Cambridge Healthtech Institute’s 25th Annual
Bio-IT World Conference & Expo
Converging Science and IT to Advance Precision Medicine
May 19-21, 2026
SUBMIT YOUR PROPOSAL
The deadline for priority consideration is October 15, 2025.
Are you ready to present at the 25th Annual Bio-IT World Conference & Expo, taking place May 19-21, 2026, in Boston, MA? We’re excited to receive your proposals!
The Bio-IT World Conference & Expo is the premier global event for showcasing the technologies and analytic approaches that solve problems, accelerate science, and drive the future of precision medicine. For 25 years, Bio-IT has brought together the leading voices from life sciences, pharma, healthcare, informatics, and technology to share innovations, case studies, and best practices that are transforming research and development worldwide.
Over the past two decades, our community has advanced discussions on digital and data transformation, the rise of AI and machine learning, IoT, and the integration of Open Source and FAIR Data principles. We’ve explored digital health tools driving medical innovation, the promise of predictive and generative AI models, and strategies for navigating complex regulatory, investment, and data challenges.
In 2026, we mark the 25th Annual Bio-IT World Conference & Expo in Boston with an expanded program featuring 11 conference tracks, focused symposia, workshops, and networking forums. With more than 200 speaking opportunities available, we are seeking dynamic speakers eager to present innovative research, applied solutions, and real-world success stories that demonstrate not only how data and technology are solving today’s toughest challenges in life sciences and healthcare, but also how those solutions are delivering measurable value, accelerating discoveries, improving efficiency, and driving better outcomes for patients and organizations alike.
This year’s agenda will highlight flagship tracks alongside exciting new additions such as AI-Powered Robotics & Intelligent Lab Automation, reflecting the latest industry trends and the evolving needs of our community. Your participation ensures that these discussions remain practical, impactful, and forward-looking—providing peers and collaborators with the insights needed to advance biomedical discovery, development, and patient care.
Join us May 19–21, 2026, in Boston for three days of engaging symposia, technical presentations, and networking opportunities. Don’t miss your chance to be part of this influential gathering, to showcase your work, and to help define the next chapter of Bio-IT innovation.
We look forward to your proposals and to seeing you in Boston!
Coverage will include, but is not limited to:
SYMPOSIA (taking place Tuesday, May 19)
S1: Generative AI Tools
Move from Proof-of-Concept to Production in Regulated Environments
The Generative AI Tools symposium equips practitioners with strategies to move beyond proof-of-concept projects and achieve production-ready systems in regulated environments. In the 2025 symposium, we explored what generative AI could do for drug discovery—from molecular design and target identification to candidate optimization. Attendees engaged directly with cutting-edge platforms and gained hands-on insight into the possibilities of GenAI in research. In the 2026 program, we shift from exploration to execution. Too many initiatives stall at the “last mile,” facing validation gaps, GxP compliance challenges, and the hidden costs of scaling. This year’s symposium focuses on overcoming those barriers through candid case studies in molecular design, lead optimization, and clinical workflows. Attendees will learn how teams are deploying GenAI responsibly, at scale, while addressing issues like model drift, technical debt, and compliance readiness. Sessions feature hands-on engagement with platforms, validated protocols, and reusable workflows—providing not only technical knowledge but also lessons learned from successes and failures. Designed for data scientists, computational biologists, and ML engineers, this symposium delivers the tactical playbooks and confidence needed to transform GenAI from innovation into impact.
S2: AI for Biologics
AI Breakthroughs Powering the Future of Biologics Discovery
The AI for Biologics symposium will explore the transformative role of AI and machine learning (ML) in biologics drug discovery. Attendees will leave with insights into both the current capabilities and future opportunities of AI/ML in biologics innovation. We will showcase novel methods developed in-house and outside of pharma/biotech, along with early, promising results, demonstrating their impact on drug discovery pipelines. Join this symposium to learn about the future outlook for AI-driven drug development and its potential to drive breakthrough therapies.
S3: Knowledge Graphs
Connect Fragmented Data for Unified Views and Powerful Discoveries
The Knowledge Graphs symposium will showcase how next-generation graph technologies are transforming the landscape of biomedical research. As the scale and complexity of multimodal data continue to grow, knowledge graphs are evolving from experimental tools into essential platforms for integrating diverse datasets and revealing new biological insights. This year’s program highlights how AI and next-generation models are being embedded in graph frameworks to build intelligent, connected systems that accelerate discovery and streamline scientific inquiry. Speakers will share real-world experiences demonstrating how knowledge graphs unify fragmented data, enable richer analysis, and map complex biological relationships across scales. Designed for data scientists, bioinformaticians, computational biologists, and R&D leaders, this symposium provides practical perspectives on how AI-infused knowledge graphs can drive more efficient research, support translational breakthroughs, and open new frontiers in precision medicine.
