NXG in the FD: 'Why promising medical startups run out of money’

NXG in the FD: 'Why medical startups run out of money'
NXG in the FD: ‘Why medical startups run out of money’
The Financieele Dagblad highlights the funding challenges for Dutch medical startups that inhibits the startups to realize their potential. This requires us, as Peter Haasjes puts it in the article, to look for follow-up financing before we invest into a startup.
We note a mindset shift from gathering clinical data to later-stage market access and reimbursement, effectively resulting in increased interest for companies with revenue in the United States. The key reasons for this are:
1. The introduction of the MDR which makes obtaining a CE-mark for medical devices more difficult as the process is lengthy and less transparent compared to the FDA.
2. The differences in national reimbursement systems within the European Union.
3. The M&A landscape shift towards primarily acquiring revenue generating companies.
Despite the challenges, we see great potential as Europe has tremendous academic ecosystem that drives advancements in regenerative medicine, minimally invasive surgical technologies, and AI. These innovations promise to transform healthcare by extending life and improving efficiency.
Still, success requires a clear understanding of the reimbursement landscape, a strong ‘go-to-market’ strategy and solid plans for funding through sales or fundraising. We’re excited to engage with companies that align with this vision and discuss strategies to bring these technologies to life.
One thing is sure, the article drives engagement. Read the full article here.
EenVandaag: Attendi saves up to 20 minutes, saving valuable time for healthcare professionals

EenVandaag: Attendi saves up to 20 minutes, saving valuable time of healthcare professionals
Attendi
Back in 2023, through our second fund, we invested in Attendi, an innovative company that decreases the administrative burden for healthcare professionals. This allows tem to relocate their valuable time to client care. EenVandaag showcased the benefits of the solution on national television, displaying a day-to-day use. View the fragment below.
In the FD: 'Utrecht companies working on medical breakthrough: heart surgery via 'keyhole'’

In the FD: 'Utrecht companies working on medical breakthrough: heart surgery via 'keyhole'’
AMT Medical
Back in 2017, through our first fund, we invested in AMT Medical, a pioneering company creating an innovative heart bypass system technology to decrease the number of open heart surgeries.
Het Financieele Dagblad wrote an interesting article zooming in, amongst others, on the development path of the company, the challenges the company is solving and potential for acquisition. Read the full article here.
In the FD: 'Pension manager PGGM invests up to €100 million in new healthcare technology’

In the FD: 'Pension manager PGGM invests up to €100 million in new healthcare technology’
Momo Medical
Our recent co-investment with PGGM , UNETI Ventures, Center for Aging + Brain Health Innovation and others got listed in Het Financieele Dagblad. The article a.o. demonstrates Momo Medical’s unique capability to provide safety and save time in nursing homes by providing smart sensors that are placed under mattresses. The full article shows more details such as the 4.5 hour time saving per 90 nursing home inhabitants generated next to an illustration of its quick growth to adoption in 250 nursing homes. Read the full article here.
How a venture fund can contribute to responsible AI in healthcare

How a venture fund can contribute to responsible AI in healthcare
How can we responsibly apply artificial intelligence (AI) to improve our health? And how can an investment fund contribute to this? Read Peter Haasjes’ vision this topic in this article. As an investor, he’s focused not only on the technology itself but also on its practical applications. It’s crucial that innovation solves a real problem.
Considerations from an investor
We are a venture fund focused on investing in companies developing technology that can make healthcare more affordable and accessible. Increasingly, AI forms the foundation of this technology. We seek dual returns from our investments: both societal and financial. If customers and societal stakeholders, such as patients and insurers, don’t see value in the technology, it becomes difficult for the company to achieve profitability.
One of our partners, Noaber, invested in a company that uses patient data from hospital information systems (HIS) to estimate the risk of sepsis in patients. Studies show that around 6% of ICU patients experience sepsis, with mortality rates ranging from 28% to 55%. Early detection of sepsis allows for timely antibiotic treatment, significantly reducing mortality.
We have also invested in a company developing software that will improve the ability to predict whether immunotherapy will be effective for cancer patients. Immunotherapy can have serious side effects, and many immunotherapies benefit only a small subset of patients. This AI application, through techniques like massively parallel sequencing and subsequent data interpretation, can analyze whether a patient will respond to immunotherapy. If not, the treatment—and its side effects—can be stopped early. This more personalized approach to administering expensive medications can also help control healthcare costs.
Evaluating practical implications
When selecting companies to invest in, we look for solutions that meet practical needs. A company must be viable, meaning there must be a market for its technological solution. The technology must also contribute positively to healthcare, ideally at the same or reduced cost. However, we can’t always prevent a technological solution from increasing costs. We don’t control how customers use the technology we’ve invested in. If they treat the solution as an add-on rather than a core tool, there’s little we can do to change that.
We see many AI innovations designed to diagnose diseases or conditions. These are interesting for research purposes, but their practical implications aren’t always significant. For instance, a technology that detects early-stage dementia might be scientifically impressive, but with limited treatments for dementia, early detection has limited practical value. Additionally, few people visit their doctors suspecting early dementia, so the AI system lacks the necessary data to be truly effective.
There are many developments in AI, but often they are relevant to only a small group, limiting their broader impact. Scaling an innovative product is challenging and expensive. Scientific validation is required, and the entrepreneur must meet various standards to bring the product to market. From the outset, an entrepreneur must ask: What problem are we solving, and how large is this problem?
No AI revolution in healthcare yet
AI is particularly useful when analyzing large amounts of relatively homogeneous data, such as patient records for a specific condition. An algorithm can analyze thousands of patients based on a select number of characteristics—such as gender or inclusion criteria for a study—far better than a human can.
However, when it comes to diagnosing a single patient, such as one with a skin condition, AI can’t yet analyze every possible diagnosis and definitively conclude whether the patient has basal cell carcinoma, melanoma or another condition. AI might suggest the patient has melanoma, but that might not be the patient’s primary concern. The patient wants to know what’s wrong with their skin and what treatment options exist. When it comes to answering those specific questions, humans are still better than AI.
Challenges in changing healthcare processes
As investors, our team has learned that changing healthcare processes is difficult. This makes the acceptance of innovation a challenge. For instance, it was harder than expected to get mental healthcare professionals to adopt online modules, where parts of an intervention could be delivered through online course material. Despite technological possibilities, healthcare providers still prefer face-to-face conversations with their patients or clients.
AI applications automate small parts of healthcare processes. Step by step, they can improve healthcare by providing greater safety or saving time. A doctor will always remain responsible for the system’s output. They need to be able to trace how the system reached its conclusion. In five years, I believe radiologists will feel like they’re doing the same work as today. The technology will quietly be integrated into their workflows by the industry, but it won’t revolutionize their jobs.
This is an adjusted version of an article that first appeared in a blog series by the Rathenau Institute.