NAMs (New Approach Methodologies)
NAMs are often defined as any technology, methodology, approach, or combination thereof that can provide information on chemical hazard and risk assessment without the use of animals, including in silico, in chemico, in vitro, and ex vivo approaches. Thus, NAMs reduce animal testing while increasing robustness, throughput and providing a mechanistic understanding of chemical modes-of-actions, in accordance with the Next Generation Risk Assessment (NGRA) principles.
Based to our extensive experience in the toxicological evaluation of substances and alternative methods (read-across, QSAR methods, in vitro/ex vivo/ in chemico testing) we can provide advice for a strategy that will avoid the use of animal testing to the extent that is possible at the moment while achieving regulatory acceptance.
Read-across
Read-across is a valuable technique used in chemical safety assessments to fill data gaps for a chemical of interest by using information from similar chemicals that have been previously tested. By integrating also in vitro/in chemico testing as well as QSAR predictions, read-across can help reduce the need for animal testing and provide valuable information on the mode of action, potential hazards and risks associated with a chemical.
To ensure the quality of the read-across approach, we follow the principles outlined in the Read-Across Assessment Framework (RAAF) developed by the European Chemicals Agency (ECHA). The RAAF provides a systematic approach for conducting read-across assessments and helps ensure that the resulting predictions are reliable and scientifically sound. It includes a prove of chemical and biological similarity, toxicokinetic behavior, the underlying mode of action and also is taken into account the remaining uncertainty of this approach, thereby making this approach usable for hazard assessment.
We can offer an extensive read-across expertise and support to clients who need to conduct chemical safety assessments. Our services can include data collection and analysis, assessment of the quality of the available data, identification of suitable analogues (also identified by QSARs), development of a read-across justification that meets the requirements of regulatory agencies.
By working with us, clients can benefit from our expertise in read-across and our commitment to providing high-quality, cost-effective services that help them meet their regulatory obligations while minimizing the need for animal testing.
QSARs
Quantitative Structure-Activity Relationships (QSARs) are a further method to account for data gaps in chemical safety assessment. QSARs are theoretical, computerised models that can predict the physicochemical, biological, and environmental fate properties of substances from their chemical structure. The most frequently used Tool for the application of QSARs is the OECD QSAR Toolbox but also other programs are often used like the VEGA Tool or ToxTree with decision tree approach. Currently it can be distinguished between two types of models, statistical models (to which the above-mentioned programs belong) and expert-knowledge based models. Each one alone cannot be used as stand-alone data gap fulfillment, however, the combination of both types of models and a detailed justification including the suitability of the applicability domain of the model and also the uncertainties that are correlated with this approach can be used to help avoid unnecessary testing, including animal testing, if the information obtained is sufficient to fulfil the information requirements. Our experts can help you identify an adequate QSAR result that meets the conditions set out in REACH Annex XI, Section 1.3, and provide the proper documentation to support your justification.
We can use QSARs to predict some simple properties and endpoints reliably. However, for higher-tier endpoints, QSARs can only give preliminary indications on the type of toxicity the substance may exhibit. Therefore, we use QSAR results as part of a weight of evidence approach or an integrated testing strategy. We can help you run several available QSAR models for the endpoint, verify that your (target) substance falls within the applicability domain of the model, and submit the proper documentation to support your justification.
Our experts have advanced scientific expertise in understanding the computational models of QSARs, the use of, justification for, and documentation of such data. We ensure that the QSAR model used is applicable to your query chemical, and relevant for regulatory purposes. Our services provide you with reliable QSAR results in a defined NAM strategy that meet the information requirements and chemical safety assessment regulations.
Weight of Evidence Approach
A weight of evidence (WoE) approach is a familiar concept found in scientific and regulatory literature. It is generally understood as a method for decision-making that involves consideration of multiple sources of information and lines of evidence. According to ECHA the weight of evidence approach means that you use a combination of information from several independent sources to give sufficient evidence to fulfill an information requirement:
Published literature
Read-across from chemical analogues
(Q)SAR predictions
Data from existing studies
In vitro studies
Epidemiological data/human experience
The European authorities also require several other information such as a minimum, two separate study records for the property – also when using textbook values. One single value from a secondary data source is not sufficient as a weight of evidence, an expert assessment for the reliability, relevance, adequacy of the available data and judge whether the combined evidence is enough to draw a conclusion about the property or effect of the substance, a detailed documentation of all information used, all steps carried out in the evaluation process and all conclusions drawn, i.e., reliability, relevance and conclusion for each study (line of evidence).
We can provide an overall WoE approach and also assist our clients with parts of the WoE in the following steps starting with the identification of data needed, gathering of data, evaluation of the reliability and relevance of each line of evidence as well as the comprehensive documentation as required by the European authorities.