Press Room

IFPAC 2023

Sunday, June 04, 2023 - 00:00
Wednesday, June 07, 2023 - 00:00
Location: Maryland, USA

Hovione is present at the International Forum Process Analytical Technology (IFPAC), a forum that brings the latest trends and real-life applications in the fields of Quality by Design, Process Analytical Technology, Emerging Technologies, Quality Metrics, Continuous Manufacturing and Process Control applications for the pharmaceutical industry, biotechnology, generic, chemical and related industries.



Hovione experts share their knowledge at IFPAC® - 37th International Forum Process Analytical Technology
June 4-7, 2023 | North Bethesda, Maryland (Washington D.C.)


June 6: Grand Ballroom G | 4:50 PM - 5:15 PM
Part of session: Recent Developments to Realizing Continuous Manufacturing
Presentation Title: Use of Statistical Process Control to drive process improvements in continuous manufacturing
Primary presenter: Fernando Barros


June 7: Grand Ballroom C | 7:50 AM - 12:00 PM
Session: Defining Incentives and Business Cases for PAT - Defining the Boundaries between Batch & Continuous Manufacturing
Chair: Anthony Tantuccio


June 7: Glen Echo Conference Room | 11:10 AM - 11:35 AM
Part of session: Enhanced Analytical Approaches & Modeling for Process Optimization
Presentation Title: A template for investigating NIR spectroscopy-based deviations
Primary presenter: Fernando Barros


June 7: White Flint Amphitheatre | 1:05 PM - 5:40 PM
Part of session: Continued Process Verification (CPV) - Practices, Challenges and Opportunities
Presentation Title: Enhance Spray Drying CPV using MVDA
Primary presenter: Tiago Porfirio


One approach to enhancing Continued process verification (CPV) is through the use of multivariate data analysis (MVDA), which allows for the identification of correlations and patterns between process parameters and product quality attributes. MVDA involves the analysis of multiple variables simultaneously, allowing for a comprehensive understanding of the process and its impact on product quality. By analyzing data from multiple sources, including automated control systems and quality control testing, MVDA can help identify the critical process parameters (CPPs) and critical quality attributes (CQAs) that are most strongly correlated with product quality. This approach can significantly improve process efficiency and product quality while reducing the risk of product failure, reprocessing and rework. Moreover, MVDA provide insights into potential causes for process deviations, facilitating the development of corrective actions. This proactive approach to CPV helps to ensure that the process remains within established control limits, minimizing the risk of non-compliance. This work will show how the integration of MVDA into CPV in a spray drying process can significantly enhance process control and product quality by leveraging multivariate data analysis.



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