Is there a Sticky Sweet Spot?

Is there a Sticky Sweet Spot? Mixture Design of a Pressure Sensitive Adhesive Emulsion Formulation M. Michaelis, C. S. Leopold Department of Chemistry Division of Pharmaceutical Technology University of Hamburg, Germany 1

Aim of the study Formulation of an adhesive mixture for transdermal patches that comprises: 1. Improved adhesion properties. Improved solubility of an Active Pharmaceutical Ingredient (API)

Introduction Transdermal Therapeutic Systems (TTS) Patches for transdermal application of APIs to achieve a systemic effect About 50 TTS products on the market 14 Active Pharmaceutical Ingredients Mostly Drug In Adhesive Design (DIA) http://www.acino-pharma.com Drug In Adhesive Design http://www.novartis.com.ph Backing Drug in Adhesive Release liner + Controlled drug delivery + Good compliance - Stability issues - Lack of adhesion API level in blood http://www.nipro-patch.co.jp http://www.pharmainfo.net Crystalization of API http://www.quit.org.au Lack of adhesion 3

Introduction Pressure Sensitive Adhesives (PSAs) Pressure Sensitive Adhesives: Tacky at room temperature Adhere to a variety of surfaces on light pressure Adhere permanently Ûsed in a lot of common products Adhesive Performance Tack: Ability to form a bond of measurable strength by simple contact with a surface (stickiness) Shear Adhesion: Ability to resist structural failure (cohesiveness) Peel Resistance: Force required to remove the tape without leaving residues 4

Materials Component 1: Polyacrylate DuroTak 387-87 -Ethylhexyl acrylate Vinyl acetate Hydroxyethyl acrylate 67 % 5 % Component : Silicone Adhesive BIO-PSA 7-430 Component 3: Oleyl Alcohol Surfactant Component 4: Ibuprofen API / model drug (high dose analgetic) Oleyl Alcohol 8 % Ibuprofen 5

Design Mixture Design 3 (4) Components Components Low [%] High [%] Polyacrylate Adhesive 0 70 Silicone Adhesive 10 60 Oleyl Alcohol 0 10 Ibuprofen 0 Total 100 = Design Space = Replicate x = Replicate x 3 Design space with constraints IV Optimal Design Suggested design: 16 runs, 5 replicates, 5 to estimate lack of fit Evaluation: FDS Graph 6

Preparation of adhesive matrix/specimen 1. Components were dissolved in ethyl acetate (wet mix) and mixed in a shaker at 90 rpm for 15 min.. Wet mix was coated on a release liner 3. Films were dried at 80 C for 30 min in an oven Adhesive matrix (a) - 100 µm thick 4. Films were laminated with a backing membrane Specimen (b) a) Coating Knife b) Backing Membrane Drug In Adhesive Drug In Adhesive Release Liner Release Liner 7

Response 1 & : 1. Tack Probe Tack Test at 1 C Adhesive matrix (a) Stainless steel probe 3 mm Contact time 1 s, contact force 0.4 N Response: Stress maximum max [N/mm²] Probe Tack Test. Shear Adhesion Test specimen (b) was attached to a stainless steel plate Area: 1 x 1 mm, weight: 50 g Response: Time to failure t [min] Shear adhesion 8

Response 3 & 4: 3. Crystal growth Area of 100 cm of the adhesive matrix after 4 h Response: Area covered by crystals in % of the whole area 1:1 1:100 4. Creaming behavior (phase separation) Bottle with wet mix after 4 h Separated phase of wet mix in % of the wet mix no creaming 0 % creaming 9

Response 5 & 6 5. Droplet size Matrix was transferred to a glass slide Microscope with 100-fold magnification Response: Mean of droplet diameter of 30 droplets [µm] 6. Droplet distribution range Response: Maximum range of 30 droplets [µm] small & narrow large & narrow small & broad large & broad 10

Analysis Transformation Model Fit Summary and Model Lack of Fit ANOVA adj. R-square pred. R-square Diagnostics Normal Plot Residuals vs. Predicted Externally Studentized Residuals Box-Cox Plot Model Graphs 11

Response Analysis 1: Tack Fit Summary and Model Highest order polynomial: Reduced Special Quartic Model ANOVA Model: 0.0001 significant Lack of fit: 0.366 not significant Adj. R-square: 0.96 Pred. R-square: 0.8641 Diagnostics Normal Plot Residuals vs. Predicted Box-Cox plot Model Graphs 1

