<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-08-26T13:36:10Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/DEDE98E0-255D-4A8C-9907-265218240930" ns1:id="DEDE98E0-255D-4A8C-9907-265218240930"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A150BC58-6A5F-42E4-9A31-C6D793A76518" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6AF47C9C-27BB-49E2-917A-685C250508C5" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C9B67E11-94C7-40CF-83A1-8DCEA291BF2E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A150BC58-6A5F-42E4-9A31-C6D793A76518" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/0CEBDF7D-2D7C-4B10-A796-3DAA4D23977A" ns1:rel="FUND" ns1:start="2016-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">102519</ns2:identifier></ns2:identifiers><ns2:title>Virtual Fish Ecotoxicology Laboratory</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>All new active pharmaceutical ingredients must undergo an environmental risk assessment (ERA) before being

authorised. Currently tens of thousands of fish are used worldwide as part of API ERAs. Development of

predictive in silico models has the potential to significantly reduce animal use (3Rs) and reduce R&amp;amp;D costs

around the ERA of pharmaceuticals. These models, when combined with recently developed in vitro bioassays,

can be used to determine up front risk. Evidence based, in silico approaches that predict the movement of an

API from the patient to aquatic systems and the subequent impacts on the ecosystems. The &amp;quot;Virtual Fish

EcoToxicology Laboratory&amp;quot; will be a transparent, evidence-based system of interlinked mathematical models,

combined with extensive datasets, that will determine risk to both apical end-points (e.g. impacts on fish

reproduction and growth) and non-apical end-points (e.g. effects on behaviour).</ns2:abstractText></ns2:project>