Simplifying CPV and CPI, Accelerate Your BioPharma Product's Time to Market
The third stage of FDA’s guidance on process validation – Continued Process Verification (CPV) – states that manufacturers must provide continual assurance that their manufacturing process remains in control over time.
Establishing a plan to collect and analyze end-to-end production and process data to ensure product outputs are within predetermined quality limits is essential. Utilizing these insights to understand root cause and provide direction on actionable Continuous Process Improvement (CPI) is equally important and key to prevent failures from occurring.
The current environment of manufacturing data management systems can be complex and are likely sources of errors, can lead to long lead times for report availability, and are labor intensive. Data is collected by different groups, geographic sites, and partner organizations. Additionally, data is managed in multiple places – spreadsheets, paper-based systems, and disparate data silos.
Join Mallory Turner and Alberto Pascual for best practices on meeting CPV and CPI requirements using purpose-built software that quickly & confidently collects and transforms critical data into the requisite outputs for product lifecycle validation.
This webinar covers:
- FDA CPV expectations overview
- Capturing all critical quality and process data (CPPs, CQAs, etc.) on a batch-by-batch basis
- Managing changes to target control limits and process specifications with automatic contextualization of this data
- Seamlessly generating required outputs for CPV including control charts for trending and process capability
- Automating raw material genealogy to quickly uncover the source of variations
- Establishing a secure collaboration platform to ensure effective data management across the Sponsor/CMO networks
Mallory Turner, Sr. Manufacturing Intelligence Specialist, IDBS
Mallory Turner is a Sr. Manufacturing Intelligence Specialist at IDBS (formerly Skyland Analytics). She has a Master’s in Quantitative Research Methods / Research Methods and Statistics from the University of Denver. After graduate school she joined a Colorado startup called Aegis on their analytic consulting team for Discoverant. In her eight years working with various software in bio-pharma manufacturing, she has established customer monitoring systems and company guidelines, delivered best practices training on CPV and Investigations – as well as directly assisting in numerous customer investigations when an extra set of eyes on an issue was needed. A self-described stats geek, Mallory finds great joy in partnering with a company as they grow from their first control chart to using advance techniques to predict their quality attributes and beyond. For the last two years she has been leading PIMS implementation with customers, strategically advising on product development, and delivering demos to prospective customers.
Alberto Pascual, Director Data Science and Analytics, IDBS
Alberto Pascual is a Doctor in Bioinformatics with a long experience in Data Science and biomedical domains. Graduated in Computer Science, he received a PhD on Bioinformatics from the Autonomous University of Madrid. After some postdoc period, he joined the National Center for Biotechnology (CNB), leading a bioinformatics Research and Core facility group. He also co-founded Integromics, a Bioinformatics start up, in 2003. The company received the Frost and Sullivan European Bioinformatics Project of the Year Award for 2007. The company was acquired by PerkinElmer in 2014, when he served as a Senior Manager AI and Analytics Innovation, developing analytics solutions in Translational, Screening and Bioprocessing until September 2020. Currently he is the Director of Data Science and Analytics at IDBS (Danaher group) where he is responsible for developing and executing IDBS’ strategy on AI, Data Science and Analytics to deliver novel products and services to our customers in life sciences R&D markets.
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