Response 1: Tack - Diagnostics Normal Normal Plot Plot of of Residuals Residuals Residuals Residuals vs. vs. Predicted Predicted 3.00 Normal % Probability Normal % Probability 99 95 90 80 70 50 30 0 10 5 1.00 1.00 0.00-1.00 -.00-3.00 -.00-1.00 0.00 1.00.00 -.00 1.00-1.00 1.50 0.00.00 1.00.50.00 3.00 Predicted Predicted 13

Response 1: Tack - Diagnostics Externally Residuals Box-Cox-Plot Box-Cox Plot for for Power Power Transforms Transforms 6.00-1.00 4.00.00 0.00 -.00-4.00-6.00 Ln (ResidualSS) Ln(ResidualSS) -1.0-1.40-1.60-1.80 1 4 7 10 13 16 Run Number Run Number -3 - -1 0 1 3 Lambda Lambda 14

Response 1: Tack - Model Graphs 100 % Polyacrylate = 0.50 N/mm² 100 % Silicone = 0.55 N/mm² A: Acrylat 70.000 Design points below predicted value 0.5 0. 0.4 3 0.3 0.000 10.000 0.3 0. Tack 0. A (70.000) 0.1 C (0.000) B (10.000) 0.4 60.000 B: Silicone 0.000 Tack 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 15

Response : Shear Adhesion - Diagnostics Fit Summary and Model Highest order polynomial: Quadratic Model ANOVA Model: 0.0001 significant Lack of fit: 0.6446 not significant Adj. R-square: 0.99875 Pred. R-square: 0.9734 Diagnostics Recommended transformation: Log Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms 3.00 4.00 10.00 Normal % Probability Normal % Probability 99 95 90 80 70 50 30 0 10 5 1.00 1.00 0.00-1.00 -.00-3.00.00 0.00 -.00-4.00 Ln(ResidualSS) Ln (ResidualSS) 8.00 6.00 4.00.00 0.00 -.00-1.00 0.00 1.00.00 0.00 0.0 0.40 0.60 0.80 1.00 1.0 1.40 1.60 1 4 7 10 13 16-3 - -1 0 1 3 Predicted Run Number Lambda Predicted Run Number Lambda 16

Response : Shear Adhesion - Model Graphs 100 % Polyacrylate = 17.min 100 % Silicone = 56.9 min A: Acrylat 70.000 Design-Expert Software Component Coding: Actual Original Scale (median estimates) Shear Design points above predicted value Design points below predicted value 30. 1.4 30. X1 = A: Acrylat X = B: Silicone X3 = C: Oleyl Alcohol 3 15 5 3 0.000 10 10.000 Shear Shear Adhesion 15.8 8.6 1.4 C (0.000) A (70.000) B (10.000) 0 60.000 B: Silicone 0.000 Shear Shear Adhesion 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 17

Response 3: Crystal Growth - Diagnostics Fit Summary and Model Highest order polynomial: Reduced Cubic Model ANOVA Model: 0.0001 significant Lack of fit: 0.7984 not significant Adj. R-square: 0.9819 Pred. R-square: 0.970 Diagnostics Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms 3.00 6.00 30.00 Normal % Probability Normal % Probability 99 95 90 80 70 50 30 0 10 5 1.00 1.00 0.00-1.00 -.00-3.00 4.00.00 0.00 -.00-4.00-6.00 Ln(ResidualSS) Ln (ResidualSS) 5.00 0.00 15.00 10.00 5.00 0.00-3.00 -.00-1.00 0.00 1.00.00 Internally studentized residuals 0.00 0.00 40.00 60.00 80.00 100.00 1 4 7 10 13 16-3 - -1 0 1 3 Predicted Run Number Lambda Predicted Run Number Lambda 18

Response 3: Crystal Growth - Model Graphs Crystal Growth 100 % Polyacrylate= 70 % 100 % Silicone= 100 % alue A: Acrylat 70.000 0 0 10 0 0 100 80 0.000 0 10.000 40 60 80 100 3 Crystal Growth 60 40 0 0-0 C (0.000) A (70.000) B (10.000) 60.000 B: Silicone 0.000 Crystal Growth 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 19

