Regulatory expectations for statistically underpinned Process Validation (PV) have found their way into current guidelines leading to demonstrating Established Conditions (ECs) in ICH Q12 and ICH Q8. The main goal is to develop a robust control strategy based on sound science CMC process understanding taking QbD principles into account. However, successful and accelerated biopharmaceutical process validation (Stage 1-3) remains unresolved in industrial practice. This is due to the necessity of using scale-down models, the cost-intensive setup of experiments, and the complexity due to the interactivity of a multitude of unit operations.
We believe that a strict use of innovative data science tools and sound workflows in Process Characterization Studies (PCS, Stage 1 process validation) will be key to deliver holistic, robust control strategies and accelerate the product life cycle to commercialization and safe batches in manufacturing. This includes the use of Digital Twins of different nature.
Target audience
- Designed for the biopharmaceutical and cell & gene therapy industry
- Individuals that are involved in process development, CMC, process validation, regulatory, quality assurance, MSAT and manufacturing of biopharmaceuticals
- Attendees from regulatory agencies may also benefit depending on their areas of interest and level of experience
Learning objectives
At the end of the course, the audience will be familiar with:
- How to save even more than 70% of your experiments in a PCS
- Typical steps in a PCS and how they are connected
- Sound science approaches to set up study plans along QbD principles
- Good practices in experimental Analysis and Scale Down Model Qualification
- Setting up a Control Strategy and Criticality Assessment
- Holistic Control Strategies using End to End Digital Twins
- Digital Twins: When to use stat. Vs. dynamic digital twins and Good modelling practices
- Use of models and control strategies along the life cycle and in real time