All the data analysis for your PAT and QbD procedures
Why implement Process Analytical Technology and Quality by Design?
The US Food and Drug Administration (FDA) launched the Process Analytical Technology (PAT) initiative in 2004 to improve process design, supervision and control in the pharmaceutical industry.
You wish to
Develop
rapid at-line, in-line or on-line analysis methods for product characterization
Pilot
and optimize continuous manufacturing processes or batch production processes
Control
product quality at each stage of the production chain, compared to standard processes
Ondalys helps you in implementing this PAT and QbD approach in your process development laboratories and production sites, using validated data analysis tools. The Quality by Design (QbD) approach, such as defined in the ICH Q8 (R2) and ICH Q11 guides, makes it possible to optimize the quality of the products and their manufacturing processes during the development phase. QbD is a systematic approach based on Design of Experiments (DoE) and integrating risk management (ICH Q9), in order to generate scientific knowledge (Knowledge Management) and a Design Space defining the field of acceptable variability to ensure effectiveness of the drug and patient safety.
Thanks to this QbD approach, Critical Quality Attributes (CQAs) as well as Critical Process Parameters (CPPs) are identified. A Process Analytical Technology (PAT) strategy can then be implemented, in order to control the quality of the entire production chain, from raw materials to finished products, including products undergoing transformation, to ensure risk control continuously (Quality Risk Management). This process can even go as far as the release of the pharmaceutical product in real time at the end of manufacturing (Real-Time Release Testing – RTRT -).
Supervision or process control involves setting up at-line, on-line or in-line time measurements from sensors (spectrometers, IoT) and process parameters. All this information must then be analyzed via multivariate models for process supervision, whether they are batch processes with BSPC methods – Batch Statistical Process Control – or more innovative continuous processes with MSPC methods – Multivariate Statistical Process Control -.
Within this PAT / QbD approach, multivariate data analysis and model validation tools are both crucial.
QbD is largely based on the theory of experimental designs (DoE), combined with risk management.
PAT includes developments of CQAs prediction models (spectroscopic calibration for the prediction of the concentration of active ingredient for example) and process supervision by BSPC or MSPC.
Chemometrics tools are necessary in the processes of Process Analytical Technology – PAT – and Quality by Design – QbD – to:
- Develop calibrations for quality control of raw materials on receipt and finished products
- Determine the Design Space (DoE / QbD) during product and process development
- Develop rapid analysis methods at-line, in-line or on-line for the prediction of CQAs in the framework of PAT
- Control a batch process by Batch Statistical Process Control (BSPC)
- Control a continuous process by Multivariate Statistical Process Control (MSPC)
Software implementation
We develop and implement all data processing on software enabling CFR21 Part 11 validation.
The QbD / DoE approach is carried out using DesignExpert® software from StatEase or MODDE® software from Sartorius Stedim Data Analytics.
For the PAT approach, Data Mining models, calibrations and process supervision are developed with validated software (Unscrambler® or SIMCA® or any validated analyzer software (OPUS, Vision, TQ Analyst, GRAMS, etc.).
Our expertise for the analysis of your data
With over 15 years of experience in data analysis (Chemometrics and Machine Learning), in particular applied to spectroscopic, analytical and sensory measurements, our teams support you at each stage of your projects
They talk about us
« Ondalys, helped reviewing of the Chemometrics chapter of the European Pharmacopoeia »