TRACKS (taking place Wednesday, May 20 – Thursday, May 21)
T1: Data Platforms & Storage Infrastructure
Optimize Data Platforms for Scale, Speed, Performance, and Cost Efficiency
Life sciences data volumes are exploding, driving the need for scalable, secure, and sustainable infrastructure. From cloud-based platforms and high-performance computing to AI-driven storage optimization, organizations are rethinking how they manage, integrate, and govern critical data. This track explores cutting-edge approaches to storage, processing, and interoperability, offering real-world strategies for balancing speed, performance, cost, and compliance. Learn how industry leaders are advancing large-scale data management and shaping the future of data infrastructure in life sciences.
T2: Data Management
Transform Data into Strategic Assets for Discovery, Collaboration, and AI
The Data Management track explores how life sciences organizations are transforming data from a siloed liability into a strategic asset that fuels discovery, collaboration, and AI. In the 2025 program, we focused on building scalable infrastructure and introducing the “data product” approach, showing how well-managed data can accelerate research and support AI readiness. Attendees gained frameworks for FAIR principles, governance, and platform-level strategies that made data more accessible and reusable. In the 2026 program, we move from concepts to operationalization, with sessions organized around the full lifecycle of modern data strategy. We begin with foundational infrastructure, highlighting scalable, distributed platforms and resilient architecture. From there, we address data integration and governance, showcasing practical approaches to harmonization, stewardship, and compliance. The program then examines data product creation, demonstrating how organizations are making data consumption-ready, AI-enabled, and reusable across R&D pipelines. Finally, we turn to AI-driven insights and outcomes, with real-world case studies that show how advanced data platforms are enabling breakthroughs such as federated ecosystems, digital twins, and accelerated trial optimization. These strategies not only modernize IT infrastructure but also empower biomedical researchers to generate new insights, streamline translational pipelines, and accelerate discovery. Designed for data managers, IT leaders, and R&D scientists, this track provides both the strategic vision and the technical playbooks to operationalize data at scale—accelerating discovery, reducing costs, and powering AI-driven innovation.
T3: Software Applications & Services
Build Next-Gen Software for Discovery, AI, and Digital Transformation
The Software, Applications & Services track explores how life sciences organizations design, build, and deploy software that powers discovery, AI, and digital transformation. In the 2025 program, we focused on improving release management, automating testing, and streamlining development pipelines. In 2026, we shift from foundational practices to next-generation applications. Sessions will highlight how software enables digital labs, powers biomanufacturing digital twins, and supports spatial biology analytics at scale. We’ll also explore new paradigms like agentic AI and FAIR software—ensuring systems are as interoperable and reusable as the data they handle. Designed for developers, computational scientists, and IT leaders, this track provides both hands-on case studies and strategic guidance for building future-ready platforms that accelerate research and deliver measurable impact across life sciences R&D.
T4: Cloud for AI/ML & Modern Data Science
Cloud Technologies and Strategies to Drive Better, Faster Analytics
Adopting and deploying cloud technologies is a critical necessity for digital transformation. Vast data volumes, AI/ML workloads, and modern data science all demand scalable, flexible, and secure infrastructure. Yet, with so many deployment models and applications, identifying the best fit remains a challenge. The Cloud for AI/ML & Modern Data Science track, through insightful case studies and best practices, offers guidance on selecting the ideal cloud or hybrid infrastructure and applications to advance R&D, foster collaboration and innovation, and maintain the flexibility needed to keep pace with the technological advances shaping pharmaceutical R&D.
T5: Generative AI
Accelerate Research and Enterprise Innovation through Responsible GenAI Adoption at Scale
Accelerate Research and Enterprise Innovation through Responsible GenAI Adoption at Scale
The Generative AI track equips organizations with strategies to move beyond experimentation and embed GenAI as a trusted, enterprise-wide capability. In the 2025 track, we explored how generative AI could harness data potential to drive innovation and overcome challenges of fragmented, inconsistent information. Attendees gained insight into the opportunities GenAI presented for biomedical research and the promise of accelerated discovery. In the 2026 program, we shift from exploration to operationalization. GenAI is no longer experimental—it is a strategic imperative for life sciences organizations navigating regulatory scrutiny, workforce readiness, and organizational transformation. This year’s track focuses on what it takes to scale responsibly across research, clinical, and IT environments: building trust in AI-driven decisions, ensuring transparency for regulators, and demonstrating ROI beyond pilot metrics. Presentations will feature case studies from executives, R&D leaders, and IT innovators who have led successful GenAI transformations, highlighting frameworks for governance, equity, sustainability, and cross-functional adoption. Designed for executives, scientists, and technology leaders alike, this track delivers the strategies, insights, and governance models needed to transform GenAI from isolated experiments into lasting enterprise value.
