10:40 AM

Innovative Practices Award Winner Presentations: Excellence in Technological Innovation

Since 2003, Bio-IT World has hosted an elite awards program with the goal of highlighting outstanding examples of how technology innovations and strategic initiatives are being applied to advance life sciences research. The 2026 Innovative Practices Awards winners represent excellence in innovation in the areas of open science, patient advocacy, global data access, and real-world AI. The winning entries include collaborations between Arizona State University with Starfish Storage; CareDx; ASAP Discovery Consortium; and Novartis with Genedata AG. These four award-winning examples show the full lifecycle of data in modern R&D, from unlocking legacy data, to building enterprise platforms, to enabling open collaboration, and ultimately driving clinical decision-making.

10:45 AM

From Unsearchable Archive to Self-Service Knowledge Platform: How ASU Transformed 20 Years of Indigenous Health Imaging Data (Innovative Practices Winner)

For over two decades, a Bolivian hospital has collected CT scans of the Tsimane indigenous population as part of Arizona State University’s Tsimane Health and Life History Project, creating a unique longitudinal archive for studying healthy aging. But the archive was functionally unsearchable. Inconsistent Digital Imaging and Communications in Medicine (DICOM) metadata across more than 20 years of scanner evolution meant every researcher request required days of manual investigation by ASU’s IT team.

ASU’s Center for Evolution and Medicine partnered with Starfish Storage to transform this archive into a self-service, consent-governed knowledge platform. Using metadata-driven virtualization, researchers now discover and access imaging data in minutes instead of weeks. Policy-based access controls enforce Tsimane community consent agreements automatically. The deployment eliminated hours of weekly manual curation that had become unsustainable as collaboration scaled, while enabling dozens of global collaborators to work independently.

11:05 AM

Real-World AI Award: Novartis Reimagines CMC with AI-Native Data Platform (Innovative Practices Winner)

As therapeutic modalities grow more complex and regulatory scrutiny becomes increasingly data-driven, traditional document-centric CMC operating models are no longer sufficient. To address this challenge, Novartis Technical R&D organization implemented an interoperable, AI-native, GxP-enabled data platform that transforms fragmented information into trusted, reusable data assets. This foundation enables in silico experimentation, modelling and simulations, process monitoring and predictive risk assessment, empowering teams to anticipate and mitigate risks earlier and accelerate readiness for regulatory milestones. These capabilities have the potential to eliminate months‑long development delays and generate multimillion‑dollar per‑site savings, while extending beyond near‑term efficiency to support better decision‑making, scalable quality and compliance, and deeper scientific insight across the CMC portfolio. The platform, developed collaboratively with Genedata, has evolved for use beyond the original implementation into an off-the-shelf product for biopharma CMC.

11:25 AM

ASAP Discovery Consortium—Data Sharing for Open Science (Innovative Practices Award Winner)

The AI-driven Structure-enabled Antiviral Platform (ASAP) is an open-science consortium developing oral, clinic-ready therapeutics for pandemic-potential RNA viruses, including coronaviruses, flaviviruses, and picornaviruses. Funded by NIAID investment, ASAP leverages the cost-efficient COVID Moonshot model to bridge the "preclinical valley of death". By integrating AI/ML, automated structural biology at Diamond Light Source, the platform has delivered a pre-clinical candidate in 2025, 8 hit to lead candidates, and ten resistance-robust targets. 

ASAP treats all outputs—including structural data, assay protocols, and chemical matter—as "first-class research products" shared via FAIR data repositories (ChEMBL, PDB, Protocols.io, AddGene, Github). Notably, in 2023, the consortium contributed 6% of all new X-ray structures to the Protein Data Bank. A recent community blind challenge with Polaris and OpenADMET further demonstrated the platform's utility by benchmarking computational methods against real-world lead-optimisation data, advancing reproducible, high-impact drug discovery.

11:45 AM

AlloSure Plus (Innovative Practices Award Winner)

AlloSure Plus is a CareDx innovation project advancing organ transplant surveillance through the integration of molecular diagnostics, clinical data, and artificial intelligence (AI). The project culminated in the development of an AI‑enabled risk‑prediction framework that combines AlloSure Kidney donor‑derived cell‑free DNA (dd‑cfDNA) analysis with routinely collected clinical and laboratory parameters to deliver a personalized assessment of kidney allograft rejection risk. 

Designed to address the long‑standing challenge of late and non‑specific rejection detection, AlloSure Plus demonstrates how data integration and machine learning can improve the timing, accuracy, and confidence of clinical decision‑making. The outcome is a scalable, validated model that supports earlier intervention, reduces reliance on invasive biopsies, and enables more individualized patient management. AlloSure Plus exemplifies how applied AI and real‑world clinical data can be translated into actionable insights that improve transplant outcomes and elevate standards of care.

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 presentation delivers a candid, comprehensive assessment of the forces reshaping scientific computing and digital R&D. Eleanor examines the technologies, platforms, modalities, and market dynamics that are truly driving change—highlighting what’s working, what’s stalling, and what’s losing relevance. She synthesizes emerging patterns across AI, data platforms, workflow orchestration, multimodal analytics, and new therapeutic and diagnostic directions, while calling out persistent bottlenecks and architectural missteps slowing progress. The result is a grounded, evidence-based view of where the field is heading and which strategies will matter most in the next cycle of innovation.

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.