Lhasa Limited shared knowledge shared progress



27 - 31 March 2022


San Diego, California

2022 Society of Toxicology (SOT) Annual Meeting


2022 Society of Toxicology

A team from Lhasa attended the 2022 Society of Toxicology Annual Meeting, in San Diego, California, where we hosted three exhibitor-hosted sessions, presented a number of scientific posters and had a Lhasa booth within the exhibition hall. We enjoyed meeting many Lhasa members, colleagues, collaborators and friends in a face to face setting again. 

Our Exhibitor-Hosted Sessions were on the following topics:

  • Practical Application of Adverse Outcome Pathways (AOPs) and AOP Networks for Toxicity Assessment
    In this session, we discussed how to use AOPs and AOP networks to make better, faster and more cost-effective human safety decisions than current assessment practices, using animals. We also demonstrated how to apply AOPs to weight-of-evidence evaluations for ICH S1.
  • Effiris: Improving QSAR models for safety assessments through privacy-preserving data sharing – an industry perspective
    This session highlighted the benefits of embedding federated QSAR models into your toxicity assessment workflow from Lhasa and Effiris consortium member and Takeda scientist, Tomoya Yukawa. 
  • Supporting the Challenge of Nitrosamine Safety Assessment – An Industry Case Study
    In this session, attendees learnt how our Lhasa solutions can be practically applied to the challenge of nitrosamine safety assessment, this was demonstrated through a Pfizer case study – presented by Krista Dobo. 

We presented the following Scientific Posters at SOT, which are available to download from the bottom of this page:

  • Application of AOPs for Weight of Evidence Assessments: Rationalizing Evidence for the ICH S1B Guidance Addendum
  • Interrogating AOP-Wiki Knowledge As A Network
  • Updated Dermal Sensitization Thresholds derived using an in-silico expert system and an expanded Local Lymph Node Assay dataset
  • Assessment of the dermal sensitization potency of extractables and leachables using existing data and in silico methods
  • Using Privacy-Preserving Federated Learning to Enable Pre-competitive Cross-Industry Knowledge Sharing and Improve QSAR Models
  • How well do defined approaches predict the human skin sensitisation potential of previously untested chemicals?
  • How to resolve inconclusive predictions from Defined Approaches for Skin Sensitisation in OECD Guideline No. 497
  • The Role of Expert Assessment and In Silico Predictions in Determining Genotoxic Risk of N-nitrosamine Impurities
  • Collaborative Analysis of Complex Nitrosamines
  • Using Data Associated with a Developmental and Reproductive Toxicity Adverse Outcome Network to Aid Safety Assessments


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