Modern toxicology can draw on a growing number of non-animal methods. Yet access to new tools does not in itself solve the challenges of safety assessment. What matters is identifying the right methods, understanding their limitations and combining evidence from different sources into a coherent strategy that supports decision-making.
This is the challenge explored by Kinga Nimz, Karolina Jagiełło, PhD, and Prof. Maciej Stępnik of QSAR Lab in an article published by the JHU Toxicology Policy Lab. Using acute inhalation toxicity as an example, the authors show why a single NAM is rarely enough to capture the response of an organism as a whole. Cell-based models may reveal tissue damage or inflammation, while in silico methods can provide additional evidence on hazard or exposure. Their real value lies in how these different elements are selected and combined.
135 methods – and the challenge of choosing between them
The range of approaches available reflects both their potential and the practical challenge involved. NAMs.Network has identified 135 methods related to acute inhalation toxicity: 102 in vitro, 25 in silico and 8 ex vivo methods.
With such a broad range of options, users need to understand more than which methods are available. They also need to know which biological domains the methods cover, which substances they are suitable for, how they have been validated and whether they can address a specific regulatory question.
This is why infrastructure that organises knowledge about NAMs and helps translate it into practical assessment strategies is becoming increasingly important. NAMs.Network supports this process by allowing users to search for methods by endpoint, application and regulatory context, and to compare their key characteristics and limitations.
From understanding a method to applying it
The next step is to turn this structured knowledge into methods that can be applied directly. QSAR models are a good example. Turning a model described in a scientific publication into a working tool may require users to reconstruct the algorithm, prepare the input data and verify its applicability domain. This can lead to differences between users and reduce the reproducibility of results.
The practical use of NAMs therefore depends on connecting structured knowledge with ready-to-use tools, standardised procedures and transparent documentation of the model, its validation, applicability domain and uncertainty.
The article’s main conclusion extends beyond inhalation toxicity: NAMs deliver the greatest value when knowledge about the methods, the tools needed to apply them and regulatory requirements work together as part of a coherent ecosystem. The next stage of development will depend not only on creating new methods, but also on how effectively existing solutions can be translated into reproducible, practical workflows that support safety assessment.
Source (JHU Toxicology Policy Lab) https://www.jhutoxicologypolicyresearch.org/tox-blog/blog77
