1. DEVELOPMENT OF QUALITY BY DESIGN (QBD) GUIDANCE ELEMENTS ON DESIGN SPACE SPECIFICATIONS ACROSS SCALES WITH STABILITY CONSIDERATIONS Scale-up Experimentation – Fluid Bed Drying Benoit Igne, Sameer Talwar, Brian Zacour, Carl Anderson, James Drennen Duquesne University Center for Pharmaceutical Technology

2. Fluid Bed Drying Scale-up The thermodynamic environment (EEF) that is ideal for drying for a given product is constant regardless of scale/equipment. The group at IIT is performing computational fluid dynamic (CFD) simulations to maximize process understanding. –The simulations define all relevant properties at specific locations in the dryer and allow these properties to be defined for a different dryer. –A limited space is defined, drastically reducing the necessary number of experiments for successful scale-up. Dr. Linas Mockus has also used traditional bubbling bed models to predict experimental results at small scale to inform scale up decisions.

3. Intermediate Scale DOE (10 L Gral) ExpWater Content Spray Rate Spray Time Imp. Speed (RPMS) Wet Massing Time (sec.) EEFEnd Moisture Target End Product Temperature Target Airflow Velocity 15%28.5 g/min105 sec420300.450.5%< 30 o C15 m 3 /hr 23%28.5 g/min63 sec420300.450.5%< 30 o C15 m 3 /hr 34%28.5 g/min84 sec420300.450.5%< 30 o C15 m 3 /hr 44%28.5 g/min84 sec345300.450.5%< 30 o C15 m 3 /hr 54%250 g/min10 sec420300.450.5%< 30 o C15 m 3 /hr 64%250 g/min10 sec345300.450.5%< 30 o C15 m 3 /hr 75%28.5 g/min105 sec420600.450.5%< 30 o C15 m 3 /hr 85%28.5 g/min105 sec42000.450.5%< 30 o C15 m 3 /hr 95%28.5 g/min105 sec420300.17 5 0.5%< 30 o C15 m 3 /hr 105%28.5 g/min105 sec420300.17 5 1.0%< 30 o C15 m 3 /hr 115%28.5 g/min105 sec420300.450.5%< 30 o C15 m 3 /hr 125%28.5 g/min105 sec420300.451.0%< 30 o C15 m 3 /hr 135%28.5 g/min105 sec420300.450.5%< 30 o C15 m 3 /hr 145%28.5 g/min105 sec420300.450.5%< 30 o C15 m 3 /hr

4. Intermediate Scale Process Models Mean Tablet Hardness Mean Tablet Weight

5. Intermediate Scale Design Space Development

6. Intermediate Scale Conclusion Both primary drying factors (EEF and EMT) were correlated to tablet weight and tablet crushing strength, while also effecting disintegration time variability The low levels for both factors seem to be optimum These process models did not include stability or presster compression data, so the “optimum” levels may be strongly determined by these data. The significant factors are similar in the lab scale and intermediate scale, but the magnitude of the effect on response variables change. The final design space at each scale will define how the process parameters vary between scales for the optimum product parameters.

7. Production Scale DOE Exp. Water Content (%) Spray Rate (g/min.) Liquid Addition Time (sec) Impeller Speed Wet Massing Time (sec) EEFTarget Moisture Endpoint Target Product Temperature Endpoint Inlet Airflow Velocity 15277105195300.450.5%<30 o C300 cfm 25277105290300.17 5 0.5%<30 o C300 cfm 35277105195300.450.5%<30 o C300 cfm 45277105290300.450.5%<30 o C300 cfm 55277105290300.450.5%<30 o C300 cfm 6427785290300.450.5%<30 o C300 cfm

8. Production Scale Process Models Median PS Weight Before Blending Mean Tablet Crushing Strength

9. Production Scale Initial Conclusions EEF is correlated to particle size and particle size skewness, yield, and tablet crushing strength. –May be the result of poor initial fluidization Many of the final response variables (presster compression data, stability, disintegration) were not included in this initial analysis. The low number of experiments limits model development at full scale, but the simulations using bubbling bed models and CFD should increase process understanding. The most important results from the production scale experiments will be to confirm that our response variable targets can be achieved within the design space defined at the intermediate scale.