(Q)SAR NON-TESTING METHODS SERIES | PART I
For registration by equivalence of pesticide technical materials, (Q)SAR modeling can support toxicological assessment. It can flag structural alerts linked to particular toxicological endpoints and provide supporting information for endpoint assessment. The European Union provides a structured framework for this assessment under Regulation (EC) No 1107/2009, while similar approaches are also used in other countries or organizations, including Australia, Brazil, Mexico, and FAO/WHO. Software can generate predictions and produce a structured report efficiently. The key issue is whether those outputs are suitable for regulatory review.
Regulatory review of a (Q)SAR report addresses three related issues: whether the regulatory assessment question is clearly defined; whether the model result can support that question; and whether the conclusion rests on an evidence base that is sufficiently robust and interpretable.
A Model Prediction Must First Address a Specific Question
When preparing a pesticide technical material registration dossier, a company may submit a (Q)SAR prediction report for a specific toxicological endpoint. The report may include model results, an assessment of the applicability domain, and supporting explanations.
Reviewers consider more than whether a prediction is positive or negative. The report should specify the question addressed by the prediction and the extent to which the result supports the assessment of the toxicological endpoint.
Model outputs must be linked explicitly to the regulatory question. A single prediction, or a limited body of information, is not usually sufficient to fully address a toxicological endpoint; expert review is required in the specific context.
A (Q)SAR report should do more than state the model result. It should explain how that result supports the question at hand.
More Models Do Not Automatically Create an Evidence Base
It is common to use more than one (Q)SAR tool and report predictions from multiple models. This approach can provide more information for comparison and help reveal differences between models.
The number of predictions alone is not the main issue in regulatory review. Reviewers need to understand why the results, considered together, support the same conclusion.
Whether multiple models produce similar or different results, conclusions should not be based on apparent agreement or disagreement alone. The results need to be assessed in the context of the regulatory question.
The value of a report does not lie in the number of model outputs in its appendices. It lies in whether the report provides a clear and appropriate response to the relevant regulatory question.
Regulatory Review Focuses on the Basis for the Conclusion
Regulatory review requires a clear link between the model output and the question the report is intended to answer. Expert review establishes this link.
A (Q)SAR report should be built around a clearly defined assessment question. Conclusions should draw on relevant information and expert review. The scope of applicability and the associated uncertainty should be described transparently.
No individual (Q)SAR prediction is necessarily sufficient to determine a toxicological endpoint on its own. Whether, and to what extent, the relevant information is used should be determined by qualified experts in the context of the case.
Expert Review Is Needed Throughout the Report Preparation Process
Expert review should not be limited to a brief summary of model results at the end of a (Q)SAR report.
In a (Q)SAR assessment report, expert review is essential throughout report preparation and conclusion development. Software can generate predictions, but turning them into technical documentation suitable for regulatory review requires expert interpretation in light of the specific regulatory question.
For registration by equivalence of pesticide technical materials, the key issue is not simply whether (Q)SAR has been used; it is whether the dossier provides a clear and appropriate response to the toxicological assessment question.
REACH24H's Perspective
(Q)SAR is an important non-testing method for the toxicological assessment of equivalence for pesticide technical materials and can generate predictions for relevant toxicological endpoints. On their own, software outputs do not establish whether a prediction is applicable to the substance under assessment, whether it addresses the specific toxicological question, or to what extent it can support a conclusion alongside existing information.
Whether a (Q)SAR report can withstand regulatory scrutiny depends less on the volume of software output than on a clear, scientifically sound rationale that meets applicable dossier requirements and addresses the specific regulatory question.
Expert review is not a restatement or compilation of software outputs. It is an expert interpretation of what the predictions mean for the specific assessment question. Its value lies in clarifying the role and limitations of each result in the dossier, turning a collection of software outputs into technical documentation that can withstand regulatory scrutiny.
REACH24H’s Services
QSAR and Read-Across for new or increased levels of impurities in a new source of technical materials or target compounds.
Global (Q)SAR Prediction & Reporting Services for Agrochemicals (EU, Brazil, Argentina, Australia, Mexico, Russia, Canada, FAO/WHO, etc.)
Weight-of-Evidence (WoE)-Based Toxicological Data Retrieval and Assessment
Rule-based and statistical QSAR models
Application of Threshold of Toxicological Concern (TTC)
Derivation of Health-Based Exposure Limits (HBELs): PDE/ADE, AI, TTC
Read-Across and chemical similarity searching
Endocrine Disruptor (ED) Assessment
Molecular Docking Simulations for Endocrine Targets
Computational Toxicology for Novel Agrochemical Discovery & Development
Global Agrochemical (Q)SAR Project Experience
REACH24H has successfully supported and submitted thousands of (Q)SAR reports for pesticide registration to regulatory authorities and international bodies across major jurisdictions—including the EU, Brazil, Mexico, Argentina, Australia, Russia, Canada, and the FAO/WHO—consistently securing official acceptance. Backed by extensive computational resources and multidisciplinary toxicological expertise, REACH24H utilizes non-testing methods (NTMs) such as (Q)SAR to assist agrochemical and pharmaceutical enterprises, as well as research institutions, throughout the screening, preliminary hazard assessment, and early development of novel active ingredients.
In addition, REACH24H has established an official partnership with Lhasa Limited, integrating world-leading in silico systems—including Derek Nexus and Sarah Nexus, widely recognized and utilized by regulatory bodies in the EU and Brazil—into its regulatory toxicology service portfolio.
REACH24H's technical team applies a broad range of regulatory-grade (Q)SAR platforms and hundreds of validated models to generate predictions across physicochemical properties, human health toxicology, ecotoxicology, and environmental fate. Every prediction and underlying model is rigorously evaluated for validity and reliability in accordance with OECD principles, with standardized technical documentation prepared using the (Q)SAR Model Reporting Format (QMRF) and (Q)SAR Prediction Reporting Format (QPRF). Furthermore, the team has accumulated deep practical experience in addressing highly complex regulatory challenges, including genotoxicity profiles, difficult ecotoxicity endpoints, and endocrine-disrupting (ED) properties.
Why Choose REACH24H
Board-Certified Toxicologists: A team of internationally certified toxicologists and regulatory modelers providing robust, defensible scientific rationales.
Proven Global Track Record: Extensive practical experience handling multi-jurisdictional (Q)SAR predictions, read-across frameworks, and integrated toxicological evaluations.
Demonstrated Regulatory Acceptance: Thousands of (Q)SAR predictions and toxicology assessment reports delivered by December 2025, maintaining consistently high official approval rates.
Extensive Software Resources & In-House Development: Access to premier global in silico platforms combined with internal technical development capabilities to address diverse regulatory needs.
Long-Standing Scientific Networks: Established communication channels with domestic and international regulatory experts, ensuring high-efficiency dossier preparation and rapid response to agency inquiries.
OECD-Compliant Reliability: Rigorous workflows ensuring all predictions satisfy strict applicability domain, mechanistic relevance, and validation requirements.
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