In silico methods for the prediction of toxicity are becoming more widely used in the field of toxicology.
Skin sensitization in silico protocol
In silico methods for the prediction of toxicity are becoming more widely used in the field of toxicology, assisting with the initial stages of risk assessment as part of the hazard identification step, where they play a critical role for substances with limited toxicological information. These computational approaches use models to predict chemical or biological properties based upon a chemical structure. The models are based on experimental datasets, structure-activity relationships, scientific literature and expert judgment, and fall into two main categories; knowledge-based systems and statistical or (Q)SAR models.
A variety of toxicity endpoints can be predicted by in silico models including mutagenicity/genotoxicity, carcinogenicity and skin sensitization, potentially reducing the need for such extensive experimental data. The use of such computational models is becoming more widely accepted as cost-effective, time-saving and accurate methods of estimating the potential toxicity of chemicals.
With such a wide use of in silico toxicology approaches across many industries, it highlights the need to develop standardized protocols when conducting toxicity-related predictions. A consortium has been assembled including representatives from international regulatory agencies, academic groups, government research laboratories in the United States, Canada, Japan, and Europe, as well as companies from major industrial sectors (e.g., pharmaceuticals, cosmetics, food and tobacco products). A general strategy paper was published by Myatt et al (2018), which further introduced the working subgroups developing in silico toxicology protocols for major endpoints. Hasselgren et al (2019) published the first endpoint specific paper last year detailing the genetic toxicology in silico protocol and the most recent paper by Johnson et al (2020) details the skin sensitization in silico protocol. This latest paper published in Regulatory Toxicology and Pharmacology presents a framework for the assessment of a major toxicological endpoint, incorporating both experimental data and in silico predications to derive an overall assessment of skin sensitization in humans.
At Broughton we use validated in silico knowledge-based systems (e.g. Derek Nexus) and statistical-QSAR software (e.g. Leadscope Model Applier) to assist with toxicity screens, hazard identification and to support read-across. Our strategy includes the use of two complementary methods for our in silico predictions in line with regulatory guidelines (ICH M7). The use of in silico models is endorsed by the US FDA premarket tobacco product application (PMTAs) and MHRA marketing authorization applications (MAAs) for electronic cigarettes.
Louise Neilson, Principal Toxicologist at Broughton is a contributing author for the “skin sensitization in silico protocol” paper, you can read the full document here.
A team of toxicologists dedicated to ENDS
Our new toxicology services division offers an experienced team for delivering Quantitative Risk Assessments, and also regulatory in vitro Toxicity Testing. This includes investment into Customised-Off-The-Shelf (COTS) in silico (Q)SAR software aligned with the company’s in-house developed toxicology software application designed for toxicology data management compliant with data integrity regulations.
To discuss how our Toxicology Services team can help you understand and reduce the health risks of your ENDS products for a regulatory submission and advance a smoke free future, contact us to arrange a meeting.