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Last week, imaging services provider RadNet announced it had acquired Dutch artificial intelligence developers Aidence and Quantib. Aidence is a radiology AI vendor which specialises in the development of clinical solutions for pulmonary nodule detection and lung cancer screening, while Quantib is an AI developer which, offers solutions for prostate cancer and neurodegeneration.
Aidence and Quantib will build on the AI capability RadNet acquired when it purchased Nulogix and DeepHealth in 2019 and 2020 respectively and leaves the American company with considerable potential in the field of cancer screening, an area in which RadNet will increasingly focus.
The Signify View
Many investors are impatient creatures. This impatience often serves them well, allowing them to spot a suitable opportunity and make a tidy return in a relatively short time frame. For the companies they invest in, however, this impatience can force them to alter and adapt their strategies, and ensure they must react to opportunities.
This flexibility is particularly important if a company is running at a loss of around $4-$5m dollars a year, against a figure of just $13m raised from venture capital investors. This is the situation that Aidence and Quantib found themselves in. Both vendors had developed promising AI technology but, with AI adoption in its infancy, commercialising and capitalising on this technology is still something of a challenge.
RadNet believes that in acquiring Aidence and Quantib, it will be able to address this issue. In combining Aidence and Quantib, with the AI capability it already possesses (via DeepHealth) as well as the extensive network of more than 290 outpatient radiology centres, the American provider believes it can create a powerful cancer screening network. It will also look to bolster the capability it has now assembled in breast, lung, and prostate, with colon cancer screening, to be able to offer a screening solution that detects around 70% of cancers that are imaging detectable at an early stage. Currently breast is the only cancer that is widely screened for, but RadNet’s strategy will see it increasingly push for greater levels of screening of these (and other) cancers, aiming to see them become as mainstream as breast screening. As this happens, RadNet will be able to leverage both its new and older acquisitions to be able to offer and deliver multi-cancer screening, capitalising on the comparatively vast numbers of patients that this would entail.
As a strategy this is shrewd, as offering screening is an additive rather than binary development. RadNet can, in the immediate term, use its breast AI tools for breast screening, offering lung and prostate scans as diagnostic clinical decision support tools, but, deriving increasingly greater proportions of revenue from them as these screening types become more common.
The fact that potentially vast numbers of patients will be imaged under screening programmes also reinforces RadNet’s decision to turn to AI tools. As a provider, RadNet will be competing with other outpatient imaging centres, as well as acute sites. This growing competition means that investments which give a provider such as RadNet even a slight competitive advantage will be worth considering. Bringing separate companies and their technology to create an efficient screening solution at present, when screening programmes outside of breast cancer are nascent, is somewhat speculative, but it will give RadNet an advantage, enabling it to drive forward and help create the market for such practices.
Even without the additional impetus given by screening programmes, prioritising the acquisition of AI capability is a sound strategy for RadNet. Both of RadNet’s latest acquisitions, but particularly Quantib’s solutions, are focused on time consuming medical imaging examinations. These involved examinations are comparatively expensive requiring large amounts of radiologist time. Radiologists are among RadNet’s most significant expense, with the provider, according to CEO Howard Berger, spending around 20% of its global net revenue on this resource.
AI solutions which streamline the reading workflow and enable radiologists to be more accurate and efficient, can represent a significant saving for the outpatient imaging provider, and therefore give it increased pricing flexibility and bolster its competitive credentials. This will both allow it to compete directly with other providers, as well as establish itself as an outsourcing option for larger providers for these highly time-consuming exams. If acute hospitals realise that an AI-equipped RadNet can perform and read imaging exams, take a share of the revenue, and still undercut acute centres, then those centres are likely to simply outsource some imaging procedures to them, rather than trying to compete with them on cost. This outsourcing looks particularly attractive for high volume and time-consuming examinations, such as brain MRI and prostate MRI exams.
Sold on Strategy?
One of the more unexpected aspects of RadNet’s acquisition of Aidence and Quantib is the provider stating its ambition to expand its presence both in North America and Western Europe, and positioning itself as an imaging IT and AI vendor as well as provider. RadNet intends to use its newly curated multi-cancer screening AI tools as a potential lead for its self-developed eRad products. This will prove a challenging task, with the imaging IT market increasingly saturated in mature regions making organic growth hard to come by. Most providers are already committed to lengthy deals with better established vendors, meaning that RadNet or other vendors eying a provider’s custom will, in most cases, have to wait several years before even having the opportunity to tender for their business. What’s more, providers are becoming less likely to “rip and replace” their existing imaging IT platform. Challenger vendors therefore need to present a significant value proposition that makes the time and cost a worthwhile investment for a provider.
RadNet, for its part, has pushed acquired centres to use its eRad products, regardless of the incumbent solutions or deal lengths. Although this has worked to date, it is less likely to translate to outside of outpatient imaging in international markets.
RadNet does have some advantages, though. As a provider itself, the AI solutions and eRad products will be used internally, and meet the company’s own need, as such, revenue brought in by the sale of the imaging IT software will, in the near term at least, be supplementary to RadNet’s core business. It is deriving another revenue stream, even if small, from already sunk cost.
If RadNet can bring its DeepHealth, Aidence and Quantib acquisitions successfully into a multi-cancer screening solution it could also hold a seriously advantageous position in the cancer screening market. While there are some AI developers that have focused on breast screening solutions, such as Volpara Health, RadNet will be among the first to offer a more broadly capable package targeting multiple cancers. This could put it in a particularly strong position if screening for other cancers becomes more common. Guidance around lung screening in particular is becoming more encouraging, with bodies broadening the criteria for which screening can be used and new studies (the latest taking place in France, funded by the Ministry of Health and the National Cancer Institute), all helping to build momentum for screening. RadNet’s position makes it look likely to capitalise on any rapid increase in screening, from both a vendor and a provider point of view. In fact, RadNet’s unique position may even enable to become a driving force for other cancer screening programmes beyond breast cancer to be adopted. However, whether it commits to such a plan highly depends on whether it has the appetite to champion such initiatives at a legislative level whilst growing its AI division.
A Matter of Timing
Although RadNet’s move to acquire Aidence and Quantib harbours some risk in that it is counting on cancer screening programmes growing in prevalence and becoming more widespread, it is a move that makes sense. The AI market is maturing and, as highlighted by MaxQ’s failure last month, developers that have been surviving off shrinking venture capital (especially in Europe), and which have failed to gain significant market traction will find themselves in increasingly precarious positions. RadNet has therefore chose an appropriate time to make such acquisitions. This timing will look particularly well-judged should the cancer screening market beyond breast cancer, take off as the provider expects.
In their decisions to sell, Aidence and Quantib also acted prudently. Their VC investors have enabled them to grow into companies harbouring competent, regulator approved solutions, but, on their own, both would face uphill battles trying to commercialise their solutions, a process that could be difficult to sustain given the losses they are making. To sell now allows the developers to, as part of a larger company, build on these foundations and become part of a more valuable whole.
Many AI developers that are finding further VC funding hard to come by, and watching their bank balances dwindle, will be hoping to be as fortunate. The AI market continues to move on, as it does, more companies will follow RadNet’s lead and decide it could well be the right time to jump on board.
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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