2026 ARCHIVES

Generative AI

Accelerate Research and Enterprise Innovation through Responsible GenAI Adoption at Scale

May 20 - 21, 2026

The Generative AI Track focuses on how life science organizations can move beyond pilots and embed GenAI as a durable, enterprise-wide capability that accelerates research, improves decision-making, and delivers measurable impact. Unlike the Generative AI Tools Symposium, which concentrates on how to build GenAI systems, this track centers on how to deploy, scale, and govern them responsibly across R&D, clinical operations, informatics, and enterprise IT. Across two days, leaders from biopharma, academia, and technology will share real-world case studies on future tech stacks, adaptive prompt frameworks, AI agents, RWD integration, multimodal foundation model tuning, and cross-functional AI adoption. Sessions highlight the organizational, regulatory, and scientific considerations required to achieve trust, compliance, transparency, and ROI when scaling GenAI across complex environments. Designed for executives, scientific leaders, and AI program owners, this track provides the playbooks, governance models, and strategic frameworks needed to transform GenAI from isolated proofs of concept into enterprise-scale accelerators for discovery, development, and clinical impact.

Tuesday, May 19

8:30 amRecommended Pre-Conference Workshops and Symposia*

On Tuesday, May 19, 2026, Cambridge Healthtech Institute is pleased to offer six pre-conference Workshops scheduled across two time slots (9:00 am–12:00 pm and 1:15–4:15 pm) and three Symposia from 8:30 am–3:45 pm. All are designed to be instructional, interactive, and provide in-depth information on a specific topic. They allow for one-on-one interaction and provide a great way to explain more technical aspects that would otherwise not be covered during the main conference tracks that take place Wednesday–Thursday.

*Separate registration required. Additional details:

Symposia: www.bio-itworldexpo.com/symposia

Workshops: www.bio-itworldexpo.com/workshops

4:30 pm

Grab Your Seat! 25th Annual Golden Ticket Prize Giveaway & Organizer’s Remarks*

Cindy Crowninshield, Executive Event Director, Cambridge Healthtech Institute

*Must be present to win.

4:35 pm

Welcome Remarks from the City of Boston and the Office of Mayor Michelle Wu

Donald Wright, Interim Chief, Economic Opportunity & Inclusion Cabinet, City of Boston

4:40 pm PLENARY KEYNOTE INTRODUCTION:

Getting Ready for Effective AI: Starting with FAIR Principles

Diana Gamez Diaz, Head, Data & AI Engineering, RCH Solutions

4:50 pm PLENARY KEYNOTE PRESENTATION:

Rare Conversations: Explorations of the Research, Funding, and Advocacy for Rare Diseases

Thomas Bartlett, Ambassador, MG Uniter Myasthenia Gravis, Amgen

Catherine Brownstein, PhD, Manager, Molecular Genomics Core Facility, Boston Children's Hospital; Scientific Director, Manton Center for Orphan Disease Research Gene Discovery Core; Assistant Professor, Harvard Medical School

Morgan Cheatham, MD, Partner, Head of Healthcare & Life Sciences, Breyer Capital

Sebastien Lefebvre, Head of Technology, Data and AI, Aurelis Insights

Dylan V. Livingston, Founder and President, The Alliance for Longevity Initiatives (A4LI)

William Van Etten, PhD, Co-Founder, CEO & Principal Scientist, StarfleetBio

Susan J. Ward, PhD, Founder & Executive Director, cTAP

In a unique plenary series of intimate conversations, we will explore the models, drivers, and challenges facing rare disease research. By uniting leaders in precision medicine, bioinformatics, national rare-disease infrastructure, and real-world legislative advocacy, we will give attendees an expansive, cross-disciplinary view of what’s required to deliver faster, more accurate, and more equitable rare-disease cures.

6:00 pmWelcome Reception & 25th Anniversary Celebration in the Exhibit Hall with Poster Viewing

The Bio-IT Kickoff Reception is a reunion, reconnect with friends, explore cutting-edge research, and celebrate innovation! This year, join us in celebrating the 25th Anniversary of Bio-IT World Conference & Expo with cake and champagne as we mark a quarter century of advancing science and technology. Enjoy poster presentations, networking, and vote for the Best of Show and Poster awards.

7:15 pmClose of Day

Wednesday, May 20

6:30 amBio-IT World’s 5K Rise and Shine Fun Run! (Sponsorship Opportunities Available)

RUN COORDINATORS:
Bridget Kotelly, Senior Conference Director, Cambridge Healthtech Institute
Eileen Murphy, Conference Producer, Cambridge Healthtech Institute

Lace up and join Bio-IT’s Coordinators for the Fun Run on Wednesday, May 20! Sprint, jog, walk, or talk-your-way-through—ALL abilities are welcome. This informal event is all about getting moving together. Full details to come…just don’t forget your sneakers!

