Validation of LC–MS Multi-Attribute Method Supporting Biopharma Process Characterization
Company Size
1,000+
Region
- Europe
Country
- France
Product
- Genedata Expressionist
Tech Stack
- Mass Spectrometry
- Automated Workflows
- Data Processing
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Innovation Output
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data-as-a-Service
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Healthcare & Hospitals
- Pharmaceuticals
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Predictive Quality Analytics
- Process Control & Optimization
Services
- Data Science Services
- System Integration
About The Customer
Merck KGaA is a major biopharmaceutical manufacturer based in Martillac, France. The company's Microbial Process Development Group is responsible for developing and producing recombinant proteins expressed in Escherichia coli and Pichia pastoris. The group includes scientists and experts in microbial processing analytics. They use mass spectrometry as a routine tool for supporting process development in recombinant protein production and are involved in developing original mass spectrometry-based approaches that enable better understanding of protein expression in microorganisms for biopharmaceutical development. Once a process is developed, it can be transferred to a manufacturing unit, where GMP specialists manage production, from pre-clinical stages through to commercial batch manufacturing of a drug substance.
The Challenge
The Microbial Process Development Group at Merck KGaA was tasked with developing and producing recombinant proteins expressed in Escherichia coli and Pichia pastoris. They used mass spectrometry (MS) as a routine tool for supporting process development in recombinant protein production. However, routine use of Multi-attribute method (MAM) in this environment meant overcoming various scientific, technological, and methodological challenges. These challenges included managing large amounts of data, producing unbiased audited results, and meeting process validation requirements. The overall production process for recombinant proteins involves multiple processing steps that are driven by defined process parameters. The characteristics of the resulting protein product must be such that the final drug substance is both safe and efficient. Studying the desired protein characteristics, then defining, monitoring, and managing critical quality attributes (CQAs) is key to success.
The Solution
The team at Merck KGaA implemented a flexible software solution with automated workflows that enabled them to address the challenges and reap the benefits of using MAM analyses routinely. They developed a peptide matching LC–MS method capable of monitoring four CQAs—oxidation, deamidation, gluconoylation, and truncation. The method was optimized to monitor the four identified CQAs, which reduced the run time from 120 minutes to just 30 minutes, quadrupling sample throughput. They also implemented an enterprise software solution (Genedata Expressionist, Genedata AG) to handle large and complex experimental MS datasets. The software enabled them to develop automated data workflows and provided full transparency throughout, with the ability to review results or export to final reports.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Case Study: Pfizer
Pfizer’s high-performance computing software and systems for worldwide research and development support large-scale data analysis, research projects, clinical analytics, and modeling. Pfizer’s computing services are used across the spectrum of research and development efforts, from the deep biological understanding of disease to the design of safe, efficacious therapeutic agents.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
Fusion Middleware Integration on Cloud for Pharma Major
Customer wanted a real-time, seamless, cloud based integration between the existing on premise and cloud based application using SOA technology on Oracle Fusion Middleware Platform, a Contingent Worker Solution to collect, track, manage and report information for on-boarding, maintenance and off-boarding of contingent workers using a streamlined and Integrated business process, and streamlining of integration to the back-end systems and multiple SaaS applications.
