Bio-IT World Conference & Expo 2025
Introduction
Earlier this month, I had the opportunity to attend the 2025 Bio-IT World Conference & Expo at the Omni Boston Seaport. This was a new one for me - I have never attended Bio-IT World before - but, considering the increasing overlap of technology infrastructures with drug development, clinical research and clinical trials, we decided to give it a shot. As one of the life sciences industry’s most prominent gatherings at the intersection of biotech, data science, and AI, the event offered a unique perspective on where technology and early-stage research (and I mean, early stage) are headed. In this post, I’ll share key themes, conference highlights, and some thoughts on what those of you considering the conference — especially those in the clinical research space — should know before booking next year’s ticket.
Conference Overview
The 2025 Bio-IT World Conference & Expo centered around the themes of data, informatics and artificial intelligence in drug and device development, with a strong emphasis on early-stage research and drug discovery. Notably, the event steered clear of late phase clinical development topics, instead leaning into conversations about R&D systems, early drug candidate identification and selection including in-silico trials, and the role of AI in all of these systems, specifically agentive AI — a class of AI that acts autonomously to assist in tasks without constant human direction — and the imperative of keeping these technologies explainable and ethically grounded.
The crowd skewed technical: software developers, AI engineers, bioinformaticians, data scientists, and cloud infrastructure professionals. Most represented companies focused on drug discovery and preclinical innovation. Clinical phase representation was notably sparse.
A few standout sessions that I attended included:
Insilico Medicine’s plenary on leveraging GenAI in preclinical drug discovery.
BMS, who showcased internal AI-powered tools enhancing operational R&D workflows.
AbbVie, presenting its CONVERGENCE initiative—an ambitious project to aggregate decades of adverse event data for better safety forecasting.
The exhibition hall featured major players like Illumina, AWS, Snowflake, and Benchling, and there was a sizable poster section too, heavily emphasizing the validation of new LLM/Gen-AI models for discovery, prognosis prediction, and the like. There was a sizable pharma contingent in attendance, with representation from companies like Merck, Eli Lilly, Vertex, and AbbVie. Lab operations and AI-enabled R&D software companies were heavily present across booths and speaking tracks. The size—around a couple thousand attendees—felt energetic but not overwhelming, with about 100–120 exhibitors and a poster presentation area with about 40 posters (the actual numbers may have been slightly off, but this is certainly in the ballpark).
Networking was interwoven throughout the day with regular breaks and a well-attended evening reception which lasted a little over an hour. One offsite event I attended was an informal yet lively industry gathering at a nearby restaurant—complete with great conversations, good food, and even better energy. I didn’t really have any business to discuss with my fellow libationists, considering the gap in focus areas, but it was fun nonetheless. Despite the chilly April weather, Boston’s Seaport delivered plenty of nightlife options, with other companies hosting events at spots like Flightclub (a bar with high-tech dartboards for group events) and F1 Arcade (a racing simulator venue). All of these were within a short walk or ride-share ride from the main conference venue.
Ratings and Review
| Category | Rating | Commentary |
|---|---|---|
| Venue & Logistics | ★★★★☆ | The Omni was a well-suited space—convenient, modern, and walkable—but split levels made session-hopping a bit of a challenge. The Seaport area is only a 15 minute drive from Boston-Logan so that was nice, and the area has really expanded over the last few years, offering a plethora of lodging options if you want to save a buck staying in a (slightly) more economical hotel. However, Boston’s April chill makes one wish for warmer host cities this time of year, or at least a break from the overly-booked biotech conference city, for god’s sake. |
| Topics & Sessions | ★★★☆☆ | Overwhelmingly AI-focused with some redundancy across tracks. Excellent for early discovery teams, less relevant for clinical-phase professionals. Some of the talks were, in my opinion, overly technical. I recall at least a half-dozen slides with mind-boggling infrastructure maps, which went well over my head, and I would imagine, the heads of many others. |
| Attendee Profile | ★★★☆☆ | Largely technical roles with few senior clinical or operational decision-makers. Great for tech-oriented networking, less so for BD or clinical trial strategy. |
| Networking | ★★★★☆ | Ample breaks, receptions, and a well-integrated app (I used Swapcard). Attendee outreach was possible but yielded mixed response rates. There was plenty to do and plenty of people to see in the lobby between the sessions and after the main agenda ended in the evening. |
| Exhibition Space | ★★★★☆ | The exhibit hall was vibrant and energetic, with solid attendance and a well-sized poster area to peruse right outside the main expo area. Booth layout allowed for smooth traffic flow. The lanes were wide enough not to be bumping shoulders except in front of the most bustling booths during “expresso” hour. |
Key Takeaways, Insights, and Final Verdict
What Stood Out
Agentive AI and explainability are not just buzzwords—they’re critical to the next-gen R&D stack.
Companies are increasingly building internal platforms (like BMS and AbbVie) to gain proprietary advantages in data-driven research. Perhaps expectedly, most large companies seem to be building their own internal systems rather than going with pre-fab solutions.
Cloud partnerships (AWS, Snowflake) and integrated platforms (Benchling, Illumina) are foundational to modern R&D infrastructure.
For Clinical Research Professionals
This is not the ideal venue to meet clinical development or trial operations executives.
However, it’s likely a good fit if you’re exploring tech partners in AI, data integration, or discovery / preclinical decision-making support tools.
Plenty of opportunities to connect with innovative tech vendors and discovery teams at big and medium-sized pharma.
Would Sapiens Attend Again?
We likely would not attend again unless our client portfolio evolves to include discovery-stage or preclinical research initiatives. While the conference delivered value for those steeped in AI-powered R&D, the near-total absence of clinical trial decision-makers meant limited relevance for our current business development goals. If our focus expands upstream into drug discovery or platform partnerships, it could be worth revisiting with a clear tactical agenda.
