IN SILICO ECOTOXICOLOGY


AN INTRODUCTION TO ECOTOXICOLOGICAL PRINCIPLES AND METHODS FOR PREDICTING HAZARD AND FATE WITHOUT RESORTING TO EXPERIMENTAL STUDIES

Trainer
Paul THOMAS


Paul THOMAS, PhD, ERT

President, Model Developer and Expert Ecotoxicologist

Email: paul.thomas@kreatis.eu

Trainer
Franklin BAUER


Franklin BAUER, PhD

QSAR Model Developer and Chemist

Email: franklin.bauer@kreatis.eu

Trainer
Pascal BICHEREL


Pascal BICHEREL, MSc

QSAR Model Developer and Ecotoxicologist

Email: pascal.bicherel@kreatis.eu


Ecotoxicologists, Regulatory affairs specialists,
environmental risk assessors, Product stewards,
REACH consultants


Courses held at KREATiS offices,
by video-conference (e.g. Microsoft Teams or Zoom)
or at any location of your choice*



1 day



1,100 € excl. VAT per participant and per day

*for locations chosen by the client, travel costs must be included in the total price

OBJECTIVES

► Grasp the principles of ecotoxicology which can be predicted by AI tools.
► Discover QSAR predictions and other in silico methods for obtaining critical physicochemical and ecotoxicological endpoints.
► Learn to assess the reliability of predictions derived using the in silico methods covered.
► Learn to generate regulatory formats for prediction reports for regulatory submission of the Read-Across and QSAR results.

PROGRAMME
Part 1

A background understanding to ecotoxicological hazard assessment and related physico-chemical properties

Part 2

► Introduction to QSARs and alternative (in silico) methods in ecotoxicology.
► Overview of in silico tools (EPIWIN/ECOSAR; iSafeRat, VEGA, OPERA, TEST…) and functionalities.

Part 3

Read-Across and QSAR predictions for:
► Critical physico-chemical endpoints
► Ecotoxicological and environmental endpoints
► Ecotoxicological and environmental endpoints
► Training participants can choose the endpoints and the chemical structures to be used for specific case studies if provided in advance.

Part 4

Understanding Read-Across/QSAR prediction report formats and their validation :
► Generation of prediction reports which could be used for regulatory purposes.