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Pharmaceutical supply security: Using a data-driven approach to solve out-of-specification issues
A new internal customer success story from Lundbeck highlights how JMP helped solve a complex quality issue that threatened the supply of a long-established pediatric epilepsy medicine. By combining measurement system analysis, design of experiments, and predictive modeling, Senior Tablet Specialist Jacob Paduan identified the root cause of an out-of-specification issue, avoided future failures, and helped ensure uninterrupted access to the medicine for patients who depend on it.
After more than 20 years of successful production, batches of the medicine began failing particle-size quality tests, even though all raw materials and manufacturing processes remained within specification. Traditional investigations failed to identify a cause, prompting Paduan to examine the measurement system itself. Using JMP, he discovered that a significant portion of the variation was coming from the measurement process rather than the product.
By building statistical models that linked raw material measurements to finished product performance, Paduan established new specification limits that would ensure future batches met regulatory requirements with high confidence.
Paduan explains how JMP enabled him to tackle a highly complex manufacturing challenge, and the success story shows how subject matter experts can use JMP to investigate variability, make faster decisions, and solve critical business problems without relying on lengthy investigation cycles.
Key Takeaways
- Lundbeck resolved a critical out-of-specification issue affecting an epilepsy medicine.
- Measurement system analysis revealed that measurement variation was a major contributor to the problem.
- Advanced modeling established robust specification limits to prevent future failures.
- Subject matter experts performed sophisticated analyses without specialist statistical support.
- The solution protected product supply and ensured continued patient access.
ROI Highlights
- Saved approximately one year of investigation time.
- Prevented potential product stockouts.
- Avoided future recurring quality investigations.
- Accelerated root-cause identification and decision-making.
- Increased employee productivity and self-sufficiency through data-driven problem-solving.
