The application of in silico approaches to food chemical assessments

Hazard identification and characterization for food safety assessment (e.g., flavourings, food contact materials, food contaminants) takes advantage of the availability of relevant data in appropriate databases as well as the application of in silico toxicology methods including category formation (i.e., chemical grouping), read-across, expert rule-based systems (i.e., structural alerts), and statistical-based systems (i.e., Quantitative Structure-Activity Relationship ((Q)SAR)).

Examples of applications of such in silico approaches include the use of QSAR and read-across for the prediction of genotoxicity in the contexts of flavourings¹ and pesticide residues² as discussed by the European Food Safety Authority (EFSA). QSAR and read-across are also valuable approaches for priority setting and for a preliminary toxicological assessment within the risk assessment of food contact materials as mentioned by EFSA in relation to impurities and reaction and degradation products referred to as NIAS, Non-intentionally added substances³. Application of structural similarity considerations for the prediction of toxicity may also be incorporated into the safety assessment of food contact substances and their constituents according to the US Food and Drug Administration Center for Food Safety and Applied Nutrition (US FDA CFSAN)⁴.

While robust (Q)SARs are available for an assessment of mutagenic chemicals, read-across based on structural analogs may be used to computationally assess additional endpoints including genotoxicity and carcinogenicity. The EFSA OpenFoodTox database (i.e., the chemical hazards database by EFSA) may be used as a source of analogs when dealing with food-related chemicals. The search for analogs may also be enriched by chemicals belonging to other databases. Indeed, the Leadscope toxicity database contains study data for over 200,000 chemicals and includes structures (and link to the original data) contained in the EFSA OpenFoodTox database. Structural searches by similarity or powerful substructure searches may then be used to identify relevant analogs and support food safety assessments.

If you would like to discuss the use of computational methods in food chemical assessments, please contact info@instem.com.

Authors: Candice Johnson, PhD, Senior Research Scientist for Instem & Arianna Bassan, PhD, Principal Consultant at Innovatune

References

1. EFSA Panel on Food Additives, (FAF), F., Younes, M., Aquilina, G., Castle, L., Fowler, P., Frutos Fernandez, M. J., Fürst, P., Gundert-Remy, U., Gürtler, R., Husøy, T., Manco, M., Mennes, W., Moldeus, P., Passamonti, S., Shah, R., Waalkens-Berendsen, I., Wölfle, D., Wright, M., … Engel, K.-H. (2021). Scientific Guidance for the preparation of applications on smoke flavouring primary products. EFSA Journal, 19(3), e06435. https://doi.org/https://doi.org/10.2903/j.efsa.2021.6435
2. EFSA Panel on Plant Protection Products, & their Residues (PPR). (2016). Guidance on the establishment of the residue definition for dietary risk assessment. EFSA Journal, 14(12), e04549. https://doi.org/https://doi.org/10.2903/j.efsa.2016.4549
3. EFSA Panel on Food Contact Materials Enzymes, F., & (CEF), P. A. (2016). Recent developments in the risk assessment of chemicals in food and their potential impact on the safety assessment of substances used in food contact materials. EFSA Journal, 14(1), 4357. https://doi.org/https://doi.org/10.2903/j.efsa.2016.4357
4. US FDA CFSAN, Guidance for Industry: Preparation of Food Contact Substance Notifications (Toxicology Recommendations). https://www.fda.gov/regulatory-information/search-fda-guidance-documents/guidance-industry-preparation-food-contact-substance-notifications-toxicology-recommendations