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Webinar offers guide to R&D data clarity with perspectives from a Big Pharma, global CRO, space‑station lab, and immune-system-in-a-dish startup

By Brian Buntz | May 14, 2025

Low-quality, poorly curated, and siloed scientific data costs advanced economies billions of dollars each year by draining researcher productivity, duplicating experiments, and slowing innovation.

A report commissioned by the European Commission estimated that failing to adopt FAIR (findable, accessible, interoperable, reusable) data principles costs Europe’s economy at least €10.2 billion annually owing to wasted researcher time and redundant work.

The problem is widespread. Gartner pegs the financial impact of poor data quality at nearly $13 million per organization. Similarly, the life sciences industry, as Pistoia Alliance’s 2024 “Lab of the Future” survey, flags inadequate data quality as the top barrier to implementing AI in R&D. More than half, 52% of respondents, pinpointed poorly curated datasets and another 38% citing non-FAIR data as barriers.

Crawl. Walk. Run. Integrate. Automate. Predict.

Those lost hours — and the discoveries still locked in the data — set the stage for a June 11 webinar that brings together Michael Roberts, Ph.D., of the ISS National Lab, Parallel Bio technologist Ari Gesher, Labcorp digital-histology lead Paul Mésange, Ph.D. and Pfizer predictive-analytics chief Jonathan Crowther, Ph.D. The panel will lay out a practical “crawl-walk-run” blueprint for turning data chaos into a searchable, automated, analytics-ready lab environment, whether the lab is orbiting 250 miles above Earth or chasing tumor biomarkers on the ground.

To curb waste and surface hidden insights, labs need a deliberate, stepwise plan.

  • Crawl means, for instance, corralling scattered files into a single source of truth, adding consistent metadata, and putting basic data-governance guardrails in place.
  • Walk adds connective tissue. Think instrument hookups, template-driven data capture, dashboarding, and modest automation that removes manual copy-paste without upending how scientists work.
  • Only when those rails are solid does the lab run: Here is where the fun begins. Machine learning, digital twins, and eventually, say, driverless workcells that spot anomalies, predict outcomes, and accelerate the pace of science.
A photo of the ISS National Laboratory

A photo of the ISS National Laboratory [Image courtesy of ISS National Laboratory]

Hands-on lessons from bench to orbit

Each speaker in the webinar arrives with a hard-won experience. Labcorp’s Paul Mésange helped connect 20+ digital slide scanners across 14 sites into a global digital pathology network, and validated AI software that identifies and quantifies breast-cancer biomarkers, improving consistency and saving time. Parallel Bio’s Ari Gesher is building a “lights-out” automated lab where robots conduct immune-organoid experiments, and its AI-driven “Clinical Trial in a Dish” platform aims to accelerate preclinical drug discovery. Pfizer’s Jonathan Crowther spearheaded efforts to aggregate scattered clinical trial data. That work is enabling predictive models and real-time monitoring that help study teams proactively identify and mitigate enrollment risks. And ISS National Lab’s Michael Roberts oversees automated experiment modules in orbit, like self-contained labs and robotic experiment platforms, that stream microgravity data to Earth in real time. Together, they show how crawl-stage data plumbing can mature into advanced pipelines that accelerate scientific discovery.

Register for the free June 11 webinar here.

Speaker biographies

Paul Mésange

Paul Mésange, Ph.D.

Global Director, Histology, Labcorp

Paul Mesange, an engineer with a PhD in pharmacology, has built a career at the intersection of science, clinical trials, and digital innovation. As Global Director of Operations, Histology at Labcorp, he drives efficiency, operational excellence, and digital transformation in clinical trials. Previously, he led global scientific efforts in anatomic pathology, optimizing biomarker research and laboratory processes. His expertise spans oncology, targeted therapies (CGT), and translational research, with a focus on Phase II and III clinical trials at Stanford and INSERM.

Ari Gesher

Ari Gesher

Head of Technology, Parallel Bio

Ari Gesher came aboard Parallel Bio in June 2024 as its first head of technology, tasked with building the AI, robotics and data infrastructure that powers the startup’s immune-organoid drug-discovery platform. Before jumping into biotech, he spent seven years as CTO of Insight M (formerly Kairos Aerospace), scaling wide-area methane-detection systems that help industry curb greenhouse-gas leaks. Earlier, Gesher was one of the earliest engineers at Palantir Technologies, where he led open-source and privacy-engineering initiatives, and before that steered development of SourceForge.net.

Jonathan Crowther

Jonathan Crowther, Ph.D.

Head, Predictive Analytics, Pfizer

Jonathan Crowther is Head of Predictive Analytics at Pfizer, where he leads transformative initiatives at the intersection of pharmaceutical innovation, healthcare data strategy, and next-generation technologies. With deep expertise in generative AI, quantum computing, and real-world data, he empowers clinical research teams to move beyond static feasibility models toward dynamic, data-driven forecasting. Jonathan is a recognized voice in the evolution of clinical trial operations, known for translating complex analytics into actionable strategy.

Michael Roberts

Michael Roberts, Ph.D.

Chief Scientific Officer, International Space Station National Laboratory

Michael Roberts is the Chief Scientific Officer of the International Space Station National Laboratory and Vice President at the Center for the Advancement of Science in Space (CASIS). Before joining CASIS in 2013, Michael worked as a microbial ecologist, principal investigator, and research group lead at the Kennedy Space Center. Prior to arriving at NASA-KSC in 1999, Michael completed an undergraduate degree in biology at Maryville College, a doctorate in microbiology at Wesleyan University and post-doctoral research at the Center for Microbial Ecology at Michigan State University.

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