One of the biggest cost items in the registration process is tests. Read-across and QSAR reduce this cost significantly when used with appropriate justification.
Read-across is the adaptation of data of articles of similar structure; QSAR, on the other hand, is feature prediction with computational models. KKDIK and REACH allow these methods to reduce animal testing; However, solid scientific justification is a must for acceptance.
ONAY Mühendislik specializes in SAR/QSAR and read-across based data generation and saves money by closing data gaps without testing.
Legal Basis for Alternative Methods
Chemical legislation requires vertebrate animal testing to be a last resort. For this reason, read-across, category approach and computational estimation methods are not only cost tools, but are ways prioritized by the legislation. It is expected that the file shows that alternative methods have been evaluated before testing.
Establishing Read-Across Justification
The decisive factor in the read-across approach is the scientific justification of the similarity between the source substance and the target substance. Structural similarity alone is not enough; It should be demonstrated that the metabolic pathways, physicochemical properties and toxicological mechanism of action are similar. A poorly justified read-across causes the file to be rejected and wastes time.
Proper Use of QSAR Models
Computational prediction models are valid provided the item falls within the model's applicability area. The data set on which the model was trained, prediction reliability, and whether the item falls within the applicability area should be reported. Estimation results presented without this information have no evidence value in the file.
Weight of Evidence Approach
When a single alternative method is not sufficient, a weight of evidence approach is used where information from multiple sources is evaluated together. Literature data, results from similar substances, in vitro studies, and computational predictions are presented together. In this approach, the reliability of each piece of evidence and how they support each other should be openly discussed.
When Testing Is Inevitable
In some hazard classes and high tonnage bands, alternative methods are not considered sufficient. In these cases, the test plan needs to be presented and justified in advance. Overcommitting to alternative methods and realizing the need for testing too late is a risk that can shift the schedule by a year; Therefore, data gap analysis should be performed at the earliest possible stage.
Reporting Read-Across and QSAR Results
Read-Across and QSAR results must be submitted with justification when filing. For read-across, the similarity hypothesis, for QSAR, the model applicability domain and prediction reliability are written explicitly. Read-Across and QSAR outputs without a justification do not have evidence value in the file and lead to a deficiency claim, even if the result is correct.
Related pages
Contact ONAY Mühendislik for your process.
Official full text of the regulation: KKDIK Regulation - Official Gazette.