Improving the Performance and Yield using open source based advanced modeling frameworks – Pharma/ Life Science
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- 17/08/2023 - 10:00 am - 10:45 am EDT
Pharma/life-science industries have been implementing the best practices of statistical techniques to ensure the quality standards are met. Being one of the most stringent sectors, circled with compliances and regulations, they have been the early adopters of the latest technologies to implement the adv. Modeling tech-stack. Driven by bulk-batch operations, this sector is cursed with the challenge of limited data, be it process or quality. Such challenges have given us the realization that right modeling approach is far more important than the platform capabilities itself. These limitations have also broadened the horizons to unleash the potential of open-source platforms for the development of advanced modeling methodologies to address the challenges of quality control, batch-to-batch variations, batch rejections and others.
In this webinar, we shall focus on advanced modeling and optimization frameworks, which has shown the potential to improve the performance and yield of the batch processes. These frameworks developed using open-source languages such as python, R, are known to address the batch-related challenges, even if the processes have limited historical data for modeling. Such frameworks empower organizations to process and model the data for such highly constrained operational conditions in order to realize reliable and high-fidelity outputs.
Key areas to cover:
- Hybrid Modeling for process optimization
- Quality optimisation
- Batch-to-Batch Variations
- Sustainability Metrics – Energy / Assets / Process
- Leveraging adv. modeling approaches
- Yield improvement
Who should attend:
- Production Engineers
- Product Development Scientists
- Data Analysts
- Digitalization leads from Lab, Pilot and Commercial production