Tag Archives: Imogen Fitt

Signify Premium Insight: Pursuing Partners – GE’s Handshake with Elekta

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Last week GE Healthcare and Elekta announced that the two companies were collaborating in the field of radiation oncology, enabling them to offer providers a more joined-up offering across imaging and treatment for cancer patients in need of radiation therapy.

According to the vendors, the non-exclusive deal is set to combine GE Healthcare’s imaging solutions with Elekta’s radiation therapy solutions. This aligning of diagnosis and treatment is set to improve care the vendors say, enabling providers to more accurately determine the size, shape and characteristics of tumours, and subsequently target them with the most appropriate dose through advanced patient position, motion management and other technologies.

The Signify View

Bridging the gap between diagnostic imaging and therapeutics has the potential to be hugely beneficial to a vendor such as GE Healthcare. Just ask Siemens Healthineers CEO Bernd Montag, who in his company’s Q421 results highlighted that Siemens’ 2020 acquisition of Elekta rival Varian was already opening new sites, giving both the imaging and oncology teams “opportunities they wouldn’t have had before.” Siemens Healthineers’ partnership and later acquisition of Varian also shows such synergising is nothing new. Even for Elekta the partnership isn’t revolutionary, with the vendor already having an arguably closer relationship with Philips.

This path makes a lot of sense for GE Healthcare. Providers are increasingly looking to simplify their supply chains and, to an ever-greater degree, purchase medical imaging equipment on ever broader managed service contracts. By forging a partnership with Elekta, GE can better compete with the likes of Siemens, offering multi-year deals which cover both imaging and radiotherapy systems. In this regard, GE’s closer ties represent a defensive move, with the vendor’s bolstering of ties to Elekta particularly important given that Siemens’ acquisition of Varian increases its reliance on the company.

Integration Options

Beyond offering more holistic packages to meet providers’ changing procurement requirements, the collaboration between Elekta and GE Healthcare, or the collaboration between Philips and Elekta for that matter, also opens up possibilities for greater software integration. One of the obvious areas that collaboration could help is for tumour board software, allowing radiologists, pathologists and oncologists to work together more efficiently in order to better plan a patient’s treatment. Selling such tools as standalone packages is challenging, with vendors having to justify additional investment when basic functionality to support collaboration can be found in existing solutions, whether that is within the EMR or imaging IT platforms. Further, the value of such collaborative tools will only grow as imaging IT vendors increasingly develop and deploy fully featured multi-ology enterprise imaging platforms, with greater integration of digital pathology data, for example, further increasing their usefulness. Such tools can be made without a close link to an oncology vendor, but GE’s new partnership will streamline such processes.

Even with this ability, however, GE Healthcare’s partnership with Elekta is still more constrained than the Siemens Varian proposition because of the opportunities for synergising that the acquisition offers. Varian’s products can be further tailored to Siemens Healthineers’ medical imaging and imaging IT systems as these are the only systems that Varian’s tools work alongside. Conversely, Elekta must ensure that its offering is compatible with the products of GE Healthcare, Philips and any other vendor’s imaging equipment that a provider may choose.

Better to Buy?

With this being the case, it is fair to ask whether GE would have been better making a bid for Elekta, or whether it is in fact considering doing so in future, with the partnership one of the early stages in building a relationship. Such a deal would represent a major strategic play, and an expensive one at that; Siemens’ acquisition of Varian, for comparison, cost $16.4bn. It does, however, represent an intriguing prospect. Aside from the additional flexibility a combination of GE and Elekta or a combination of Philips and Elekta could offer, such a deal would also prevent a competitor from taking advantage on such synergies. A vendor looking to capitalise by focusing on the broader oncology pathway could find itself hamstrung if the two major radiotherapy players were committed to their respective owners.

Even without an acquisition from GE, Philips, which has a long and well-established relationship with Elekta, may stand to lose some of its influence. Elekta’s decision to bolster its relationship with GE suggests it may feel that it is not getting as much out of its partnership with Philips as possible. This could mean Elekta is ready to innovate and is increasingly planning to do so with GE. This will lead to closer ties to the American firm, which over time could leave Philips at a disadvantage in trying to secure large comprehensive deals with providers, at least from an oncology perspective. One of Philips’ strengths is in cardiology and cardiology interventional equipment. As such, the vendor could be more focused on realising growth from joining diagnostics and cardiology treatment than diagnostics and oncology, choosing another global health burden to specialise in. This could be especially true given that Siemens has effectively “doubled-down” on Oncology and Diagnostics. Philips does product software capability via its Intellispace Oncology offering in partnership with leading Oncology provider Dana-Farber, but the initiative has yet to drive substantial new demand.

