New therapeutic modalities play a critical role in our health and safety. Novel therapeutics may be comprised of biologically based molecules including peptides, monoclonal antibodies, and genetic materials. The quality and safety of these products can be assessed using experimental systems; however, it is important to ask whether in silico methods can add value to the analysis workflow. In silico methods have an advantage of providing a rapid screening of effects that could be used in early stages of development to triage and prioritize chemicals based on the likelihood that they may lead to the assessed effect.
In considering how in silico models could be used to support the development and quality of therapies consisting of biomolecules, we can leverage the ability of models to predict chemical reactivity. Active pharmaceutical ingredients which consist of biomolecules (biomolecule-APIs) may be exposed to leachables from container/closure systems, delivery devices or manufacturing systems. The leachables may react with the biomolecule and potentially impact the safety and/or quality of the drug product. In this context we investigated the use of in silico methods which either predict peptide reactivity, direct acting mutagenicity (as a surrogate for reactivity with a DNA or RNA containing API) or assigns a reaction domain (description of the nature by which a covalent interaction may or may not occur) to predict the potential chemical reactivity of leachables in an extractables and leachables (E&L) database. The prevalence of potentially reactive chemicals was low with 16.7% of the set of 801 leachables predicted as reactive based on assignment to a domain; whereas, 16.1% and 5.4% were considered reactive based on the peptide reactivity model and direct acting mutagenicity alerts respectively. To validate the use of such models in early screening, we selected 22 representative E&L chemicals and experimentally determined the reactivity of these chemicals with insulin glargine. The peptide reactivity and reaction domain models were used to predict the observed reactivity. A consensus approach based on the model results, was found to be conservative; that is, most of the reactive chemicals were flagged for reactivity. Factors such as steric hindrance was identified as an important consideration for expert review.
Leachables often exist at very low concentration, and a flag by the in silico models may not necessarily translate into a safety or quality issue. As such, a workflow, which entails a review of model predictions to ensure reliability of the prediction, as well as product quality and safety attributes could be referenced to determine whether follow-up studies are necessary.
This work was conducted by members of the Biomolecule Reactivity Consortium: a group of experts with diverse experience and expertise in the assessment of extractables and leachables. A manuscript is being prepared for publication. Click here to access a recorded presentation on this work which was presented at the E&L USA 2022 conference.
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