantial cash-burn rate.

If these priorities can be achieved, and Harrison.ai can begin generating sizable revenues, then the trajectory for future funding rounds and potential listings could be unprecedented. Moreover, the vendor could have a profound influence on the direction of AI. Many of Harrison’s peers are trying to add value in different ways, such partnering to create suites and developing end-to-end solutions that address entire clinical workflows. Harrison.ai offers another way, creating truly comprehensive solutions for specific use cases and then expanding into other adjacent areas. If the vendor is able to achieve commercial success on a par with its funding success, the developer will no doubt sit alongside HeartFlow as a posterchild of the segment. This could be particularly true if the vendor decides to list in the future.

There are, of course, challenges ahead. A lack of standardisation in pathology could make things harder than the DICOM-based world of radiology, while looking to split focus, as well as investment, between different areas, particularly when the vendor is still so young, could prove to be detrimental to both. Doubly so as it begins to compete with more established competition on both fronts.

These are proportionately minor worries, however. Harrison.ai has progressed carefully and methodically and to the pain of its competitive peers, very quickly. Now, bolstered by extra cash, and guided clinically by its customer partners, the precocious vendor is ready to demonstrate that its worth extends far beyond its valuation.

 

 

About Signify Premium Insights

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here