7:00 amRegistration and Morning Coffee

8:00 am

Grab Your Seat! 25th Annual Golden Ticket Prize Giveaway & Organizer’s Remarks*

Allison Proffitt, Editorial Director, Bio-IT World and Clinical Research News

*Must be present to win.

8:05 am PLENARY KEYNOTE INTRODUCTION:

From Tools to AI Teammates: How AI-Driven Scientific Workbenches Can Redefine the Scientist User Experience

Sayan Lahiri, Vice President, CLOVERTEX

Life sciences R&D is drowning in powerful tools, massive data, and advanced infrastructure—yet scientists still spend too much time managing environments, rerunning workflows, and navigating fragmented systems. The real bottleneck is no longer data or compute; it is the scientist’s user experience. In this plenary, we explore how Clovertex’s AI-driven scientific workbench called NUMEN is changing the role of technology from passive infrastructure to an active scientific collaborator. By embedding AI directly into the workbench, these platforms guide scientists in choosing the right compute, optimizing cost, enforcing reproducibility, tracking metadata, and scaling experiments seamlessly from exploration to production—all while governance and security remain invisible. AI-powered workbenches create a shared operating model where science moves faster, results are trusted, and innovation scales. The future of life sciences R&D will not be defined by more tools—but by intelligent platforms that work like a teammate alongside scientists.

8:15 am PLENARY KEYNOTE PRESENTATION:

The Collaboration Breakthrough: How Federated Learning Is Rewriting the Rules of Drug Discovery

Mohammed AlQuraishi, PhD, Assistant Professor, Systems Biology, Columbia University

Jonathan B. Gilbert, PhD, Senior Director, Ecosystem Growth and Contributor Partnerships, Eli Lilly and Company

José-Tomás Prieto, PhD, Director of AI Programs, Apheris

Woody Sherman, PhD, Founder and Chief Innovation Officer, PsiThera

Christina Taylor, PhD, Senior Science Fellow and Computational Molecular Design Lead, Bayer

Arman Zaribafiyan, PhD, Head of Strategic Alliances, AI Simulation, SandboxAQ

The pharmaceutical industry sits on a collective treasure trove of proprietary structural biology data, yet competitive concerns have historically prevented the data sharing necessary to train the most powerful AI models for drug discovery. Federated learning is changing this paradigm, enabling biopharma companies to collaborate on AI model training while keeping sensitive data secure and confidential. This plenary session explores the groundbreaking AI Structural Biology (AISB) Network, where industry leaders are pooling proprietary protein-ligand structure data to collaboratively train OpenFold3, an AI model designed to predict molecular interactions with precision approaching X-ray crystallography. Through the federated computing platform, thousands of experimentally determined protein–small molecule structures remain securely at their original locations while contributing to a shared learning framework that no single organization could achieve alone. This session reveals how federated learning solves the industry's most persistent challenge: unlocking collective intelligence while protecting intellectual property. Attendees will hear directly from consortium leaders about:

The technical architecture enabling privacy-preserving collaborative AI training across competing organizations
Real-world implementation of federated learning platforms and computational governance frameworks
Strategic rationale for industry collaboration: why sharing model training beats going it alone
Impact and outcomes from early OpenFold3 results in predicting binding affinities and accelerating small molecule discovery
The future of collaborative AI in biopharma, from structural biology to clinical development

9:30 amCoffee Break in the Exhibit Hall with Poster Viewing (Sponsorship Opportunity Available)

Start your morning with coffee, connections, and cutting-edge research! Enjoy poster presentations, network in the Exhibit Hall, vote for awards, and a chance at a fabulous raffle prize!

10:15 am

Organizer's Welcome Remarks

Erin Kadelski, Associate Project Manager, Production, Cambridge Innovation Institute

10:20 am Chairperson's Remarks

Alex Madama, DO, Hewlett Packard Enterprise

10:25 am

Flashes to Flames: Predicting the Future Technology Stack

Vinod Das, Associate Director, Pharma R&D, Drug Innovation and AI Enablement, Bayer Pharmaceuticals

Generative AI has rapidly evolved from experimental flashes of innovation into a blazing force reshaping the technological landscape. As the flames of GenAI spread, the future tech stack will be defined by hybrid architectures that blend foundation models, agentic AI, knowledge graphs, and domain-specific autopilots. Together with advances in federated learning, memory systems and compute infrastructure, these approaches will amplify human creativity, accelerate decision-making, and unlock collaborative innovation across the life sciences.

