Bridging the Gap for AI in Medicine: NIST Consortium Approach to Standardizing Flow Cytometry and Data Harmonization

THE SPEAKER

Paul C. DeRose, PhD: NIST; FCSC WG1 Co-Chair

Lili Wang, PhD: NIST; FCSC PI and WG2 Co-Chair

Yu "Max" Qian, PhD: Associate Professor, J. Craig Venter Institute; FCSC WG5 Co-Chair

WEBINAR SUMMARY

Recent advances in regenerative medicine advanced therapies (RMAT) are revolutionizing health care. While flow cytometry assesses RMAT quality (viability, identity, purity, potency), inconsistent results across platforms and sites hinder standardization and AI/ML development. To solve this, NIST launched the Flow Cytometry Standards Consortium (FCSC) in 2020 to develop measurement standards that accelerate RMAT manufacturing and approval.

FCSC has established five working groups (WGs) to advance standardization, data infrastructure, and AI in cytometry. This webinar highlights the work of three:
•   WG1: Focuses on Equivalent Reference Fluorophore (ERF) measurement standards and is conducting its first interlaboratory study (ILS) to evaluate the accuracy of ERF value assignments and associated uncertainty.
•   WG2: Standardizes high-priority cytometric assays. It published its first ILS on the TBMNK assay and is near completion on a second ILS for CD19 CAR-T cell phenotyping and CAR expression analysis.
•   WG5: Collaborating with global organizations, it is harmonizing data and metadata standards to support AI/ML development, alongside establishing operating procedures and evaluation criteria for AI/ML systems.

Keywords: Standardization, Standards

CMLE Credit: 1.0