How to Invest for Success in Digital Pathology’s AI Ecosystem. Part Two.

Publication Date: 19/07/2023

Cranfield, UK, 24th July 2023 – Digital Pathology’s ecosystem will not support its AI vendors indefinitely. So how should investors and partners differentiate between players in today’s market?

There is an abundance of vendors currently developing their own products in the AI ecosystem for digital pathology (DP), and as I detailed in a previous article the market is simply not ready to sustain every vendor in operation indefinitely. Consolidation has already begun, note the recent acquisitions of Crosscope and KeenEye, yet new entrants are still expected over the next few years – keeping the market crowded.

Several vendors are also currently seeking investments and partnerships to help develop their businesses further. It can therefore be a challenge for third parties to navigate the AI ecosystem and successfully differentiate between vendors in a meaningful way.

At Signify Research, I’m due to publish our ‘AI in Digital Pathology’ deep dive, the second deliverable of our market intelligence service, at the end of this month. Further details can be found here.

Below is an excerpt of some of the key findings from this study, which may prove useful for prospective stakeholders looking to invest their time/money/reputation in DP AI.

Ultimately the question I am looking answer on behalf of these stakeholders is: how can stakeholders ensure that they invest in a solution that will be a success?

1. Understand How the Vendor is Planning to Approach its Ecosystem

Figure 3: Digital Pathology Ecosystem by Vendor Type. Note, this list is not exhaustive, merely intended to showcase examples of digital pathology vendors developing AI software.

The above diagram briefly outlines the many types of vendors currently developing their own DP AI algorithms. Note that many of these have existing partnerships with one another, and some are more proactive than others.

One of the key trends driving the general DP market forward today is interoperability – labs don’t want to be tied down/restricted to a single or select group of vendors. They want the freedom to be able to select any of the best-of-breed products as and when the requirement arises.

Therefore, each AI developer will need to make an important decision as they commercialise their products:

  • Will they integrate with other third-party platforms?
    • And will this strategy be pursued strategically or on an ad hoc basis?
  • Or will the vendor choose to develop its own platform to host in-house and third-party algorithms?

Both approaches have their own strengths and weaknesses, however what is clear is that there is no way forward that relies on one vendor as a silo.

On that note, I would encourage potential investors to examine their prospective investment’s partnership strategies closely, as the key to a successful algorithm is making it as widely available as possible.

2. Understand Vendor Types and their Respective Strengths and Weaknesses

As can be seen in Figure 1, I’ve divided the ecosystem into roughly 8 types of vendor, each with their own strengths, weaknesses, opportunities and threats. Table 1 below outlines these briefly and discusses the relative impact each is set to have on the DP AI market over the next few years.

Table 1: The different types of digital pathology AI (DP AI) vendor discussed.

As the table above shows, each type of vendor has unique advantages and potential disadvantages shaped by its background.

Whilst some of the lines between vendor types are blurring as the market evolves (think AI Incumbent/Image Analysis Specialists developing Image Management Software (IMS)), each will shape its strategy based on these strengths.

To thoroughly evaluate a vendor, investors and partners must understand the nuances of each company’s background and be informed how each will take advantage of its strengths and mitigate any disadvantages to win opportunity over similar competitors and other vendor types.

3. Understand Geographical Nuances

Other factors that may impact a company’s ability to successfully commercialise its product(s) include its location – as I alluded to in the last insight not all geographic markets offer equal opportunities. Some regions are already much more digitised than others, and thus are inherently more likely to adopt AI sooner.

So, I encourage you to ask:

  • Which markets are key to your partner’s early commercialisation strategy?
    • Is their domestic market one that will embrace home-grown AI expertise?
    • Or is the vendor situated in a market set to experience stagnated growth in the next five years?

If the last question is true, then a keen strategy to commercialise internationally must be in place, along with evidence that the vendor understands its core targeted markets.

Some customers such as those in Asia for example, typically prefer bundled purchasing to consolidate spending. Standalone AI vendors therefore may struggle to commercialise in these regions and should have a partnership/development plan in place to tackle this.

After all, it’s not always the quality of a product which dictates a company’s success.

4. Establish and Verify the Value in the Product

This point is perhaps the most obvious, however due to the complexity of pathological diagnosis, and the sheer number of algorithms and products in the market today, differentiating between products can be the hardest challenge.

The simplest way to evaluate the commercial prospects of a product is of course to speak to its users – this may not always be possible however.

Below, I have summarised a few of the core product types available today and added some of my thoughts on respective potentials:

A) AI for QC – Can be embedded on the scanner or be decision support AI utilised as a second-read ‘QC’ check for diagnosis. Whilst QC for scanners likely has the most potential to be widespread in the market (a significant amount of value can be derived from ensuring slides do not need to be re-scanned), it is also highly likely to become commoditised as a product. Standalone vendors therefore are higher risk as scanner vendors are also likely to be self-developing these capabilities which will be fine-tuned to their scanners and priced competitively.

