Supporting Decisions
Encoding approaches to help toxicologists interpret, combine and reason between NAM evidence to reach meaningful conclusions.
Weight of evidence approaches and Integrated Approaches to Testing and Assessment (IATA) require toxicologists to pull together large quantities of data, reason between disparate lines of evidence, and reach conclusions on hazard, potency, exposure, and risk — all while evaluating confidence. Even with all the evidence to hand, this can be a daunting task.
At ToxComponents we understand the challenge. Interpreting complex NAM outputs, understanding how different evidence types relate to one another, assessing relevance and reliability, and evaluating coverage against the toxicity endpoint of interest are all difficult problems. Our philosophy is that software should augment the expert toxicologist, not attempt to replace them.
We build transparent, interpretable software tools that support safety decisions — encoding reasoning frameworks that help you structure, weigh, and document your evidence.
NAM Data Interpretation
New approach methods produce complex, high-dimensional data — from transcriptomic profiles to high-content imaging. Interpreting these outputs and extracting meaningful signals relevant to toxicity requires specialist methods.
At ToxComponents we develop approaches to translate NAM data into interpretable evidence that can feed directly into weight-of-evidence and IATA frameworks.
QSAR prediction interpretation
QSAR model predictions are powerful but must be used with care. Understanding applicability domain, reliability, and how predictions from multiple models relate to one another is essential for credible safety assessment.
We are building tools that surface this information clearly, helping toxicologists make informed, defensible decisions when incorporating QSAR predictions into their assessments.
WoE decision support
Weight of evidence is not simply tallying positives and negatives. It requires structured reasoning that accounts for the relevance, reliability, and coverage of each line of evidence against the endpoint of concern.
At ToxComponents we encode established WoE frameworks into software tools, providing toxicologists with transparent, auditable decision support that scales from screening to full regulatory submission.
References
Cayley AN et al. Development of a network of carcinogenicity adverse outcome pathways and its employment as an evidence framework for safety assessment. ALTEX. 2023;40(1):34-52. doi: 10.14573/altex.2201311. PMID: 35575642.
Brescia S et al. Risk assessment in the 21st century: where are we heading? Toxicol Res (Camb). 2023 Jan 10;12(1):1-11. doi: 10.1093/toxres/tfac087. PMID: 36866215; PMCID: PMC9972812.
Cayley A, Fowkes A, Williams RV. Important considerations for the validation of QSAR models for in vitro mutagenicity. Mutagenesis. 2018;34(1):25-32. doi: 10.1093/mutage/gey034.
Honma M et al. Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project. Mutagenesis. 2018;34(1):3-16. doi: 10.1093/mutage/gey031.
Barber C et al. Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained. Regulatory Toxicology and Pharmacology. 2016;76:7-20. doi: 10.1016/j.yrtph.2015.12.006.