Quality by Design (QbD) Framework for Manufacturing Peptide-Drug Conjugates

Mohammad Ali Riaz

Abstract: A unified computational Quality by Design framework integrates kinetic modelling, computational fluid dynamics, and interpretable machine learning to define a risk-based design space for peptide drug conjugate manufacturing. The kinetic model, parameterized from aggregated literature, yields an activation energy of 52 kJ mol^-1 for maleimide cysteine conjugation and reproduces observed rates of 0.5 L mol^-1 min^-1 at 25 °C and pH 7.4, enabling prediction of conversion times where 98% conversion is reached in roughly 18 minutes at pH 7.4 compared to roughly 40 minutes at pH 6.5, and aggregated degradation behavior with a combined half-life of approximately 14 hours at pH 7.4 and 37 °C. CFD simulations of a microfluidic T mixer with 200 μm channels report mixing indices exceeding 0.95 within milliseconds, reaching 0.95 in 2.3 ms at 50 μL min^-1, and Damkohler numbers remaining below 0.1 with a maximum of approximately 0.08 for flow rates up to 500 μL min^-1, supporting a numbering up scale up strategy while noting Newtonian and boundary condition assumptions. An XGBoost surrogate trained on literature formulation data predicts PLGA microsphere particle size and encapsulation efficiency with RMSE values near 12 nm and 3.5%, respectively, and SHAP analysis ranks sonication amplitude with a mean SHAP value of approximately 14.2 nm and polymer concentration with a mean SHAP value of approximately 9.5 nm as dominant drivers. These mechanistic and data driven outputs are mapped to ICH Q8 through Q10 concepts to set allowable ranges for temperature, reaction time, flow rate, sonication energy, and polymer concentration, and to specify PAT and SPC strategies for lifecycle management. Limitations and targeted next steps including bench kinetics, pilot mixing validation, PAT deployment, and incremental ML retraining are identified to reduce uncertainty and enable regulatory engagement.

Keywords: Quality by Design, peptide drug conjugates, maleimide thiol conjugation, multi pathway kinetics, computational fluid dynamics, XGBoost, SHAP, ICH Q8, process analytical technology, design space

How to Cite?: Mohammad Ali Riaz, "Quality by Design (QbD) Framework for Manufacturing Peptide-Drug Conjugates", Volume 15 Issue 8, August 2026, International Journal of Science and Research (IJSR), Pages: 974-982, https://www.ijsr.net/getabstract.php?paperid=SR26723215912, DOI: https://dx.doi.org/10.21275/SR26723215912

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