Influence of blender type on the performance of ternary dry powder inhaler formulations

Transcription

1 Institute of Pharmacy Kiel University Influence of blender type on the performance of ternary dry powder inhaler formulations Mats Hertel

2 Theoretical background Binary formulation: 1 st blending Ternary formulation: 1 st blending 2 nd blending Advantages: Saturation of active sites Lucas P, et al. (1998) Buffer effects during blending Dickhoff BHJ, et al. (2006) Formation of agglomerates (fines + API) Louey MD, et al. (2002) Change in fluidisation behaviour Shur J, et al. (2008)

3 Theoretical background Blending process Blender type Blending time Blending speed Blending sequence Blending energy input Blending mechanism Drug deagglomeration Drug distribution on the carrier surface Press-on forces ontothe the carrier surface Mixture properties Drug content homogeneity Drug-carrier adhesion Drug aerosolisation behaviour adapted from W. Kaialy (2016)

4 How to find the right process parameters? Picomix high shear mixer module Rotation speed = min -1 Volume = 180 ml Turbula low shear tumble blender Rotation speed = min -1 Volume = 135 ml

5 Fine particle fraction [%] How to find the right process parameters? Methods: A Picomix and a Turbula mixer were used to prepare blends with salbutamol sulfate and a coarse lactose carrier Mixing time and mixing intensity were varied Blending energy input Picomix : 500 rpm Turbula : 90 rpm Cordts E, et al. (2012)

6 Used process parameters Preparation of model DPI formulations: Picomix high shear mixer module Rotation speed = 500 min -1 Blending time = 2-10 min Total rotations: Batch size = 30 g Effective volume = 24 % Turbula low shear tumble blender Rotation speed = 90 min -1 Blending time = min Total rotations: Batch size = 30 g Effective volume = 32 %

7 Materials Carrier (C) Lactose monohydrate (InhaLac 70) X 50 = ± 1.0 µm Share of blend = 91 % Fines (F) Lactose monohydrate (InhaLac 400) X 50 = 6.3 ± 0.0 µm Share of blend = 7.5 % API Budesonide X 50 = 1.5 ± 0.0 µm Share of blend = 1.5 %

8 Methods Factors: D-optimal quadratic setup Blender type: Turbula & Picomix Total rotations (Rot): 1000, 3000 & 5000 Blending order (BO): [C + F] + [API] & [C + API] + [F] Responses: Drug content homogeneity and recovery 10 samples, each 12 mg Determination of in vitro fine particle delivery (FPF, FPD, MMAD) 3 runs per blend; 5 shots per run +

9 Rel. standard deviation [%] Kiel University Recovery [%] Results Drug content homogeneity and recovery: Rotations Rotations Turbula Picomix Turbula Picomix error bars = min / max

10 Fine particle fraction [%] Results Determination of in vitro fine particle delivery (FPF, FPD, MMAD): Summary of fit (MLR) * Fine particle fraction R2R 2 Q2Q 2 RP p * The poor model validity is a result of an artificial lack of fit Coefficients plot (scaled and centered)

11 Results [Carrier + API] + [Fines] before dispersion [Carrier + API] + [Fines] after dispersion 100 µm 100 µm 20 µm 20 µm

12 1 st blending step Carrier + API Carrier + Fines Press-on forces Press-on forces Press-on forces Press-on forces

13 2 nd blending step [Carrier + API] + Fines [Carrier + Fines] + API Press-on forces Press-on forces Press-on forces Press-on forces

14 Inhalation [Carrier + API] + Fines [Carrier + Fines] + API FPF FPF

15 Conclusion How does blender type influence the performance of ternary dry powder inhaler formulations? No significant influence on blend homogeneity and API recovery The blender type had the lowest impact on the in vitro fine particle delivery How does blending process influence the performance of ternary dry powder inhaler formulations? The number of rotations was the most important factor influencing the FPF, due to an increase of press-on forces SEM pictures showed saturation of active sites and gave an explanation for blending order results

16 Thank you for your attention!