T6: AI for Drug Discovery & Development
Next-Gen AI Driving Discovery, Validation, and Development across the Biopharma Lifecycle
The AI for Drug Discovery & Development track showcases how artificial intelligence is accelerating innovation across the entire biopharma lifecycle. In the 2025 program, we explored AI’s transformative impact on target identification, molecular design, precision medicine, and clinical development—highlighting how machine learning can accelerate timelines and improve therapeutic success rates. In the 2026 program, we move beyond exploration to focus on operationalization and next-generation paradigms. Sessions will highlight how organizations are applying foundation models for biology and chemistry, multimodal omics + imaging integration, and agentic AI systems to drive discovery and streamline workflows. Case studies will showcase the design–make–test–learn loop in action, including high-throughput synthesis and automated experimentation. We’ll also address ADMET and PK-PD prediction, explainable AI, validation benchmarks, and regulatory readiness—key enablers for moving AI-driven candidates into the clinic. Designed for computational biologists, data scientists, and R&D leaders, this track provides both scientific insight and practical frameworks to implement AI responsibly, transforming it from an experimental tool into an enterprise-wide driver of discovery and development.
T7: AI for Oncology, Precision Medicine & Health
Transform Multimodal Data into Clinical Impact with Trusted AI
The AI for Oncology, Precision Medicine & Health track highlights how next-generation AI is reshaping cancer research, clinical decision-making, and patient care. In 2025, we focused on applying AI to bridge gaps in real-world data and drive early advances in precision medicine. In 2026, we shift to operationalization and validation. Sessions will cover multi-modal fusion (pathology, radiology, omics, clinical notes), foundation models for imaging and pathology, and AI-enabled clinical trials for trial matching and cohort selection. We’ll also explore digital twins for oncology, bias/fairness in clinical AI, and regulatory readiness with explainable AI and validation benchmarks. Designed for oncologists, data scientists, and health system leaders, this track delivers both the scientific depth and the practical playbooks needed to responsibly integrate AI into oncology workflows—accelerating precision medicine while ensuring equity, trust, and clinical impact.
T8: Data Science & Analytics Technologies
Scale Data Science in Life Sciences from Algorithms to Outcomes
Scale Data Science in Life Sciences from Algorithms to Outcomes
The Data Science track showcases how life sciences organizations are moving from algorithms to operational impact. In the 2025 program, we highlighted scalable platforms, personalized analytics, and building data-driven organizations, setting the foundation for applied AI in biopharma. In the 2026 program, we shift to execution and trust. Sessions will explore MLOps/LLMOps in GxP environments, causal inference for RWE and trial optimization, and uncertainty quantification, explainability, and model validation benchmarks. Talks will also highlight multimodal fusion architectures, graph ML for biology, and the role of FAIR, reproducible software, in regulated workflows. Case studies will show how teams are moving from notebook to production—operationalizing data science to deliver ROI, compliance, and scientific breakthroughs. Designed for computational biologists, data scientists, IT engineers, and R&D leaders, this track provides the frameworks, technical playbooks, and validation strategies needed to make data science trustworthy, compliant, and impactful across discovery and development.
T9: Bioinformatics
Operationalize Bioinformatics and Multimodal Data for Discovery and Clinical Impact
The Bioinformatics track highlights how next-generation computational methods and multimodal data integration are transforming biomedical research and clinical practice. In the 2025 program, we explored how bioinformatics fuels discovery through multiomics integration, functional genomics, structural bioinformatics, and AI-powered predictive modeling. Sessions demonstrated how bioinformatics tools help personalize treatments, generate insights from high-throughput sequencing, and advance precision medicine. In the 2026 program, we move from exploration to operationalization. Talks will feature advances in pangenome analysis, structural variant detection, and spatial/single-cell omics, alongside strategies for integrating genomics, proteomics, metabolomics, imaging, and clinical data into cohesive multimodal frameworks. Presentations will also spotlight workflow orchestration with Nextflow, Snakemake, and WDL, emphasizing reproducibility, benchmarking, and FAIR practices. A new focus will be on validating pipelines in CAP/CLIA and IVDR environments, bridging the gap between research and regulated clinical applications. Designed for bioinformaticians, computational biologists, and clinical genomics leaders, this track provides both technical depth and translational perspective—equipping attendees to scale bioinformatics and multimodal data from the bench to the clinic with rigor and impact.
