In Silico Assessment of Biomolecule Reactivity with Leachables

Area of Science:

• Pharmaceutical Science
• Computational Chemistry
• Drug Safety

Background:

• Leachables from pharmaceutical packaging can interact with biomolecule Active Pharmaceutical Ingredients (APIs), affecting drug safety and quality.
• Monoclonal antibodies (mAbs), peptides, and RNA are susceptible to degradation or modification by reactive leachables.

Purpose of the Study:

• To evaluate the utility of in silico models for screening extractables and leachables for reactivity with biomolecule APIs.
• To identify chemical classes of leachables most likely to be flagged by in silico screening methods.

Main Methods:

• Application of in silico models to known leachable datasets to identify reactive chemical and functional classes.
• Validation of selected in silico methods using experimental data of leachable interactions with insulin glargine.

Main Results:

• In silico models flagged functional classes such as antimicrobials and colorants, and chemical classes including epoxides, acrylates, and quinones.
• The sensitivity of multi-method in silico screening ranged from 80%-90%, with specificity between 58%-92% when tested against experimental data.

Conclusions:

• In silico models offer a viable preliminary screening tool for assessing leachable-biomolecule reactivity.
• A proposed workflow integrates computational modeling and quality risk management for enhanced drug safety assessments.