BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ChamberMaster//Event Calendar 2.0//EN
METHOD:PUBLISH
X-PUBLISHED-TTL:P1H
REFRESH-INTERVAL:P1H
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
DTSTART:20070101T000000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:Eastern Daylight Time
END:DAYLIGHT
BEGIN:STANDARD
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
DTSTART:20070101T000000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:Eastern Standard Time
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261110T120000
DTEND;TZID=America/New_York:20261110T130000
X-MICROSOFT-CDO-ALLDAYEVENT:FALSE
SUMMARY:CYTO U Webinar: Bridging the Gap for AI in Medicine: NIST Consortium Approach to Standardizing Flow Cytometry and Data Harmonization
DESCRIPTION:Register: https://learning.isac-net.org/products/bridging-the-gap-for-ai-in-medicine-nist-consortium-approach-to-standardizing-flow-cytometry-and-data-harmonization\n\nBridging the Gap for AI in Medicine: NIST Consortium Approach to Standardizing Flow Cytometry and Data Harmonization a CYTO U Webinar Presented by Paul C. DeRose\, Lili Wang\, and Yu "Max" QianWEBINAR SUMMARYRecent 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:\n 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.\n 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.\n 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.
X-ALT-DESC;FMTTYPE=text/html:Register: https://learning.isac-net.org/products/bridging-the-gap-for-ai-in-medicine-nist-consortium-approach-to-standardizing-flow-cytometry-and-data-harmonization
Bridging the Gap for AI in Medicine: NIST Consortium Approach to Standardizing Flow Cytometry and Data Harmonization a CYTO U Webinar Presented by Paul C. DeRose\, Lili Wang\, and Yu "\;Max"\; Qian
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:
&bull\; \; 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.
&bull\; \; 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.
&bull\; \; 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.
LOCATION:
UID:e.4653.1643700
SEQUENCE:3
DTSTAMP:20261104T105402Z
URL:https://internationalsocietyforadvancementofcytometryisac.growthzoneapp.com/eventcalendar/Details/cyto-u-webinar-bridging-the-gap-for-ai-in-medicine-nist-consortium-approach-to-standardizing-flow-cytometry-and-data-harmonization-1933862?sourceTypeId=Hub
END:VEVENT
END:VCALENDAR