T10: AI-Powered Robotics & Intelligent Lab Automation
Unite Physical and Digital to Build the Intelligent Laboratory of the Future
The AI-Powered Robotics & Intelligent Lab Automation track explores how robotics, AI, and computational integration are reshaping R&D operations and accelerating discovery. In 2025, automation was still largely viewed as an engineering challenge. In 2026, the conversation shifts to intelligent, computationally integrated labs—where physical robotics and digital infrastructure operate as one. This new track highlights how AI-driven robotic platforms, cloud-integrated digital twins, and adaptive experimental design are transforming laboratories into self-optimizing research environments. Sessions will feature case studies of autonomous lab systems delivering high-throughput screening, synthesis, and analysis with minimal human intervention. We’ll explore how collaborative robots, predictive maintenance, and multi-robot orchestration enable scalable and reliable automation. Talks will also cover integration with LIMS, bioinformatics pipelines, and edge/cloud architectures to create seamless data-to-discovery workflows. Designed for lab automation engineers, R&D operations leaders, informatics specialists, and IT architects, this track provides the strategic vision, technical playbooks, and implementation frameworks needed to scale intelligent lab automation—bridging the gap between physical robotics and digital computation to build the laboratory of the future.
T11: Pharmaceutical R&D Informatics
Digitalization of Pharma R&D and the Path to Innovation
The need and urgency to generate, organize, and analyze data in the pharmaceutical industry has not waned. With the increase in digitalization in Pharma R&D, increasingly large and complex system landscapes have been established, and as a consequence, pharma companies struggle with the exploded operative effort, limiting the potential for further innovation. At the same time, many life science organizations remain limited by fragmented workflows and disconnected systems. The Pharmaceutical R&D Informatics track will include talks from senior-level pharma and biotech experts who will showcase current digital transformation efforts, within their organizations, for optimizing operations via new technologies and services to create an efficient informatics ecosystem, while meeting scientific, business, and regulatory demands.
Innovation Showcase – NEW
The Bio-IT World Conference & Expo Innovation Showcase offers emerging companies (pre-commercial, offering solutions for life sciences, pharma, clinical research, healthcare, or informatics/tech; founded in 2020 or later; and currently raising a late seed or Series A) an alternative to sponsoring a traditional 15- or 30-minute vendor presentation. This thought-leadership opportunity features a shorter, in-track presentation with event-wide visibility via curated lightning talks or demos, connecting start-ups with an engaged audience of experts, partners, and investors. To discuss participation, contact Cindy Crowninshield at ccrowninshield@healthtech.com, and she’ll connect you with our Sales team.
INVESTOR CONFERENCE (taking place Tuesday, May 19, 2026)
Bio-IT World Venture, Innovation & Partnering
Connect Capital and Science to Shape the Future
As part of the 25th Annual Bio-IT World Conference & Expo, the 3rd Annual Bio-IT World Venture, Innovation & Partnering Conference (May 19, 2026) delivers an executive-level platform for investors, corporate leaders, and entrepreneurs driving the next wave of biotech and precision medicine. This boutique event convenes C-suite leaders from venture capital, private equity, corporate venture arms, growth-stage companies, and pharma. The 2026 program zeroes in on AI-driven discovery, platform- vs. product-investment models, evolving M&A and partnership strategies, IPO and private liquidity pathways, and regulatory shifts shaping capital deployment. Sessions are designed to provide investors with clear insights into market dynamics, risk-adjusted returns, and scalable innovation strategies. Through candid discussions, fireside chats, and curated panels, participants will explore how capital is being allocated, where innovation pipelines are headed, and how to identify long-term winners. Alongside investor-focused dialogue, attendees gain access to 150+ exhibits, 11 scientific tracks, and global partners from 30+ countries to broaden their market perspective.
If you would like to submit a proposal to give a presentation at this meeting, please click here.
The deadline for priority consideration is October 15, 2025.
All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Innovation Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.
Opportunities for Participation:
SUBMIT YOUR PROPOSAL