Ultimately, GE’s partnership with Elekta will not bring about any immediate dramatic change. However, as vendors increasingly shift towards supporting condition-based care, providing complete solutions for the diagnosis and care of major global health issues, the move will put GE in a stronger position to compete going forwards, especially as it spins-off its corporate conglomerate parent in 2023. As highlighted in our recent Premium Insight The Fate of the Five, its acquisition and exploitation of Varian is one of the factors that has left Siemens Healthineers in the strongest position going into 2022. GE’s closing ties to Elekta, while potentially bad for Philips, will help the Boston-based firm fight on an equal footing.

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Signify Premium Insight: Grasping the Nettle in Digital Pathology

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Imogen Fitt
Market Analyst

“If an imaging IT vendor is going to enter the digital pathology market, now is the time to begin doing so,” emphasises Imogen Fitt, the co-author of Signify Research’s Digital Pathology – World – 2021 report. “Since the COVID-19 pandemic hit, the market has seen real momentum build, causing adoption to accelerate much more quickly than previously anticipated. Keeping track of market changes will be increasingly challenging for new entrants, so they need to arm themselves with as much information as possible. However, they also need to think about how they are going to approach the market.”

According to Fitt, there are several ways that a vendor could make this approach. One is the approach taken by Sectra, one of the more pioneering imaging IT vendors in exploring digital pathology. The Swedish vendor took it upon itself to develop its digital pathology solutions in house. This is a strategy that requires a lot of investment over a long period of time, and so represents a long-term commitment. A second approach sees imaging IT vendors acquiring digital pathology vendors, but this is expected to be a relatively unpopular approach.

“We haven’t seen many acquisitions, and while it is possible we could see more, I don’t think it’s likely,” she comments. “A lot of best of breed digital pathology vendors have grown quite considerably over the last few years thanks to the jump in the market. This makes acquisition quite costly compared to what it would have been a few years ago.

“It’s also a passion project for a lot of digital pathology vendors, so they have their sights set on the longer term. This isn’t true for all vendor types however, as  AI vendors for instance see the best route to market as becoming integrated into other solutions, and making acquisition an attractive exit strategy.”

Pathological Teamwork

The third approach an Imaging IT vendor could take is partnering with existing digital pathology vendors. This approach has been adopted by several firms including Fujifilm which has partnered with Inspirata. This, more cautious approach, allows imaging IT vendors to take advantage of digital pathology solutions and engage in enterprise imaging deal for lower levels of investment and commitment.

“We are expecting many more of these partnerships to come forward in the coming years,” comments Fitt, “at the moment this approach makes the most sense.”

“There is also one more approach currently being pursued by vendors in the digital pathology market which holds some promise,” she adds, “and that’s vertical solution integration, service provision.

“There are companies such as ContextVision which are evolving their digital pathology department into a laboratory service. Another company, Diagnexia, is a spin-off of a UK company called Deciphex, while Cyted.ai is another. This approach essentially capitalises on the acute deficit of pathology personnel that is available and offers outsourcing services, using the technologies that it, itself has developed.

“Partnering with those types of companies could be an interesting approach that would differentiate an imaging IT vendor, but I don’t really expect them to take it, because it requires a significant change to business models. Noticeably, none have yet done so in radiology.”

Pathology’s Uniqueness

While comparisons with radiology can be useful in some such situations, imaging IT vendors would do well to remember that despite some similarities, digital pathology is still a very different discipline, so what works in radiology will not necessarily have the same impact. One of the key differences, for example, is the comparative lack of digitalisation.

“Over 2020, the market grew enormously, by around 45%,” explains Fitt. “That was primarily down to shifts in working patterns, when remote diagnosis became necessary in the wake of the pandemic.”

There was a spike in 2020, but revenues are still experiencing healthy growth

“So, whereas the market was in a period of almost stasis, where digital pathology wasn’t really taking off, we are now in a period of unprecedented enthusiasm, engagement and investment.”

