This talk explores how digital technologies are transforming laboratory environments. We will discuss how advanced software solutions and cloud-based services enable automation, data integration, and collaboration in scientific research. Key topics include AI-driven analysis, electronic lab notebooks (ELNs), laboratory information management systems (LIMS), and secure cloud platforms. These innovations streamline workflows, enhance data accuracy, and support remote access, making labs more efficient, connected, and future-ready.

Translational research increasingly depends on secure and compliant management of complex patient sample data, including radioactive and isotopically labeled assays. To overcome workflow fragmentation and data integrity challenges, we developed CAMEO, an AI-ready digital platform that streamlines secure data exchange, automates device interactions, and standardizes review and approval processes. By enabling interoperability, compliance, and future AI integration, CAMEO accelerates data reliability and digital transformation across experimental and clinical workflows.

Biomedical discovery increasingly depends on shared, AI-ready data platforms, yet operating them across institutions and constraints is challenging. The ASAP Discovery Consortium is a multi-site antiviral drug discovery effort built on shared infrastructure and capabilities rather than proprietary silos. This talk examines the software platforms, FAIR data pipelines, governance, and provenance mechanisms supporting the consortium, and shares lessons learned enabling reproducible collaboration and blind AI benchmarking across distributed drug discovery teams.

Public data and software infrastructure remain foundational to biomedical innovation, but the conversation has shifted. Rather than broad instability, recent policy and funding changes are creating targeted adjustments in priorities, governance, and access that are reshaping how scientific data is generated, shared, and sustained. This session focuses on how leaders across academia, government, and biopharma are actively adjusting their strategies in response. The discussion moves beyond awareness to execution, examining how organizations are changing how they generate, access, and rely on scientific data.

The session opens with insights from the Global Alliance for Open Science (GAFOS), launched at the 2025 Bio-IT World Conference & Expo. Drawing on input from more than 170 professionals across academia, biotech, pharma, government, and nonprofits, the survey highlights key concerns, emerging risks, and practical challenges related to public data and software infrastructure. Short talks and discussion will then examine how perspectives and strategies have evolved over the past twelve months. Where are risks still real? Where has the narrative corrected? What signals are driving decisions now? The session concludes with a moderated, interactive discussion between speakers and attendees.

Attendees will leave with a clear understanding of how data strategy, funding reliance, and infrastructure decisions are changing across the ecosystem, and what actions are required to operate effectively in this new environment.

• 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

While AI continues to dominate discussions in project management, many Project Management Offices (PMOs) struggle to move from conceptual curiosity to real implementation. This talk introduces a practical AI Readiness Roadmap specifically tailored for PMOs. It will walk participants through the maturity stages, from assessing organizational data, processes, and tools, to piloting AI use cases, and eventually scaling AI adoption responsibly.

This talk will explain how a knowledge graph-driven digital twin of the pharma supply chain turns complex drug launch planning into reliable, data-driven decisions. As new modalities expand operational and manufacturing complexity, graph-based models integrate diverse data, reveal causal bottlenecks, and support validated, explainable scenario analyses. The result is a scalable, production-ready framework that reduces cost, improves predictability, and accelerates the delivery of next-generation therapies to patients.

The focus on compliance continues to intensify, spurred by a growing list of data privacy, security. and publication mandates such as the recent changes to the NIH Genomic Data Sharing Policy. Research organizations are looking for solutions to meet these new requirements without unduly burdening investigators. We will discuss how the Globus platform enables definition and enforcement of diverse policies that enable researchers to confidently work with PII, PHI, and other sensitive or controlled-access data without compromising compliance requirements. We will present common use cases and review features that address compliance with frameworks such as NIST SP 800-171.

For 20 years, Trends from the Trenches has been Bio-IT World’s unscripted pulse check, offering candid, insider perspectives on what works, what fails, and what’s pure hype in scientific computing. As the field evolved, the session broadened to reflect the real operational challenges and breakthroughs shaping R&D. For 2026, the format evolves again: a focused, credibility-driven keynote paired with a community-powered unconference built from attendee input. The result is a forum for late-breaking insights, grounded realities, forward-looking perspectives, and practical solutions you won’t find in vendor decks, marketing summaries, or any LLM. It leaves participants energized by the collective intelligence in the room and inspired by the emerging possibilities shaping the future of life-science computing.

This presentation frames the industry’s next chapter by tracing how Trends from the Trenches has shaped digital R&D for two decades and by spotlighting the forces redefining scientific computing today: AI–HPC convergence, modality-driven compute, multimodal data, and rising expectations for speed, interoperability, and trust. Remarks set the foundation for a forward-looking exploration of where digital biology and computational innovation are heading next.

This session features a structured, participatory unconference built around topics sourced from Bio-IT event attendees during the conference week. A working group synthesizes all submissions Wednesday evening into a small set of high-value discussion themes. The facilitator guides the room through rapid-fire exchanges, micro-debates, and collaborative problem-solving focused on operational realities in AI, computing, data engineering, and scientific software. The goal is to surface patterns, stress-test ideas, and extract practical solutions emerging across the community—creating an annual, crowd-generated state-of-the-field snapshot that only this session can produce.