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SAP BLOG Digital Manufacturing in Life Sciences for A Quality Batch Release

SAP Blog

Kayıtlı Üye
Katılım
22 Ara 2017
Mesajlar
547
Tepki Puanı
4
Puanları
6
In the Life Sciences industry, drug product quality is of paramount importance due to patient safety. Regulatory agencies suggest a Continuous Process Verification (CPV) approach to process validation that includes continuous evaluation with relevant process variability protocols and overall monitoring of the shop floor process manufacturing performance. CPV leverages various types of in-process quality control techniques based on process know-how and material specifications. CPV involves combining a feedback loop to make necessary adjustments to the process manufacturing techniques to maintain quality control within acceptable tolerance limits. Manufacturers need to consider the critical quality attributes (CQA) and critical process parameter (CPP) for a given material and its commercial manufacturing process, along with assessing the associated risk to build a batch release strategy for a given market.

There are several factors to determine a batch release in a regulated industry such as regulatory data about change management in manufacturing sites, electronic batch record (EBR) data covering equipment, resources, and environmental conditions ; material drug product relevant data that is managed through the CPV manufacturing process and specifications and Certificate of Analysis (COA) for real time release testing (RTRT).

Today, Life Sciences manufacturers have several legacy systems like Manufacturing Execution System (MES), Data Historian, Quality Management Systems for CAPA/non-conformances, engineering change management etc., for various manufacturing process globally and data relevance to make batch release decisions which exists today in disparate systems.

There is a need for business transformation to have a higher-level system consolidation to bring data from these various islands in one place to make management by exception decisions based on risk categories, for saving cycle time which leverages results of in-process quality before lot disposition decisions. Lot disposition decisions for work in process batches, while collaborating with contract manufacturing organizations (CMOs) may have different criteria, whereas batch releases for regional markets for patient consumption may have additional constraints that needs to be considered by Market Authorization Holder (MAH).

The SAP Digital Manufacturing Insights (DMI) solution leverages Internet of Things (IoT) and SAP Cloud Platform (SCP) to provide end-to-end analytics across entire global manufacturing site operations. SAP Leonardo offers the right infrastructure to the manufacturing line of business stake holders to make strategic and tactical decisions to achieve best-in-class quality, which improves overall manufacturing process performance. SAP offers integration capabilities to capture data from multiple systems via relevant interfaces like Quality Management – Inspection Data Interface (QM-IDI) and Statistical Data Interface (QM-STI), bringing MES data into the quality system of record repository. SAP empowers quality supervisors with intuitive and pre-configured analytics to analyze global, plant-level manufacturing performance along with associated causes. SAP Digital manufacturing enables the build of key performance indicators (KPIs) for manufacturing insight and expedite problem analysis to support continuous improvement with advanced algorithms and machine learning.

Thus, the SAP Leonardo intelligent technology foundation can be leveraged to build a control strategy for CPV that can help facilitate design thinking concepts around consulting services solution based on requirements from bio-pharma manufacturers for innovative batch release. For more info, refer to SAP Digital Manufacturing Insights | Manufacturing Process Analytics.

Innovative quality batch release (QBR) seems to be a promising candidate to reimagine work aligned with new business models in the Life Science industry, but how soon will our industry leaders adopt this use case in near future? Time will tell… I am looking forward to your comments, feedback and suggestions for Life Sciences co-innovations and ideas are always welcome.

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