10:55 am

Harnessing Generative AI to Transform Real-World Data into Actionable Evidence for Pharma R&D

Anu Sharma, Senior Principal Scientist, MRL BARDS Epidemiology RWE Capabilities and Analytics, Merck & Co., Inc.

In today’s evolving healthcare landscape, Real-World Data (RWD) and advanced analytics are increasingly shaping pharmaceutical research and development. This session introduces Merck’s Real-World Data Exchange (RWDEx) platform and its use of generative-AI–enabled workflows to support evidence synthesis, regulatory awareness, and scalable analytics. Through applied case studies, attendees will learn how these approaches help streamline study execution, reduce data fragmentation, and support more timely, data-informed decision-making across the R&D lifecycle.

11:25 am

Strategy Considerations for AI Agents in Drug Discovery for a Rapidly Evolving Ecosystem

Peng Cheng Zhang, PhD, Technical Associate Director Scientific Products, Integrated Data and Insights/SDP/NX, Novartis Institutes for BioMedical Research, Inc.

In a rapidly evolving technology landscape for drug discovery, AI agents or agentic systems present new strategic opportunities and challenges. This talk highlights several key strategic considerations—platform agility, proprietary data, and physical-world validation loops. I share some perspective on a balanced approach for efficiency and innovation, and why integration first thinking is essential for navigating emerging opportunities in this dynamic landscape.

11:55 am

Beyond the Pilot: Enterprise AI for Faster, Smarter Drug Development

Nirav A. Mehta, Life Sciences R&D Digital and AI Innovation Leader, Deloitte

Jennifer G. Rola, Director, Data & Analytics Engineering Lead, Pfizer Inc.

Mark Lee, Industry Ecosystem GTM, HLS, Databricks Inc

Sriram Krishnamurthy, Director, GD-IT, Regeneron Pharmaceuticals, Inc.

AI is reshaping drug development from study design through clinical operations, safety, regulatory, and medical affairs—unlocking faster cycle times, better decisions, and greater throughput when paired with strong data foundations and human oversight. This panel will explore how biopharma leaders are moving beyond isolated pilots to enterprise-scale transformation through AI, automation, and agentic workflows. Panelists will discuss where value is emerging now and which capabilities are required to scale responsibly while balancing innovation and workforce evolution to accelerate outcomes.

12:25 pm

Applying AI-Driven Mechanistic Biosimulation Decision-Making into Drug Discovery

Leif Pedersen, President, Certara

This session explores how PBPK/QSP, machine learning, and integrated data workflows can bring model-informed drug development into the DMTA cycle, helping teams translate in vitro and in silico signals into first-in-human dose, DDI, formulation, safety, and candidate-selection decisions. Through industry case studies and Certara’s evolving MIDD platform, attendees will see how AI-driven mechanistic models can automate high-throughput prediction, bridge discovery and clinical teams, and support smarter go/no-go decisions.

12:55 pmTransition to Lunch

1:05 pm

LUNCHEON PRESENTATION: Interoperable AI Ecosystems: Modernizing Biomarker, Sample, and Clinical Workflows

Tobias Guennel, PhD, CTO & Co-Founder, QuartzBio

Clinical trials increasingly rely on harmonizing multimodal data from diverse systems and stakeholders. We’ll demonstrate how QuartzBio’s platform uses domain‑specific AI agents to automate interoperability, unify ontologies, and streamline data flow across the R&D lifecycle. These coordinated agent networks improve data quality, reduce manual effort, accelerate operational and scientific decisions, and empower subject matter experts to focus on strategic, high‑impact work.

1:35 pmRefreshment Break in the Exhibit Hall with Poster Viewing (Sponsorship Opportunity Available)

Bio-IT's hall is bigger than ever; one break won’t cut it! Enjoy dessert and coffee after lunch, explore booths and posters, vote for awards, and participate in our raffle for a chance to win a prize!

2:25 pm

Chairperson's Remarks

Jack DiGiovanna, PhD, Independent Advisor

2:30 pm

The State of AI Prompting: How We Talk to AI Today and What Comes Next

Vinod Das, Associate Director, Pharma R&D, Drug Innovation and AI Enablement, Bayer Pharmaceuticals

Pearson Henri, Forward Deployed Engineer, OpenAI

Etai Jacob, PhD, Head of Applied Data Science and AI, Oncology R&D, AstraZeneca

NAVI, Adaptive Prompting GenAI Agent, NAVI Autonomous Systems, Physical AI, Conversational AI

Neha Tadimeti, Product Manager, Nvidia

Generative AI is rapidly transforming pharmaceutical landscape, and prompting is becoming more than just a way to interact with models. It is emerging as a driving force behind innovation, accuracy, speed, and computational costs. As language models demand significant data center resources, even small changes in how we prompt can influence performance, sustainability goals, and associated expenses. This session explores how evolving prompt strategies and architectures are reshaping everything from drug discovery to clinical documentation and scientific decision-making.

