Are we ready for the in vitro/in silico revolution in aquatic ecotoxicology?

  • Thu 15 Nov 18

    13:00 - 14:00

  • Colchester Campus

    STEM 3.1

  • Event speaker

    Dr Nic Bury (School of Science, Technology and Engineering, University of Suffolk)

  • Event type

    Lectures, talks and seminars
    School of Biological Sciences Seminar Series

  • Event organiser

    Life Sciences, School of

  • Contact details

    Dr Patrick Varga-Weisz
    01206 872318

Are we ready for the in vitro/in silico revolution in aquatic ecotoxicology?

Dr Nic Bury and Prof Duncan Bell School of Science, Technology and Engineering, University of Suffolk  

Host: Dr Tom Cameron

There are estimated to be 100,000 of synthetic chemicals in the environment. The challenge for society is to identify those that pose a risk and contribute to the biodiversity crisis we are currently witnessing.

The EU Registration, Evaluation, Authorization & Restriction of Chemicals (REACH) initiative required industry to re-evaluate the environmental risk of manufactured chemicals. It became evident from the initiative that we do not have sufficient information to make a judgement on their ecological impact for thousands of compounds. These compounds will require additional toxicity testing and as part of current legislation, this will include a large number of fish. However, It is impractical, or near impossible, to perform the number of tests required: it will take decades, cost millions of pounds and use millions of fish. Thus, we must find alternative ways to evaluate ecological risk.  

Over the last 8 years we have been assessing the versatility of a fish gill cell culture model and invertebrates to evaluate the uptake and bioconcentration of drugs, with an aim to reduce the number of fish used in these tests. More recently, we have used modelling approaches to evaluate which physiochemical properties of a compound contributes to uptake across the gill epithelium; utilised ICT scanning techniques to understand invertebrate internal anatomy in relation to bioconcentration and identified which of 24 linear and machine learning models best predict bioconcentration and used this for read-across from invertebrate to vertebrate data sets. The results are extremely promising and indicate that in vitro techniques and machine learning are tools that ecotoxicologists should explore to evaluate the risk posed by chemicals.

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