Advancing Safety Standards: International Guidelines and In Silico Toxicology

In Silico Insider: Candice Johnson, PhD

International harmonization guidelines in the context of toxicity assessments are crucial for establishing consistent safety standards, ensuring efficient regulatory compliance, and streamlining product approvals across regions. There are several areas where harmonization is occurring; however, the following are selected for discussion: extractables and leachables (E&L) testing (ICH guideline forthcoming)1, UN GHS system of classification and labeling of chemicals, and ICH guidelines including M7. These domains converge on a shared goal; that is, safeguarding human health by identifying and mitigating risks associated with chemical exposures.

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In silico methods have played a role in harmonization guidelines; for example, the ICH M7 guideline specifically incorporates in silico methods for assessing the mutagenic potential of impurities in pharmaceuticals. Recently, in silico methods(consensus models based on statistical and expert-rule based approaches) have been shown to be fit for purpose for the classification and labeling of non-dangerous goods based on acute rat oral toxicity2,3,4.

Important factors facilitating the incorporation of in silico methodologies such as (Q)SAR in harmonization guidelines include well defined frameworks guiding the generation of reliable predictions of a relevant endpoint as well as the ability to communicate and increase prediction reliability through an expert review5.

The forthcoming ICH Q3E guideline on E&L assessment is highly anticipated for its significant contribution to advancing harmonization in this critical area. The guideline aims to support a harmonized approach in the evaluation of E&L and encompasses E&L study design, risk assessment and lifecycle management1. We anticipate clarification on how in silico methodologies could be leveraged to conduct safety assessments of E&L.

On this exciting note, we wish our readership best wishes for the year ahead.

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References

  1. https://database.ich.org/sites/default/files/ICH_Q3E_ConceptPaper_2020_0710.pdf
  2. Bercu, J., Masuda‐Herrera, M. J., Trejo-Martin, A., Hasselgren, C., Lord, J., Graham, J., Schmitz, M., Milchak, L., Owens, C., Lal, S. H., Robinson, R. M., Whalley, S., Bellion, P., Vuorinen, A., Gromek, K., Hawkins, W. A., van de Gevel, I., Vriens, K., Kemper, R., … Myatt, G. J. (2021). A cross-industry collaboration to assess if acute oral toxicity (Q)SAR models are fit-for-purpose for GHS classification and labelling. Regulatory Toxicology and Pharmacology, 120, 104843. https://doi.org/https://doi.org/10.1016/j.yrtph.2020.104843
  3. Gromek, K., Hawkins, W., Dunn, Z., Gawlik, M., & Ballabio, D. (2022). Evaluation of the predictivity of Acute Oral Toxicity (AOT) structure-activity relationship models. Regulatory Toxicology and Pharmacology, 129, 105109. https://doi.org/https://doi.org/10.1016/j.yrtph.2021.105109
  4. Moudgal C, Anger LT, Muster W, Nguyen R, Melnikov F, Siramshetty VB, Graham J. The application of acute oral toxicity computational models in dangerous goods classification. Toxicol Ind Health. 2023 Dec;39(12):687-699. doi: 10.1177/07482337231209091. Epub 2023 Oct 20. PMID: 37860984.
  5. Myatt, G. J. G. J., Ahlberg, E., Akahori, Y., Allen, D., Amberg, A., Anger, L. T. L. T., Aptula, A., Auerbach, S., Beilke, L., Bellion, P., Benigni, R., Bercu, J., Booth, E. D. E. D., Bower, D., Brigo, A., Burden, N., Cammerer, Z., Cronin, M. T. D. M. T. D., Cross, K. P. K. P., … Hasselgren, C. (2018). In silico toxicology protocols. Regulatory Toxicology and Pharmacology, 96, 1–17. https://doi.org/10.1016/j.yrtph.2018.04.014

Candice Johnson, PhD

Candice Johnson, PhD is a Senior Research Scientist at Instem. Dr. Johnson has co-authored several peer-reviewed publications describing the implementation of in silico approaches and methodologies for gaining confidence in in silico predictions. Her work expands into novel application of in silico approaches and supports the advancement of alternative methods. She is particularly interested in the application of computational tools to support toxicological evaluations; for example, in the assessment of extractables and leachables.

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