The session will feature NAVI, a Physical AI companion robot assembled and personalized by Vinod Das, with custom skills and memory designed to demonstrate human < > AI interaction beyond software and screens. NAVI illustrates how prompt design and voice based prompting influence real world AI usability, interactive prompting literacy, and efficiency gains.

Speakers will discuss how self-correcting prompt systems can improve reliability by refining outputs in real time. The conversation will also explore the surprising value of hallucinations, showing how unexpected or creative outputs can spark new scientific ideas while highlighting strategies to manage risks responsibly in high-stakes environments. The session will also spotlight the rising role of voice-based prompting, from hands-free lab workflows to natural, spoken interactions with intelligent agents. This evolutionary shift makes generative AI more accessible and impactful across all roles in pharma, including research, regulatory, and commercial teams. Whether you work at the bench, manage data, or shape strategy, this session offers practical insights into how modern prompting techniques can elevate your everyday work and unlock deeper value from AI.

3:30 pm

Innovation Showcase—Emerging Solutions for Life Sciences (NEW)

Cindy Crowninshield, Executive Event Director, Cambridge Healthtech Institute

The Innovation Showcase offers emerging companies (pre-commercial; founded in 2020 or later; focused on life sciences, pharma, clinical research, healthcare, or informatics/tech; and currently raising a late seed or Series A) an alternative to a traditional sponsored talk. This curated, in-track session features lightning talks and demos from startups developing tools for discovery, development, and clinical research, highlighting novel approaches, architectures, and deployment models. To discuss participation, contact Cindy Crowninshield at [email protected].

3:35 pm

INNOVATION SHOWCASE:

Agentic AI Activated: From Proof of Concept to Enterprise Impact

Gaugarin Oliver, CEO, MadeAi, Inc.

As agentic AI moves from concept to execution, identifying where it delivers real value is critical. In this lightning session, CapeStart showcases MadeAi, an agentic AI platform developed with top pharma, highlighting its architecture, rapid deployment, and workflow orchestration. Through a live proof of concept, learn how high-impact use cases are identified, activated, and scaled across clinical, commercial, and real-world workflows.

3:40 pm

INNOVATION SHOWCASE:

An Agentic AI Platform for Workflow Automation in Biopharma

Martin Bittner, CEO, Redouble AI

Agentic AI holds significant promise for biopharma companies, but implementing secure AI solutions beyond pilots, in actual production, is often challenging. Redouble AI has developed a novel, Java-native Agentic AI platform for biopharma, designed to enable the rapid development and deployment of secure agentic workflows in production. The talk will present the framework as well as several case studies highlighting successful deployments for automation of complex data and document workflows from discovery to clinical trials, manufacturing, and regulatory documentation.

3:45 pm

INNOVATION SHOWCASE:

From Perturbation Data to Mechanistic Insights: Unlocking Genetic and Chemical Signals at Scale with protoXell

Tri Le, Chief Product Officer, DataXight

This talk introduces protoXell, the first point-and-click software that enables translational scientists to explore and compare chemical and genetic perturbations at scale. By combining a curated perturbation catalog with AI-powered interpretation, protoXell enables researchers to uncover mechanisms of action and generate hypotheses for target discovery and drug repurposing, without requiring computational expertise. The software supports both public and proprietary data and is designed for integration with downstream analytical workflows, including AI-driven models and virtual cell systems.

3:50 pm

INNOVATION SHOWCASE:

Unlocking Agentic AI in Life Sciences with Memory and Context

Ali Brocato, CEO, Co-Founder, Beakr

AI in life sciences will not be unlocked by better models alone, but by systems that retain memory and preserve context across people, space, and time. In research, the most valuable knowledge is rarely a single dataset. It's the history of what was tried, what failed, why decisions were made, and the connections that only emerge when fragmented work is brought together. This talk explores why that layer is essential for agentic AI, and how Beakr is building it to accelerate scientific discovery.

3:55 pm

Q&A with Innovation Showcase Speakers

Jack DiGiovanna, PhD, Independent Advisor

4:00 pm

The AI Your Science Deserves: Orchestrating AI Agents across the Enterprise

Jason Hillenbach, Director, Life Sciences Industry Partner GTM Lead, ServiceNow

Sean Mcdonough, Senior Solution Sales Executive, ServiceNow

Life sciences organizations are scaling AI fast—agents running across IT operations, clinical workflows, manufacturing, and enterprise services. But as deployments grow from a few pilots to hundreds of autonomous tools, a critical gap appears: orchestration.

