24th - 25th April 2012

Hotel Palace Berlin

AGENDA

Day One24th April 2012

08:00

Registration and Refreshments

08:55

Chair's Opening Remarks

Andreas Schneider, Vice President Life Science Alliances, Roche Diagnostics & Co-Chair Global PAT Data Management Team, ISPE Switzerland

09:00

Lessons Learnt from the FDA QBD Pilot Programme

Case study: Merck Serono

Dr. Pascal Valax, Group Head, Biotech Process Sciences, Merck Serono S.A Switzerland

09:40

Building Quality Earlier in The Process

Fully optimising processes by implementing QbD earlier in development

Moving away from empirical approaches to process design which are fundamentally contradictory to QbD
Successfully building QbD earlier into process development and defining process steps
Developing robust processes earlier in the development timeline and ensuring processes stay robust later in the development trajectory

Dr. Alessandro Butte, Head of DSP, Lonza Switzerland

10:20

Using a Criticality Assessment Approach to Assign Criticality and Linking Those Decisions to Registered Details

Approaches will be illustrated via a small molecule API case study

Assessing, detectability, severity and probability
Using scorability to decide what's critical and what needs to be filed for regulatory review

Dr. John R Donaubauer, Director, Scientific Affairs Development Sciences Process R&D, Abbott USA

11:00

Networking and Refreshment Break

11:30

Using a Clearly Articulated Control Strategy to Respond to Regulatory Expectations

Clarifying regulatory uncertainty and successfully filing to satisfy regulatory QbD expectations with a clearly defined control strategy

When is testing actually required? Industry vs. regulatory views on product testing
Testing quality into products vs. using a control strategy as a confirmatory step for the normal process performance
Knowing how to implement a clearly articulated control strategy and using the correct QbD terminology in the right format
Fully articulating the types of controls and locations, i.e. release tests - to model based controls using a design space
Clearly demonstrating what is controlled, how, and where
Providing scientific rationale and justification for each control

Dr. Gawayne Mahboubian-Jones, Program Head - Excellence in Science and Design, Philip Morris International Switzerland

12:10

Improving Process Understanding

Evaluation of PAT tools for monitoring and control of a PER.C6® based process

Use of multivariate data analysis for exploitation of available data
Analysis of industrial datasets characteristics
Improvement of process understanding through designed experiments and additional analytical measurements

Sarah Mercier, Scientist USP, Crucell Holland BV Netherlands

12:50

Networking lunch

14:15

Using Mechanistic Understanding to Enhance Process Understanding

Beyond statistical regression of multivariate data sets to quality attributes

Understanding “how” and mainly “why” data sets are related in order to achieve mechanistic understanding
Converting data into information and understanding multivariate correlations
Getting real information vs. being flooded with data sets
Understanding how to set up design of experiments with the benefit of a reduced number of experiments by using information parameters instead of raw process parameters
Using mechanistic understanding allows: knowledge transfer along development phases and scale up as well as continuous improvement and the extrapolation of knowledge back to process development for platform technologies and the product n+1

Prof. Dr. Christoph Herwig, Research Division Biochemical Engineering, Vienna University of Technology,Institute of Chemical Engineering Austria