PhD Medical Microbiology
API - Successful optimization of pharmaceutical manufacturing process
When a pharmaceutical company faced critical challenges related to product variation during production, they turned to Emendo R&D for assistance. Emendo R&D successfully optimized the company’s outdated pharmaceutical manufacturing processes, resulting in both improved efficiency and cost-effectiveness and reduced variation.
Emendo R&D implemented a systematic approach to address the challenge of batch variation arising from an outdated pharmaceutical manufacturing process. Leveraging our scientific understanding, extensive regulatory experience and employing LEAN tools, we developed a comprehensive strategy to tackle this issue. Here is a breakdown of the approach:
Achieving Insight and Efficiency Through Structured Process Understanding
Emendo R&D employs a systematic approach, utilizing detailed process maps, optimization scope evaluation, and statistical analysis to unravel vital insights. By capturing essential information at each step, including time, resources, raw material data, parameters, and yield variation, Emendo R&D establishes a solid foundation for subsequent optimization efforts. Through the evaluation of critical factors such as target product profiles, compliance requirements, and cost considerations, the team expertly identifies knowledge gaps and prioritizes optimization efforts. Join us as we explore these three pivotal steps in achieving process efficiency and optimization.
Emendo R&D began by creating detailed process maps that captured essential information for each process step, including time, resources, raw material data, parameter, and yield variation. These maps formed the basis for subsequent optimization efforts.
The team defined the scope of optimization by evaluating target product profiles, product specifications, historical process performance, and key drivers for optimization such as compliance, regulatory requirements, safety, scrap rates, cost, and lead time.
A comprehensive assessment of process parameters was performed to identify knowledge gaps and effectively prioritize optimization efforts with focus on variation and impact on critical quality attributes. The assessment was performed on-site with operators, process specialist, compliance team and regulatory to ensure that the evaluation was considering all aspects of the process from producibility to regulatory impact.
Statical Analysis and
Root Cause Analysis:
Historical batch data was statistically analyzed along with root cause analysis for out-of-spec (OOS) and out-of-trend (OOT) observations. This data-driven approach retrofitted a design space and improved process understanding.
Emendo R&D implemented the Blackbird Smart Data Collection System to monitor and improve knowledge of process parameters, reducing the need for additional test batches and small-scale Design of Experiments (DoEs).
Statistical analysis and modeling helped define the impact of parameters on the process and guided decision-making on final process changes.
Process Optimization and Validation: Achieving Control and Sustainability
By implementing and automating key parameter monitoring through in-process controls, including pH, oxygen, metabolites, and biomass, Emendo R&D harnesses the power of simple measurements and cloud-based data analysis to significantly reduce process variability. Thoroughly collecting process parameters during earlier stages increases the success rate of test runs and validation, ensuring accurate and reliable results. Finally, the project concludes with a revision of the control strategy, guaranteeing sustainable process control that adheres to regulatory standards. Regulatory files are updated to reflect any process changes implemented during optimization. Join us as we explore these final crucial steps towards achieving heightened control, reliability, and adherence to global standards.
Appropriate in-process controls were implemented, automating the monitoring of key parameters such as pH, oxygen, metabolites and biomass through simple measurements and cloud-based data analysis. This significantly reduced process variability.
While test runs and validation were essential, thorough collection of process parameters earlier in the process significantly increased the success rate of these phases.
The project concluded with a revision of the control strategy to ensure sustainable process control. Regulatory files were updated to reflect any process changes made during optimization.
The comprehensive and structured optimization strategy of Emendo R&D has yielded very tangible results:
In summary, Emendo R&D's systematic approach to optimizing pharmaceutical API processes not only solved critical production challenges, but also resulted in significant cost savings and improved process efficiency, demonstrating the importance of data-driven optimization strategies in the pharmaceutical industry.