OSD
Tackling assay variability in liquid vials to achieve product robustness
Assay variability in liquid vials is a persistent challenge in parenteral drug development, often leading to out-of-specification (OOS) results, delayed timelines, and increased costs. Recipharm addresses this issue with ReciPredict, an advanced Quality by Design (QbD) and predictive analytics platform that applies machine learning to identify and control the root causes of assay variability.
Key insights:
- Common challenges of variability include API weighing inaccuracies, excipient variabilities, fill homogenisation issues, and assay sensitivity methods.
- Traditional troubleshooting often fails due to isolated analysis of parameters.
- ReciPredict enables a holistic, model-driven approach
- Targeted interventions such as optimised dilution step, adjusted filling speeds, and refined API dispensing led to the complete elimination of sporadic OOS events.
- Quantitative impact: OOS results reduced from 2.37% to 0.00%.
Why it matters:
By leveraging historical data and predictive modelling, Recipharm helps pharmaceutical companies achieve robust, reproducible manufacturing outcomes without additional experimental trials.
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