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 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 scientific infrastructure (data repositories, software ecosystems, foundational research programs, and open-source tools) forms the backbone of biomedical innovation. But recent and ongoing shifts in U.S. federal funding have introduced significant instability, with consequences that ripple from early academic discovery to startup formation, venture investment, pharma R&D, and global data access. These changes threaten not only scientific progress, but also U.S. competitiveness, innovation pipelines, and the reproducibility of AI/ML models that increasingly rely on publicly funded datasets and code.

This session convenes diverse voices across the biomedical R&D ecosystem to examine how funding disruptions are reshaping discovery, development, and long-term innovation and what each sector believes is needed to maintain a stable scientific future. We open with global survey results from the Global Alliance for Open Science (GAFOS), founded at the 2025 Bio-IT World Conference & Expo. With input from more than 170 professionals across academia, biotech, pharma, government, and nonprofits, the survey reveals community-wide concern, emerging risks, and real-world challenges as core public data and software resources become increasingly unstable.

The discussion then expands beyond the survey to include perspectives from early-stage academic researchers who rely on NIH/NSF grants; seed- and pre-seed founders generating the data needed to attract private investment; venture capital groups assessing risk in a weakening public infrastructure environment; pharma and techbio teams dependent on public datasets and open tools for drug discovery, diagnostics, and ML model development; and policy and regulatory experts evaluating the long-term consequences of reduced public investment on U.S. innovation leadership.

Independent community initiatives, including GAFOS and international organizations engaged in mirroring, redundancy, and policy advocacy, will also share how the global community is responding to emerging risks.

Attendees will leave with a data-driven understanding of the challenges ahead, a cross-sector view of what is at stake, and actionable strategies the Bio-IT community can advance to safeguard the scientific infrastructure upon which biomedical innovation depends.

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.

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.