Hampleton’s newest Healthtech report makes for happy reading for founders in the industry. Not only have we observed a huge surge in investment for digital health companies, but – significantly – there’s been diversification on the part of venture capital.

Having shown understandable interest in telemedicine during the peak of the pandemic, when lockdowns made it imperative for healthcare systems to reach out to patients remotely, investors have since spread their wings and explored other parts of the healthtech ecosystem.

As noted in our report, companies developing AI healthcare software are highly sought after by investors. Such cognitive technologies were once squarely in the domain of science fiction, yet are now able to actively assess patients and make the lives of doctors and researchers a lot easier.

Let’s take a look at four fields where AI healthtech firms are changing the game.

The process of developing new medications has always presented big challenges. Finding and retaining patients for the painstaking trial process, marshalling the research, gathering large enough data sets – all of these facets can be hard to get right. 

Companies are providing ingenious AI solutions in order to accelerate the process and cut costs. A prominent example is San Francisco-based startup Unlearn.AI, whose technology creates ‘Digital Twins’ of real human subjects. A Digital Twin draws on AI modelling to show what would happen to a patient if they’d been given a placebo rather than the real medication.

The Twin is created after just one visit by the patient, with the software using baseline data to predict the progression of a disease. In other words, it removes the need for control cohorts, massively streamlining the trial process. The potential of the tech has been well recognised by investors, with Unlearn.AI announcing $50 million in Series B funding in April this year.

Another company making headway in clinical trials is PathAI, which applies machine learning to pathology analysis. This effectively removes the element of human subjectivity that can lead to incorrect assessments, allowing researchers to accurately chart the efficacy of their drugs. The Boston-based firm raised $165 million in Series C funding in May 2021.

While we’re still a way off from the sci-fi fantasy of robots or holograms replacing doctors, a number of companies have developed machine learning algorithms that can provide accurate diagnoses for a range of conditions.

In June of this year, Boston startup Elucid secured a $27 million Series B round. The windfall is helping the company to expand the reach of its AI-powered tech, which can diagnose heart disease long before it reaches its devastating conclusion. 

Elucid’s software is able to analyse CT images of artery walls, cross-referencing them with its database of existing tissue samples in order to assess the stability of plaques and predict the risk of a stroke or heart attack. The founder of MedTex Ventures, one of the backers of this latest funding round, is clearly a true believer in its potential, saying the company may be able to ‘finally stop heart disease in its tracks’.

Another firm to watch in this space is Aidoc, the Israel-based startup which in June

raised $110 million in Series D. The company’s AI can look over CT scans and X-rays to flag up any issues, dramatically speeding up the diagnostic process. At the time of writing, the AI has been used to evaluate almost 14 million scans, saving healthcare providers over 70 million minutes in work time. This is a much-needed resource, given that hospitals everywhere are dealing with staffing shortages and bottlenecked workloads.

Tackling mental health issues is one of the most pressing concerns of healthcare systems around the world, with the psychological fallout of lockdowns still being keenly felt. But can software algorithms really provide the kind of sensitive, nuanced care that many patients need?

The answer appears to be yes. In fact, automated systems like chatbots can provide distinct advantages over human therapists. They’re available right around-the-clock to people from all parts of society, including those who may struggle to access in-person help. They provide a safe space for patients who may feel trepidation about opening up to other human beings. And, since they’re available on mobile phones like any other app, such tools can normalise the idea of getting help for anxiety, depression and other mental health conditions.

One company eliminating barriers and providing equity in mental healthcare is Woebot Health. Its app provides patients with a ‘personal health ally’ – a smart AI presence you can chat to, and which provides guidance and strategic solutions based on cognitive behavioural therapy and interpersonal psychotherapy. The San Francisco healthtech company received a $9.5 million investment in March this year, following on from last year’s $90 million Series B round.

There’s been a lot of focus on AI’s potential to improve outcomes during pregnancy. Tech giants are getting involved, with Google announcing earlier this year that it would launch a hospital partnership to make ultrasounds more accessible through AI. The partnership will rest on technology that can record ultrasound scans in real time, as the wand is passed over a pregnant belly, and then assess images for signs of foetal abnormalities.

Meanwhile, French startup Sonio has already been applying AI in a similar fashion. The company, which received $5.2 million in investment in June, takes aim at a troubling statistic. Namely, that around 50% of birth defects don’t get detected by ultrasound. Sonio’s technology can diagnose issues by drawing not only the scans themselves, but on patients’ medical histories and genetic data. 

Being an SaaS solution that exists in the cloud, Sonio’s tech doesn’t require a complex installation process, and can be accessed from any computer or tablet. It underscores just versatile and agile AI solutions can be, allowing clinicians everywhere to reap the benefits of future-facing tech.