Despite this recent interest, parity has not yet been reached with other departments.

“Pathology operates in much more of a silo, and is typically much less well funded than radiology,” Fitt continues. “This gives key advantage to some imaging IT vendors when approaching these kinds of digitisation efforts, because, by offering an enterprise imaging deal which also includes pathology image storage, pathology departments can ‘piggyback’ of the larger budgets of radiology. Vendors focused solely on pathology don’t have access to that kind of advantage.”

There are other differences too. Chief among them is the levels of digitisation within pathology. Radiology is, in many markets, approaching 100 % digital maturity, however in pathology, that figure sits at around 15-20%. The lack of budget is one of the reasons for this low uptake, but another factor is that in radiology, the transition to digital often ultimately implied a cost saving. In pathology, where a slide still needs to be prepared pre-digitalisation, the cost saving component isn’t there. Making a case for adoption based on the return on investment has therefore been much more difficult.

Differences Within Pathology

An approach into digital pathology will also vary based on where in the digital pathology pathway vendors will target, with there being three broad areas. The first is primary diagnosis, in which pathology is supporting pathologists’ primary reading and reporting. There is secondary use, which includes clinical consult, tumour boards and medical education, and finally in preclinical use, in research, clinical trials and drug development.

“Approaching the preclinical research market and the primary and secondary clinical use markets is very different,” opines Fitt. “Vendors are approaching markets at very different phases of maturity with regards to many  trends.

“The research market is much more open to things like cloud storage and AI adoption, because there are fewer restrictions, such as only being able to use solutions that are CE marked or FDA approved. This has meant that there has been much greater adoption, particularly in fields like drug development.

“This is in contrast to the clinical markets, which saw most implementations starting from scratch, or a very low level of usage, with secondary reading much more common than primary. But, with the pandemic, primary use suddenly became much more attractive to pursue which has led to a number of vendors which are now entering the clinical market and pursuing primary reading capability.

“Over time,” she continued, “I expect secondary reading to evolve into more of a consultative or telepathology role, for tertiary hospitals, for example, or in less economically developed markets that need to outsource their staffing requirements.

“This will see deal sizes increase, but will also allow data to be centralised and be more usable. In addition, the preclinical submarket is starting to interact with the clinical world, with examples of projects looking at  companion diagnostics becoming much more common.”

Data Driver

Data is playing an increasingly important role in other ways too. AI is among the technologies set to have the most significant impact in digital pathology as it is beginning to also have in radiology and in other areas. There is some overlap, and some vendors are looking to target both markets, Harrison.ai for example announced its ambitions in pathology following its most recent funding round. However, capability isn’t as directly transferable as might be expected.

“One of the key things to remember, is that a radiology vendor would be approaching a completely different kind of market, where budgets are much smaller,” Fitt states.

“This begs the question of who will pay for it, and how is the cost justified? Regardless, before these questions can be answered, and before there can be any meaningful use of AI, pathology as a discipline needs to get its feet off the ground and become digitised.

“There are arguments that see the two go hand in hand, that the potential of AI will drive the digitalisation of pathology. Arguments centred on the workflow and making manual processes such as cell counting and measurements automated would help any cost savings become much more obvious.

“And while there may be an element of that, the question is still ultimately, ‘what is the real benefit of this AI?’, how does a vendor prove that it isn’t going to cost a provider more money that it saves them.

“That is a question that is yet to be sufficiently answered.”

The Time is Now

Digital pathology, as highlighted in our 2022 predictions Insight is destined to play a far more significant role in both the strategies of imaging IT vendors, as well as the purchasing decisions of providers. There are still many considerations that will have an impact on these facets, from file sizes that are magnitudes larger than many radiology images, to the lack of standardised image formats in digital pathology and the expensive up-front cost of many scanners, particularly compared to the budgets of pathology departments. These factors don’t exist in isolation either, with broader considerations like enterprise imaging strategies and cloud adoption strategies all intersecting the deployment and use of digital pathology.

“These are ancillary concerns, but they need to be considered before a provider buys in to a solution,” Fitt concludes. “The market is developing very quickly at the moment. It is a very interesting and engaging place. There are opportunities, but imaging IT vendors need to appreciate the differences compared with the radiology market and pay close attention if they are to keep up.”

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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