Pharmaceutical Manufacturing Solutions
Productivity and efficiency have received little emphasis in pharmaceutical product manufacturing. Nearly 25% of pharmaceutical industry expenses are incurred in product manufacturing, where waste can be as high as 50%. QbD is a best practice strategy, well suited for improving overall plant performance, reducing costs, and assuring regulatory compliance. Quality-by-Design is a best practice strategy for overall plant performance efficiency improvements and cost reductions while maintaining regulatory compliance.
In recent years, large investments have been made in IT infrastructure in an effort to improve control performance in pharmaceutical manufacturing. A side benefit of these investments is the accumulation of large quantities of raw data on a multitude of elements of the manufacturing process in data historians. Quality-by-Design can leverage this rich, highly underutilized, information asset to reveal sources of critical variability and identify strategies for significant improvements in process performance. Such Scale-up and Post-approval changes (SUPAC), if restricted to the design space, are allowed under FDA’s ICH Q8 guidelines, without requiring regulatory post-approval.
Inference for QbD is used in a pharmaceutical manufacturing environment to achieve quality-by-design in the following ways:
- Manufacturing Process Improvements. Inference for QbD provides an assortment of diagnostic tools to identify manufacturing parameters that have an influence of product quality and variation of product quality.
- Manufacturing Production Control. Using the multivariate data analysis and machine learning tools of Inference for QbD enables assembly of reliable prediction models, which can be used by plant operators for production control.
- Control of Variation in Raw Materials. A principal strategy for ensuring product quality is tight control over raw material specification. Monitoring raw material specifications often requires expensive and time consuming wet chemistry measurements. Replacing these measurements with spectroscopic methods in conjunction with multivariate calibration provides provide a more efficient means to monitor raw materials and ascertain their impact on product quality.
- Real-Time Process Monitoring. Pharmaceutical manufacturing entails a complex sequence of unit operations usually carried out in batches. Unit operations are typically monitored by process analytical technology as a time series. The trajectory of these batches from initiation to completion can be summarized into a multivariate process signature, a fingerprint. Multivariate analysis of these fingerprints and comparison to historical fingerprints of successful and failed batches provides a means to ascertain the status of a current batch in real time.