Long-Term Stability Prediction for Developability Assessment of Biopharmaceutics Using Advanced Kinetic Modeling

Area of Science:

• Pharmaceutical Science
• Biopharmaceutical Development
• Chemical Kinetics

Background:

• Long-term stability is critical for biopharmaceutical drug products, especially peptides in liquid formulations.
• Ensuring stability over shelf life (e.g., 2 years at 5°C and 28 days at 30°C) is essential for patient safety and therapeutic efficacy.
• Traditional stability testing is time-consuming, delaying drug development timelines.

Purpose of the Study:

• To present a case study on predicting the long-term stability of a therapeutic peptide (SAR441255).
• To evaluate the use of accelerated chemical degradation data and advanced kinetic modeling for stability predictions.
• To validate these in silico predictions against real-world, long-term stability data.

Main Methods:

• Chemical degradation of SAR441255 in various formulations and packaging was analyzed under accelerated conditions.
• Advanced kinetic modeling was employed to predict long-term stability under recommended storage conditions.
• In silico predictions were compared with analytical data obtained under long-term storage conditions.

Main Results:

• The study successfully predicted the long-term stability of the therapeutic peptide SAR441255.
• Predictions derived from accelerated data showed high accuracy when compared to subsequent long-term stability measurements.
• Stability insights were obtained within weeks, a significant acceleration compared to traditional methods.

Conclusions:

• Advanced kinetic modeling using accelerated degradation data provides accurate long-term stability predictions for therapeutic peptides.
• This in silico approach drastically reduces the time required for stability assessment, facilitating earlier clinical development.
• This methodology offers a novel and efficient strategy for biopharmaceutical stability evaluation.