FMAI Newsletter #1 2025

FMAI Newsletter #1 2025

As today marks ~5.75% of our way through 2025, I ( Harry Salt ) welcome you to our inaugural newsletter of the year! In this edition, you'll find some great highlights from across our platform, plus some recent headlines.

Firstly though, a warm welcome to those who are new to the FMAI community. Our last newsletter was 3 months ago, and since we've more than doubled our follower count!

Whether old or new to the platform, I encourage anyone to reach out about your interests across AI in health. I'd love to know what you'd like to see from us.

If you want to take things a step further and work on some content with us, whether an article on your area of interest or a video, please reach out via LinkedIn.

We're extremely passionate about making Future Medicine AI the best place to find the latest news, insights, and resources at the intersection of AI in Health. We've got a shed tonne of ideas for 2025 and some really exciting stuff to come. That being said, we're still growing and constantly looking to improve. So once again, let us know what you think needs changing.


Roundup | AI in Health/Medicine 2024

I started working on a 2024 roundup in mid-december. But things simply got so busy following GIANT Health Event , which itself was a big milestone for us (check out our highlights here). So here's a few thoughts and observations:

2024 Trends | LLM's, Multi-modality, & Open Source

Well large language models (LLM’s) largely laid the foundation for 2024, upon which we’ve seen the development of multimodal models incorporating images, video, and audio into their reasoning.

We’ve also seen a huge paradigm shift from closed systems to open models, which has largely been championed by Meta’s and its Llama LLMs. Notably, and more specific to the life sciences fields, Google DeepMind have since open sourced Alpha Fold 3 and Nvidia their BioNemo.?

Perhaps surprisingly to some, LLM’s remain largely vacant in frontline medicine. Well officially that is. We reported a story suggesting that one in five doctors are actually using these technologies in stealth.

However, AI has been making its way into clinical practise in the form of ‘ambient scribes’- audio transcription tools that curate appointments into summaries for clinicians. Indeed, workflow optimization currently remains the most popular integration of AI in healthcare, particularly for non-clinical purposes.?

Drug Discovery

AI made waves in the drug discovery space throughout 2024, and we've covered a load of it on the site if you want to learn more. While we're yet to see an generative AI drug make it to market, it's a prospect many pharma companies are betting big on, following trailblazers such as Insilico Medicine . They are a particularly interesting company we'll be keeping a close eye on in 2025.

What to Expect in 2025

  • Agents are the talk of the town at the moment. You'll see people talking about them everywhere. So what are they? In this great resource, IBM defines an agent as a "system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools." Anthropic 's computer use is perhaps the most prominent example of this. However, I'm yet to see any health specific uses of these, so let me know if you have.
  • Bigger and better LLM's are just around the corner. In the 12 Days of OpenAI, OpenAI demonstrated their next frontier model ChatGPT-4-o3, which is focused on more complex tasks. The applications of this model will likely be tailored far more towards developers and researchers. So it will be interesting to see how it's used in the health space. That being said, hallucinations remain a huge barrier to real world applications of LLM's in healthcare settings.

Ultimately, I think we're up for a rollercoaster ride in 2025, and there's more things to look out for than I have time to write about here. So my best advice is to stay tuned for more.


The Latest from Future Medicine AI— Expert Insights

New to Expert Insights? This is a video series of podcast-style conversations with thought leaders from the intersection of health and AI. In these videos, you will get a glimpse into what makes them tick as we discuss big picture topics and delve into the intricacies of their respective fields.

Navigating AI Regulation in Healthcare | Dr Hugh Harvey

From his journey as a radiologist to becoming a key figure in healthcare tech regulation, Dr. Harvey shares invaluable insights on bringing AI medical devices to market. Learn about the

Healthcare on the Brink: The Blue Pill of Bureaucracy or the Red Pill of Revolution? | Liam Cahill

Can AI help us reimagine healthcare in a way that serves humanity first? Or are we sleepwalking into a future where efficiency trumps empathy? ?? Find out in this enthralling Expert Insight with Liam Cahill as he delivers an unflinching exploration of the


Events

News and Developments


The U.S. Food and Drug Administration (FDA) released draft guidance on the use of AI in biological product and drug development, emphasizing model reliability and safety. This marks the agency’s second effort to provide specific AI-related recommendations, following earlier guidance for AI-enabled medical device providers, now focusing on its role in drug and biologic development.


The U.S. Chief Digital and Artificial Intelligence Office (CDAO) has finalized a crowdsourced pilot program to test the potential use of AI in military medicine. The initiative, called “Crowdsourced AI Red-Teaming (CAIRT) Assurance Program”, aimed to assist the Department of Defense (DoD) in exploring the applications of Large Language Models (LLMs) to enhance clinical note summarization and provide medical advice for the military.


NVIDIA has announced new collaborations with IQVIA, Illumina, Mayo Clinic, and Arc Institute to harness AI and accelerated computing in genomics, drug discovery, and healthcare services. This initiative aims to reshape the $10 trillion healthcare industry, powering solutions like AI-driven clinical trials, advanced genomic research, and robotic surgery.


Owkin, an end-to-end AI-biotech has announced Owkin K1.0 – a proprietary operating system for discovering new disease biology with the goal to become the first Artificial General Intelligence for biology.


VirtuDockDL is an automated deep-learning-based platform designed to streamline drug discovery. It combines molecular graph construction, Graph Neural Network modelling, virtual screening, and compound clustering, into a unified framework to identify potential drug candidates.


BCR-Net leverages vast amounts of partially labelled datasets rather than relying on a smaller amount of fully annotated data. This approach (weakly supervised learning) prioritizes the analysis of broader patterns over precise details, reducing the time and effort required for data preparation while maintaining high predictive accuracy.

Thank you for reading and stay tuned for more soon!

Harry Salt

Editor-in-chief

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