Virtual Fish Ecotoxicology Laboratory
Lead Participant:
SIMOMICS LIMITED
Abstract
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&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 "Virtual Fish
EcoToxicology Laboratory" 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).
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&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 "Virtual Fish
EcoToxicology Laboratory" 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).
Lead Participant | Project Cost | Grant Offer |
---|---|---|
SIMOMICS LIMITED | £493,187 | £ 295,912 |
  | ||
Participant |
||
INNOVATE UK | ||
UNIVERSITY OF YORK | £149,262 | £ 149,262 |
ASTRAZENECA UK LIMITED | £353,160 | £ 1,589 |
People |
ORCID iD |