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VERSION:2.0
PRODID:www.eu-parc.eu
BEGIN:VEVENT
UID:69f3b14a108c3
DTSTART:20251209T130000Z
SEQUENCE:0
TRANSP:OPAQUE
DTEND:20251209T140000Z
SUMMARY: Data-driven Design of Fish Cell Line-based Reproductive Toxicity A
 ssays
CLASS:PUBLIC
DESCRIPTION:The NC3Rs hosted a webinar on Data‑Driven Design of Fish Cell
  Line‑Based Reproductive Toxicity Assays on 9 December 2025\, from 14:00
  to 15:00 CET. This free\, one‑hour online session presented key outcome
 s from the SAFE CRACK IT Challenge\, a collaborative initiative led by aQu
 aTox Solutions GmbH\, Eawag\, and the National Institute of Biology (Slove
 nia)\, aimed at advancing New Approach Methodologies (NAMs) to reduce reli
 ance on in vivo fish testing for environmental risk assessment. Participan
 ts learned about a novel computational pipeline for identifying reproducti
 ve toxicity biomarkers\, expression data generated from rainbow trout live
 r and testis cell lines\, and machine‑learning models built on historica
 l and newly generated in vitro and in vivo datasets.Target audienceThis we
 binar was particularly suited for ecotoxicologists and regulatory scientis
 ts from industry\, academia\, and government agencies involved in the deve
 lopment\, evaluation\, or regulatory acceptance of NAMs.
X-ALT-DESC;FMTTYPE=text/html:<!doctype html><html><body><p>The NC3Rs hosted
  a webinar on <em>Data‑Driven Design of Fish Cell Line‑Based Reproduct
 ive Toxicity Assays</em> on 9 December 2025\, from 14:00 to 15:00 CET. Thi
 s free\, one‑hour online session presented key outcomes from the SAFE CR
 ACK IT Challenge\, a collaborative initiative led by aQuaTox Solutions Gmb
 H\, Eawag\, and the National Institute of Biology (Slovenia)\, aimed at ad
 vancing New Approach Methodologies (NAMs) to reduce reliance on in vivo fi
 sh testing for environmental risk assessment. Participants learned about a
  novel computational pipeline for identifying reproductive toxicity biomar
 kers\, expression data generated from rainbow trout liver and testis cell 
 lines\, and machine‑learning models built on historical and newly genera
 ted in vitro and in vivo datasets.</p><p><strong>Target audience</strong><
 br>This webinar was particularly suited for ecotoxicologists and regulator
 y scientists from industry\, academia\, and government agencies involved i
 n the development\, evaluation\, or regulatory acceptance of NAMs.</p></bo
 dy></html>
DTSTAMP:20260430T194514Z
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