Most enterprises have no unified way to see which agents are running, what data they're accessing, how they interact, or whether they're delivering value. The result is agent sprawl—duplicated efforts, untracked decisions, security blind spots, and no clear picture of AI's business impact. This session introduces ServiceNow's answer: enterprise AI agent orchestration. A platform where agents don't just execute tasks—they're inventoried, governed, measured, and monitored from a single AI control tower.

4:30 pmBest of Show Awards Reception in the Exhibit Hall with Poster Viewing

Unwind with colleagues at our lively reception! Explore posters, vote for the best, network with exhibitors, enjoy a drink, and try to win a raffle prize. Celebrate Best of Show winners!

5:45 pmClose of Day

Thursday, May 21

7:00 amRegistration Open

7:00 amConnect & Collaborate: Breakfast Networking Roundtables (Sponsorship Opportunities Available)

Start the day with small-group roundtable discussions designed to spark collaboration and exchange insights across the Bio-IT community. Attendees join themed tables—spanning AI, data ecosystems, foundational models, and more—for focused, peer-driven discussions that foster problem-solving, connection, and cross-functional perspectives ahead of the plenary keynote.

IN-PERSON ONLY –

TABLE 1: Knowledge Graphs

Tom Plasterer, PhD, CEO & Co-Founder, Knowledge3

How are knowledge graphs supporting reliable scientific intelligence
Lessons from early deployments
Remaining challenges and barriers to scale

IN-PERSON ONLY –

TABLE 2: From Molecules to Qubits: A Collaborative Conversation on Pharma’s Quantum Future

Christopher Bishop, Chief Reinvention Officer, Improvising Careers

Learn how leading global pharma companies are applying quantum principles to real-world research.
Discover the quantum companies transforming traditional processes around drug development and drug discovery.
Discuss how quantum, along with HPC and AI, is poised to help researchers tackle historically intractable problems and potentially find new treatments for diseases like cancer, Alzheimer’s, and diabetes.

IN-PERSON ONLY –

TABLE 3: From AI Tools to Autonomous Discovery: Are We Ready for Agentic AI in Drug Discovery?

Parthiban Srinivasan, PhD, Professor and Director, Centre for AI in Medicine, Vinayaka Mission's Research Foundation, India

Where are we today? Are AI tools truly integrated into workflows, or still operating in silos?
What changes with agents? How do LLM-based agents shift drug discovery from prediction to decision-making?
What is blocking autonomy? Data quality, validation, trust, or organizational readiness for AI-driven discovery?

IN-PERSON ONLY –

TABLE 4: Bridging Tech Transfer and Industry: Unlocking Real Collaboration at Bio-IT

Nancy Wetherbee, Director Commercialization, Research Innovation Center, Northeastern University

Where are the highest-value collaboration opportunities between academia/TTOs and industry (biopharma, startups, AI/data, investors), and what makes them actually work?
What types of partnerships are most effective in practice (licensing, co-development, startup creation, sponsored research), and how do both sides evaluate quality and fit quickly?
What specific formats, access points, or structures at the Bio-IT event would actually drive follow-up, partnerships, and deal-making?

IN-PERSON ONLY –

TABLE 5: Supporting Innovation While Managing Risk: The CIO’s Dilemma in AI-Driven R&D

Chris Dwan, Fractional CIO, Triveni Bio

How do CIOs enable rapid AI and data innovation without breaking governance, compliance, or data integrity frameworks?
What separates pilot-stage innovation from scalable, production-grade systems? Where do most organizations fail?
How do leaders manage emerging risks (model bias, data provenance, regulatory exposure) while still pushing competitive advantage?

IN-PERSON ONLY –

TABLE 6: Real-World Data and Evidence: Unlocking Value Beyond Clinical Trials

Michael Liebman, PhD, Managing Director, IPQ Analytics, LLC

How real-world data is being used alongside clinical and experimental data
Challenges in standardization, access, and regulatory acceptance
Opportunities to improve outcomes, access, and long-term patient insights

IN-PERSON ONLY –

TABLE 7: Beyond Data Management: Why AI Fails without Institutional Memory in Life Sciences

Alexandra Brocato, CEO & Co-Founder, Beakr, Inc.

