Is genAI the Prescription for Healthcare’s Biggest Problems?
Breega Watch #6 — Your Monthly Insider’s Guide to Tech Verticals. Why is this sector grabbing our attention ? Why now? What investment opportunities do we see arising ? This month, we’re exploring GenAI in Healthtech. Let’s dive in.
Crafted with 💚 & 🧠 by Paul-Adrien & Shim Young .
Why It Matters
In the UK, 63% of trainee doctors are at high or moderate risk of burnout, with emotional exhaustion reaching pandemic-era levels once again (GMC, 2024). Across the continent, doctors are drowning in admin: in Spain and the Netherlands, studies show that excessive reporting and paperwork are damaging morale and motivation, pulling clinicians away from care.
Add to that a chronic workforce shortage, highlighted by the World Health Organisation as a growing crisis across Europe.
The message is clear: healthcare systems need relief, fast. Today 79% of healthcare organizations use AI to some extent, transforming everything from patient care to drug discovery. If COVID-19 undoubtedly accelerated innovation and adoption, the groundwork was already being laid before.
Today’s major deals like Sanofi’s partnership with BioMap and French-startup Aqemia’s €31 million funding underscore how AI is now supercharging health innovation and this is merely a start.
GenAI’s Applications to Healthcare
Generative AI has demonstrated its potential to transform healthcare by increasing productivity for general practitioners (GPs), researchers, and healthcare institutions. Here’s where AI is already changing the space :
Patient Engagement: AI chatbots now handle routine medical queries, easing the load on GPs and offering primary care support, reducing the need for in-person consultations.
Drug Discovery: GenAI is revolutionizing drug discovery by predicting how molecules behave, speeding up the process of identifying new drug candidates. It has cut drug development timelines significantly(Bain).
Clinical Documentation: GenAI automates note-taking and regulatory compliance, saving doctors time on administrative tasks, freeing them to focus more on patient care(The Official Microsoft Blog)(Health Tech Solutions).
Care Decision Making: GenAI improves decision-making through advanced image analysis (e.g., X-rays) and symptom analysis
Healthcare-Specific LLMs: These models help avoid hallucinations and draw insights from unstructured medical data, enhancing AI’s reliability in healthcare settings.
Medical Publishing & Regulatory Support: GenAI boosts researchers’ productivity by automating compliance tasks and generating documentation for publication.
Let’s take a look into the GenAI in Healthtech Landscape
What does it take to succeed ? A bundle of Data, Distribution & Regulation
Make sure to keep a Human-in-the-loop: In Healthcare, GenAI tools must earn the trust and buy-in from clinicians and hospitals, whose current acceptance of AI-based treatments remains relatively low. Their involvement not only reassures patients but also ensures compliance : medical decisions can’t be based solely on AI models like large language models (LLMs) at this stage.
Data access and processing : Access to relevant, real-time, and continuously updated data is the lifeblood of GenAI companies. However, with the sensitive nature of patient information, the key challenge lies in determining which large language model (LLM) to use for processing: should it be a sovereign LLM, one that ensures maximum safety and security?
Direct proof of financial ROI for GPs/Hospitals : Clear, measurable financial ROI is essential for GPs and hospitals to prevent churn, especially in an environment where budgets are tight and non-essential tools are the first to go.
Distribution edge : Reaching healthcare professionals is challenging, but leveraging a mix of public and private partnerships can open doors to large contracts. A prime example of this is Doctolib’s national contract during the COVID-19 pandemic.”
Where We See the Most Promise at Breega
Drug discovery : GenAI is revolutionizing the process by predicting molecular structures and identifying promising treatments. According to BCG, it could cut early-stage discovery timelines by up to 70% and improve accuracy, reducing costly trial failures. For conditions like rare diseases, this could be a game-changer.
Research : GenAI is turning mountains of unstructured data : clinical trial results, medical records, and research papers into clear insights. By spotting patterns that humans might miss, GenAI is helping scientists uncover new treatment pathways faster. BCG says this data-driven precision can shave months off research timelines.
Patient experience : GenAI is creating more personalized, proactive healthcare. Smarter symptom checkers, tailored treatment plans, and digital health assistants are improving care while giving patients more control.
Overall Productivity : Automating admin tasks like documentation, claims processing, and scheduling can dramatically reduce admin burden and help staff focus on what matters most: caring for patients. BCG estimates these tools could boost productivity in hospitals and clinics by 20–30%.
We’re interested in meeting players in the space so reach out to pauladrien.marie@breega.com if you’re building a company in the space.
