\\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Droplets-HD-Title-R1d.png Petr Beňovský QUALITY BY DESIGN, DESIGN OF EXPERIMENTS, PROCESS ANALYTICAL TECHNOLOGY \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Droplets-HD-Content-R1d.png \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Droplets-HD-Content-R1d.png Definition of Quality by Design: •Systematic approach to development and manufacturing; •The concept of QbD is to determine the critical quality attributes of a product resulting in a target product profile; •Begins with predefined objectives; •Emphasizes product and process understanding and process control; •Based on sound science and quality risk management. • QUALITY BY DESIGN AND DESIGN OF EXPERIMENTS CONCEPT \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Droplets-HD-Content-R1d.png QUALITY BY DESIGN AND DESIGN OF EXPERIMENTS CONCEPT Definition of Design of Experiment: •Strategy to gather empirical knowledge, i.e. knowledge based on the analysis of experimental data and not on theoretical models. It can be applied when investigating a phenomenon in order to gain understanding or improve performance. \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Droplets-HD-Content-R1d.png QUALITY BY DESIGN AND DESIGN OF EXPERIMENTS CONCEPT Approach to Process Validation (FDA Guideline excerpt): Stage 1 – Process Design The commercial manufacturing process is defined during this stage based on knowledge gained through development and scale-up activities; Stage 2 – Process Qualification During this stage, the process design is evaluated to determine if the process is capable of reproducible commercial manufacturing; Stage 3 – Continued Process Verification Ongoing assurance is gained during routine production that the process remains in a state of control. \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept QbD = Process Understanding A process is considered well understood from the physico-chemical perspective when • All key (critical) sources of variability are explained; •Quality attributes can be predicted based on key (critical) inputs; •Process capability of “Key (Critical) Quality Attributes“ meets acceptance levels. • A well understood process is by definition a process with a low risk of delivering of a poor quality product. \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept • Target the product profile • • Determine critical quality attributes (CQAs) • •Link raw material attributes and process parameters to CQAs and perform risk assessment • •Develop a design space • •Design and implement a control strategy • •Manage product lifecycle, including continual improvement \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept • Target the product profile • • Determine critical quality attributes (CQAs) • •Link raw material attributes and process parameters to CQAs and perform risk assessment • •Develop a design space • •Design and implement a control strategy • •Manage product lifecycle, including continual improvement \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept LavenderFlowers.jpg Field_of_Flowers.jpg Target the product profile I want a flower ! But I wanted something different !! \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept Target the product profile • Dosage Form • Characteristics – appearance, shape, form, size • Strength • Assay • Purity/impurity • Stability • Others • cQAs \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept • Target the product profile • • Determine critical quality attributes (CQAs) • •Link raw material attributes and process parameters to CQAs and perform risk assessment • •Develop a design space • •Design and implement a control strategy • •Manage product lifecycle, including continual improvement \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept Risk assessment – Ishikawa (fishbone) diagram fishbone.jpg \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept ▪ DOE results in a set of experiments. ▪ All factors are varied, systematically and independently. ▪ The number and type of factors and regression model specify the prerequisites. ▪ The DOE defines the optimal number of runs and the best factor combinations for the runs. ▪ DOE is used for three primary experimental objectives screening: which factors are important and what are their appropriate ranges? optimization: what are the optimal factor settings? robustness testing: how sensitive is a response to small factor changes? ▪ Advantages with DOE compared to OVAT: factor interactions are estimable; reliable maps of the systems; seen effects and noise are separable and estimable; probability analysis. Carlson, R. Design and Optimization in Organic Synthesis, Elsevier 1992 \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept • Target the product profile • • Determine critical quality attributes (CQAs) • •Link raw material attributes and process parameters to CQAs and perform risk assessment • •Develop a design space • •Design and implement a control strategy • •Manage product lifecycle, including continual improvement \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept Design Space The process design space is a multidimensional combination and interaction of input variables, i.e. material attributes and process parameters, that have been demonstrated to provide adequate quality. \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept • Target the product profile • • Determine critical quality attributes (CQAs) • •Link raw material attributes and process parameters to CQAs and perform risk assessment • •Develop a design space • •Design and implement a control strategy • •Manage product lifecycle, including continual improvement \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept The Control Strategy must include CQAs and CPPs that are included in the Design Space Examples: • Raw material purchase specification • API characteristics • Operating ranges for process parameters • In-process controls • Acceptance criteria • Release testing •API and drug product specifications and their acceptance criteria \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept When fully implemented, QbD means that all critical sources of process variability have been identified, measured and understood so that they can be controlled by the manufacturing process itself. The resulting business benefits are significant: • Reduced batch failure rates; • Lower operating cost; •Increased predictability of manufacturing output and quality; •Faster tech transfer between development and manufacturing; •Faster regulatory approval of new product applications and process changes; •Fewer and shorter regulatory inspections of manufacturing sites; •Significant reductions in working capital requirements, resource costs and time to value. \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept parachute.jpg landing.jpg \\DROBO-FS\QuickDrops\JB\PPTX NG\Droplets\LightingOverlay.png Quality by Design and Design of Experiments Concept Mohammed, A.Q. Org.Process Res.Dev. 19, 1634 (2015) – Quality by Design in Action 1 Mohammed, A.Q. Org.Process Res.Dev. 19, 1645 (2015) – Quality by Design in Action 2 Murray, P.M. et al Org.Biomol.Chem. 14, 2373 (2016) – the application of design of experiments in reaction optimization and solvent selection