Why critical experimental knowledge is lost across ELNs, LIMS, and siloed teams, and the cost of reinventing work
How structured experimental memory makes past decisions, failures, and context reusable across teams
How organizations can make scientific knowledge reusable for both humans and AI

IN-PERSON ONLY –

TABLE 8: Intellectual Property in Biotech: Strategy, Patents, and Trademarks

Elizabeth F. Jackson, Acting Director, Northeast Regional Outreach Office, U.S. Patent and Trademark Office

How to think strategically about IP early in biotech and AI-driven research
Common pitfalls in patent and trademark applications and how to avoid them
Navigating ownership, protection, and commercialization of innovations

IN-PERSON ONLY –

TABLE 9: Are Bioinformatics Workflows Broken? Rethinking Pipelines in the Age of No-Code and AI

Daniel Clarke, Biomedical Software Developer, Icahn School of Medicine at Mount Sinai

Why do current workflow systems fail most scientists in practice?
Can no-code and AI-driven workflows meet standards for reproducibility, validation, and clinical readiness?
What would a “production-ready” workflow ecosystem actually look like across teams and organizations?

IN-PERSON ONLY –

TABLE 10: Data Readiness for AI: Why Most AI Programs Fail Before They Start

Bahador Marzban, PhD, Principal Data Scientist, Innovative Medicine R&D, Johnson & Johnson

The gap between AI ambition and the reality of data foundations, platforms, and operating models
What “AI‑ready data” actually means in practice—beyond pilots, dashboards, and proofs of concept
Where AI initiatives most often break down: data integration, data quality, metadata, and governance at scale

8:00 am

Grab Your Seat! 25th Annual Golden Ticket Prize Giveaway & Organizer’s Remarks*

Cindy Crowninshield, Executive Event Director, Cambridge Healthtech Institute

*Must be present to win.

8:05 am

Bio-IT World 2026 Innovative Practices Awards Ceremony (Winners Announced)

Allison Proffitt, Editorial Director, Bio-IT World and Clinical Research News

Since 2003, Bio-IT World’s Innovative Practices Awards have recognized outstanding technology innovation advancing life sciences research. The 2026 winners highlight excellence in open science, patient advocacy, global data access, and real-world AI through collaborations involving Arizona State University and Starfish Storage, CareDx, ASAP Discovery Consortium, and Novartis with Genedata AG. Together, these projects illustrate the modern R&D data lifecycle, from unlocking legacy data to enabling collaboration and driving clinical decision-making.

8:25 am

Bio-IT World 2026 Emerging Innovator Award—NEW (Winner Announced)

Allison Proffitt, Editorial Director, Bio-IT World and Clinical Research News

The Emerging Innovator Award recognizes one exceptional early-career researcher advancing the future of life sciences through breakthrough work in biomedical data, computational methods, or technology-enabled discovery. The 2026 awardee will deliver a 20-minute plenary keynote at Bio-IT World, highlighting the impact of their research and the forward-looking direction of their work.

8:35 am

EMERGING INNOVATOR AWARD PRESENTATION: Scalable Connectomics for AI-Ready Brain Data

Ons M'Saad, PhD, Co-Founder & CEO, panluminate Inc.

Mapping the brain at synaptic resolution—connectomics—could transform neuroscience, medicine, and AI. Until now, the field has depended on electron microscopy: slow, expensive, difficult to scale, and limited to structure alone. Dr. Ons M’Saad presents a new optical approach that adds molecular context to large-scale brain maps, opening new ways to study neurodegenerative disease and inform more biologically grounded AI.

8:55 am PLENARY KEYNOTE INTRODUCTION:

Trusted Data, Accelerated Science: Building a Context-First Data Foundation for AI in BioPharma

Scott Weiss, Vice President, Product & Strategy, IDBS

As AI reshapes BioPharma R&D, the biggest barrier isn’t the model—it’s the data. Experimental and process data remains fragmented across spreadsheets and siloed systems, often stripped of scientific context. In this introduction, Scott Weiss, VP Product & Strategy at IDBS, argues that a context-first data foundation is essential to AI success, showing how unified, traceable lab data becomes AI-ready, GxP-compliant, and accelerates confident decision-making.

9:05 am PLENARY KEYNOTE PRESENTATION:

Generative AI across Drug Discovery Tasks

Jeremy L. Jenkins, PhD, US Head, Discovery Sciences, Novartis BioMedical Research

Many steps in drug discovery are informed by large-scale biological and chemical data, from genomics to the chemical universe, to phenotypic cell profiling. Generative-ML models are increasingly being deployed across these domains, including single-cell foundation models for target discovery, generative chemistry for rapid ligand design, and transfer learning to accelerate image analysis. Practical applications of generative AI in early drug discovery will be described, including simulated functional-genomics screens with in silico perturbations; compound design conditioned on protein pockets; and in silico-labeling approaches that replace traditional image staining. Together, these advances illustrate how generative AI is transforming how drug discovery research is conducted.

