With 7+ years building products and helping scientists get science done through software, Samantha leads innovations that address real customer and scientific field needs. Her background includes expertise in molecular and biochemical techniques, microscopy, biomolecular condensates, proteomics, and RNA-sequencing. Samantha connects deeply with the customer base, transforming scientific challenges into solutions that drive innovation. She brings a decade of bench experience in molecular biology and a passion for FAIR data/metadata to the Revvity Signals product team.
Despite massive investments in automation and high-throughput technologies, drug discovery scientists find themselves increasingly bogged down by data management rather than focused on scientific innovation. This provocative session examines how fragmented software ecosystems and inconsistent data practices are silently sabotaging productivity across the industry. We'll explore the critical gap between FAIR data principles in theory and their practical implementation in the lab—where scientists often view standardization as bureaucratic overhead rather than scientific enablement. Revvity Signals is pioneering a new approach that embeds ontologies directly into workflow tools, making standardization intuitive while creating AI-ready datasets that can be meaningfully compared across teams and organizations. We'll discuss how this paradigm shift transforms FAIR from an administrative burden into a powerful scientific accelerator, enabling researchers to extract insights that would be impossible with traditional data management approaches. Organizations that solve this "hidden productivity crisis" while building truly comparable datasets stand to gain months or even years in development timelines.