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Integrating ReproTracker into DART AOP Frameworks for mechanism-based teratogenicity assessment

Lhasa Limited Principal Scientist, Alun Myden, presented in webinar hosted by Toxys on the use of DART AOP frameworks for mechanism-based teratogenicity assessment.

 

Testing for developmental toxicity according to the current guidelines requires large numbers of animals. In addition to the ethical considerations and high costs of these traditional animal models, the outputs provide limited mechanistic understanding for any observed toxicity. Therefore, there is a growing demand for new approach methods (NAMs) to assess the human-relevant developmental toxicity potential of substances more accurately and more efficiently.

To help drive the evolution of developmental toxicity testing through the use of NAMs, a research collaboration was undertaken between Toxys and Lhasa Limited. Toxys developed the ReproTracker assay, a unique in vitro human-based reporter assay that can identify the teratogenic potential of new pharmaceuticals and chemicals and signify the outcome of in vivo test systems. To contextualise assay results for developmental toxicity, Alun Myden on behalf of Lhasa discussed the development of a predictive DART adverse outcome pathway (AOP) framework contained within our in silico AOP solution, Kaptis.

In this webinar, through specific examples, presenters illustrated how:
  • The information from advance outcome pathway (AOP) networks complement the in vitro human based assay ReproTracker;
  • This can enhance both industrial and regulatory confidence and reduce reliance on animal models;
  • This supports decision making for chemical safety through contextualised assay results and mechanistic insight.
Webinar presenters:

Amer Jamalpoor, CSO at Toxys
Introduction to ReproTracker as a new approach methodologies (NAMs) assay that reliably classifies chemicals according to their DART profiles

Alun Myden, Principal Scientist at Lhasa Limited
Introduction to the Lhasa predictive DART AOP framework Kaptis to enhance decision making when using NAMs.