9:45 amCoffee Break in the Exhibit Hall with Poster Competition Winners Announced (Sponsorship Opportunity Available)

Bio-IT is all about connections! Explore booths, award-winning posters, and network with clients, colleagues, and exhibitors. Grab coffee, build relationships, and stay for a chance to win a raffle prize!

10:30 am

Organizer's Remarks

Erin Kadelski, Associate Project Manager, Production, Cambridge Innovation Institute

10:35 am

Chairperson's Remarks

Grant Stephen, CEO & Co-Founder, bPrescient, Inc.

10:40 am PANEL DISCUSSION:

Foundation Model Tuning for Biomedical AI: From Domain Adaptation to Enterprise Deployment

PANEL MODERATOR:

Ben Busby, PhD, Global Alliances Manager, Omics, NVIDIA

While foundation models transform biomedical R&D, most pilots fail to scale due to inadequate domain adaptation. This session unites academia and industry leaders to share proven frameworks for fine-tuning multimodal models across molecules, omics, and clinical data. Learn practical strategies for data curation, validation protocols, and governance structures that ensure regulatory compliance and build trust. Speakers present case studies demonstrating successful enterprise deployment, helping attendees move from experimentation to responsible, ROI-driven implementation.

PANELISTS:

Integrating Genomics into Multimodal EHR Foundation Models: A Study on the All of Us Research Program

Jonathan Z. Amar, PhD, Senior Applied AI Scientist, Generative AI, Verily Life Sciences

This research introduces an innovative EHR foundation model that integrates genomic PRS as a foundational data modality, moving beyond traditional EHR-only approaches to build more holistic health profiles. Leveraging the extensive and diverse data from the All of Us (AoU) Research Program, this multimodal framework aims to learn complex relationships between clinical data and genetic predispositions. The methodology extends advancements in generative AI to the EHR foundation model space, enhancing predictive capabilities and interpretability. Evaluation on AoU data demonstrates the model's ability to predict the onset of various conditions, particularly T2D, and that integrating the PRS modality improves predictive performance.

From Single Cells to Systems Insight: The Foundation Model Powering Cellarity’s Platform

Parul Bordia Doshi, Chief Data Officer, Cellarity

Cellarity, a clinical-stage biotech, has built an end-to-end AI platform grounded in a holistic view of disease biology at single-cell resolution. At its core is a foundation model trained on more than 150 million diverse single cells, capturing dysfunctional cellular states and the gene networks that drive them. Integrated with proprietary perturbation data and clinically translatable experimentation, our platform identifies small molecules that enable differentiated, translatable therapies.

GraphRAG and beyond: Question-Answering with Real-World Knowledge Graphs

Andreas Kraemer, PhD, Senior Staff Computational Biologist, QIAGEN

The QIAGEN Biomedical Knowledge Base contains tens of millions of curated biological relationships across genes, drugs, diseases, biological functions, and pathways, making it one of the most comprehensive biomedical knowledge graphs for drug discovery. Harnessing this data source for LLM-based reasoning requires precise retrieval of graph-based information relevant for the given context. I will discuss how subgraph retrieval and GNN-informed LLM prompt tuning improves over a naïve RAG approach in benchmarks covering multi-hop drug-discovery questions spanning target identification, disease mechanisms, and biomarker contextualization.

Scaling AI for Life Sciences with BioNeMo

Neha Tadimeti, Product Manager, Nvidia

Simulating biology to design new therapies remains a core objective of life sciences R&D. As data volumes grow and foundation modeling efforts expand, researchers require advanced computational technologies to support their work. This comprehensive talk outlines NVIDIA's approach to meeting these technical demands, focusing on the following key areas.

Data and Genomics: Advancements in data processing
Foundation Modeling: Strategies for scaling biological models and accelerating molecular discovery
AI Workflows: Developing end-to-end AI-scientist workflows to streamline modern research

12:10 pm

From AI-Ready Data to Intelligent Workflows: Ontologies as the Foundation for Pharma R&D

Andreas Matern, Vice President, Professional Services, Life Sciences Solutions, Elsevier

AI is rapidly reshaping expectations for scientific R&D, but most organizations cannot move directly from fragmented data landscapes and core systems such as electronic lab notebooks (ELNs) to fully autonomous, agent-driven workflows. The challenge is not the absence of data, but the lack of a shared semantic foundation that makes scientific information consistent, interpretable, and actionable across systems.