AI for a ‘second-read’ in contrast, targets a subtle entry to the clinical lab intended to alleviate pathologists concerns. By not relying on an algorithm for diagnosis, and instead using it as a ‘double-look’ pathologists can both avoid having to QC check each other’s work and get to know the capabilities of AI in a more controlled way. It is imperative therefore that these solutions disrupt the pathologist’s workflow as little as possible until an alert is made.

B) AI for clinical diagnosis – there are many different types of solutions available in today’s market focusing on H&E, IHC and other types of stained slides. Breast and prostate cancer are by far the most common indications, and it will be integral to understand exactly how a vendor’s software differs to its competitors. Why have they chosen to develop these despite the competition? What comes next and why? Is the development process ad hoc or planned with partners?

Above all, AI must supplement pathologists’ workflow. If a pathologist can take one look at a slide and derive the same information an AI product is showcasing, what value does it really add? Solutions must be comprehensive and tackle enough of the workflow to make a difference to an individual’s everyday workload. Breadth of software (and choice) is also inherently tied to this but is something that will come with time.

C) AI for biomarker development/research –┬áMany AI vendors are engaging in projects with pharmaceutical companies to develop novel biomarkers for personalised medicine. These projects often involve some sort of CapEx fee to support the business until a CDx is developed. Development can take a long time but the business, if it performs well, will be supported by revenue from its partnerships. Lucrative royalties/volume-based pricing will then appear once a sufficient product has been developed. It’s likely that these types of vendors will see the most growth over the next five years as life science companies scale up their digital pathology initiatives.

Each type of product listed above possesses many sub-types, more than can be covered in a single insight. However, in summary, I’d advise prospective stakeholders to consider carefully whether a vendor’s unique selling point lies in their product – how is the AI different to what’s already offered? And does this difference matter to pathologists?

One of the ‘golden tickets’ in the industry will lie in validation studies centred on diagnostic and academic value. Some like Ibex Medical Analytics, Paige, etc.. are already participating in large studies, whilst others are years away from being able to say they have ‘proof’.

You can wait for vendors to reach this stage of maturity, risk less and earn less, or choose to enter the market at an earlier stage and potentially earn more over a longer period.

In summary, the digital pathology AI ecosystem is incredibly complex, like its discipline, and for an outsider to truly be able to invest wisely in the market there must be considerable time spent understanding the ecosystem in sufficient detail.

Signify Research has been following the digital pathology market since 2017, leveraging input from stakeholders, our expertise from adjacent healthcare technology markets, and infastructure databases to advise vendors, investors and healthcare systems as they shape their digital pathology strategies.

If you’d like to learn more about any of the vendor/product types I’ve listed I’d encourage you to reach out to discuss how our market intelligence reports can support your strategic planning – I can be contacted directly via, or alternatively click here to download our service brochure.

Related Research

Digital Pathology Market Intelligence Service – World – 2023

Signify Research’s Market Intelligence Service provides a rolling 12-month coverage of the global Digital Pathology market. The service is composed of four deliverables, as shown below.

This core market update, the first of four publications included as a part of the service, builds upon five years of previous research, and will enable you to:

  • Inform product investment and business strategy
  • Evaluate the ever-changing competitive landscape to assess the impact of associations and select potential partners
  • Acquire a holistic view of the nuances between different pathology research and clinical markets
  • Understand adjacent markets such as enterprise imaging, laboratory information systems and the influence these will have on Digital Pathology

For any further questions, or samples of the service contents, please contact the Imogen Fitt, the report author.

About Imogen Fitt

Imogen joined Signify in 2018 as part of the Healthcare IT team. She holds a 1st class Biomedical Sciences degree from the University of Warwick where her studies included molecular biology and pharmacology. Since joining the team Imogen has studied the medical imaging software and hardware markets and is now expanding Signify Research’s Diagnostics and Lifesciences coverage.

About the Diagnostics and Lifesciences Team

The Diagnostics and Lifesciences team provides market intelligence and detailed insights on the multiple healthcare technology markets where the clinical world intersects with the preclinical. Our areas of coverage include digital pathology, laboratory information systems, clinical Real-World Data (cRWD) platforms, oncology information systems, tumour board software, oncology decision support software and radiotherapy IT. Each report provides a data-centric and global outlook of its markets with granular country-level insights. Our research process blends primary data collected from in-depth interviews with healthcare professionals and technology vendors, to provide a balanced and objective view of the market.

About Signify Research

Signify Research provides healthtech market intelligence powered by data that you can trust. We blend insights collected from in-depth interviews with technology vendors and healthcare professionals with sales data reported to us by leading vendors to provide a complete and balanced view of the market trends. Our coverage areas are Medical Imaging, Clinical Care, Digital Health, Diagnostic and Lifesciences and Healthcare IT.

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