This session explores how ontologies provide that foundation by enabling data normalization, cross-domain integration, and context-aware AI workflows. We will examine how ontologies can connect ELNs and other R&D systems into a unified semantic layer, improving data capture, retrieval, and reuse. We will also show how ontologies are already enhancing LLM-based applications such as semantic search, entity resolution, and knowledge extraction, and how they are beginning to support more advanced use cases, including tool-using AI agents.

12:40 pm

Building AI-Ready Scientific Data Portals: Turning External Content into Actionable Insights

Neal Dunkinson, Senior Director, Solutions Sales, Corporate New Sales, CCC (Copyright Clearance Center)

To power generative AI and analytics, life science companies are increasingly shifting from ad-hoc search and article purchases to curating machine-readable datasets. Questions remain, however, when it comes to complying with copyright laws and policies. This session explores best practices for compliant, AI-ready data portals that integrate external scientific sources—maximizing data accessibility, scalability, and downstream value to stakeholders.

12:55 pm

A Practical Path to AI-Grounded Drug Discovery with Knowledge Graphs

Mark Hahnel, Vice President, Open Research, Digital Science

LLMs in drug discovery suffer from hallucination and lack of semantic intelligence. This talk presents practical, knowledge-grounded AI applications using knowledge graphs for use cases like target identification and polypharmacy prediction. The core is the neuro-symbolic approach which uses a knowledge graph to transform probabilistic LLMs into reliable reasoning systems. Learn to accelerate your pipeline by connecting internal knowledge with the research ecosystem via persistent identifiers.

1:10 pmSession Break and Transition to Lunch

1:20 pm

LUNCHEON PRESENTATION: Radically Accelerate Drug Discovery & Development Using Agentic AI

Dhaval Patel, Global AI Leader, Life Sciences, Chapsvision

Jeff Evernham, Head of Innovation, ChapsVision

For the pharmaceutical industry, where billions are spent on drug discovery, moving from AI pilots to production-grade autonomous agents is now critical. Join Dhaval Patel and Jeff Evernham as they share a framework for a unified AI intelligence layer integrating clinical, omics, real-world data, and internal knowledge. Learn key agent use cases, how to build enterprise agentic AI, and why a governed knowledge fabric is essential for trusted, scalable impact.

1:50 pmRefreshment Break in the Exhibit Hall with Poster Viewing (Sponsorship Opportunity Available)

Feeling tired? Recharge during the final Networking Exhibit Hall break! Visit booths, explore posters, connect with peers, and turn in your Game Cards for a chance to win a raffle prize.

2:30 pm

Chairperson's Remarks

Grant Stephen, CEO & Co-Founder, bPrescient, Inc.

2:35 pm

Three Steps to Success: Framework for Optimizing AI’s Impact on Drug Development

Umut Eser, PhD, Head, Generative AI, Johnson & Johnson Innovative Medicine

Grant Stephen, CEO & Co-Founder, bPrescient, Inc.

Based on extensive research, this presentation explores the three leading ways AI can accelerate the drug development process while substantially reducing costs. We provide a framework for considering how to deploy these capabilities in research and clinical while setting out (i.) the supporting evidence base and (ii.) the remaining challenges to be overcome. Our priority is to provide the audience with practical ways to positively impact their own drug development processes.

3:05 pm PANEL DISCUSSION:

Beyond Discovery: Turning AI Insights into Real-World Clinical Impact

PANEL MODERATOR:

Grant Stephen, CEO & Co-Founder, bPrescient, Inc.

PANELISTS:

Anastasia Christianson, PhD, Pharma Industry Data Science Leader

Charmaine Demanuele, PhD, Vice President, R&D Data Science & Digital Health - Neuroscience, Johnson & Johnson Innovative Medicine

Arturo J. Morales, PhD, Vice President, Technology Enabled Science, CSL Behring

Alexander Sherman, Director, Center for Innovation and Bioinformatics, Massachusetts General Hospital

Nagaraja "Sri" Srivatsan, CEO, Endpoint Clinical, Inc.

While AI dominates early-stage drug discovery discussions, pharmaceutical organizations struggle to connect these innovations to downstream clinical operations and real-world patient care. This panel tackles three critical gaps in current AI implementation: 1) integrating AI across R&D functions from target identification through clinical development, 2) leveraging digital health platforms and AI as the bridge between research insights and patient outcomes, and 3) enabling cross-team collaboration and external partnerships through shared AI infrastructure. Industry leaders from biopharma, hospitals, and digital health will debate what it really takes to break down silos between discovery, development, clinical, and commercial teams. Through candid discussion of real implementations, panelists will explore how to build communication channels that connect internal teams with external partners (hospitals, payers, and patients), creating an AI ecosystem that delivers measurable impact across the full therapeutic lifecycle.

4:05 pmClose of Conference