Response 4: Creaming behavior - Diagnostics Fit Summary and Model Highest order polynomial: Reduced Cubic Model ANOVA Model: 0.0001 significant Lack of fit: 0.6410 not significant Adj. R-square: 0.9460 Pred. R-square: 0.7104 Diagnostics Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms 3.00 6.00 9.00 Normal % Probability Normal % Probability 99 95 90 80 70 50 30 0 10 5 1.00 1.00 0.00-1.00 -.00-3.00 4.00.00 0.00 -.00-4.00-6.00 Ln(ResidualSS) Ln (ResidualSS) 8.00 7.00 6.00 5.00 4.00 3.00 -.00-1.00 0.00 1.00.00 5.00 10.00 15.00 0.00 5.00 30.00 1 4 7 10 13 16-3 - -1 0 1 3 Predicted Run Number Lambda Predicted Run Number Lambda 0

Response 4: Creaming Behavior - Model Graphs Design-Expert Software Component Coding: Actual Creaming Design points above predicted value Design points below predicted value 7.3743 A: Acrylat 70.000 10 15 4.44444 X1 = A: Acrylat X = B: Silicone X3 = C: Oleyl Alcohol 30 0 5 5 3 0 0.000 10.000 5 Creaming Creaming 15 10 5 C (0.000) A (70.000) B (10.000) 0 0 15 10 60.000 B: Silicone 0.000 Creaming 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 1

Response 5: Droplet Size - Diagnostics Fit Summary and Model Highest order polynomial: Reduced Cubic Model ANOVA Model: 0.0001 significant Lack of fit: 0.113 not significant Adj. R-square: 0.9733 Pred. R-square: 0.7747 Diagnostics Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms 3.00 6.00 8.00 Normal Normal % % Probability 99 95 90 80 70 50 30 0 10 5 1 Internally.00 1.00 0.00-1.00 -.00-3.00 4.00.00 0.00 -.00-4.00-6.00 Ln(ResidualSS) Ln (ResidualSS) 7.00 6.00 5.00 4.00 3.00.00-3.00 -.00-1.00 0.00 1.00.00 3.00 0.00 10.00 0.00 30.00 40.00 1 4 7 10 13 16-3 - -1 0 1 3 Predicted Run Number Lambda Predicted Run Number Lambda

Response 5: Droplet Size - Model Graphs A: Acrylat 70.000 Design-Expert Software Component Coding: Actual Droplet Size Design points above predicted value Design points below predicted value 40 3.75 X1 = A: Acrylat X = B: Silicone X3 = C: Oleyl Alcohol 50 40 0.000 10.000 0 3 10 Droplet Size Droplet Size 30 0 10 A (70.000) 0 C (0.000) 10 30 B (10.000) 40 60.000 B: Silicone 0.000 Droplet Size 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 3

Response 6: Droplet Distribution Range - Diagnostics Fit Summary and Model Highest order polynomial: Reduced Cubic Model ANOVA Model: 0.0001 significant Lack of fit: 0.831 not significant Adj. R-square: 0.930 Pred. R-square: 0.7410 Diagnostics Recommended Transformation: Square Root Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms Normal Plot of Residuals Residuals vs. Predicted Box-Cox Plot for Power Transforms 3.00 6.00 1.00 Normal % Probability Normal % Probability 99 95 90 80 70 50 30 0 10 5 1.00 1.00 0.00-1.00 -.00-3.00 4.00.00 0.00 -.00-4.00-6.00 Ln(ResidualSS) Ln (ResidualSS) 10.00 8.00 6.00 4.00 -.00-1.00 0.00 1.00.00 0.00.00 4.00 6.00 8.00 10.00 1 4 7 10 13 16-3 - -1 0 1 3 Predicted Run Number Lambda Predicted Run Number Lambda 4

Response 6: Droplet Distribution Range - Model Graphs A: Acrylat 70.000 value value 80 0.000 10.000 0 40 60 3 Droplet Distribution Range Droplet Distribution 60 40 0 0 C (0.000) A (70.000) B (10.000) 60.000 B: Silicone 0.000 Droplet Droplet Distribution Distribution Range 50.000 C: Oleyl Alcohol B (60.000) A (0.000) C (50.000) 5

Discussion: Response 3 & 5 & 6 A: Acrylat 70.000 0 0 A: Acrylat 70.000 A: Acrylat 70.000 0 0 3 3 10 3 0.000 0 10.000 40 0.000 10.000 0.000 10.000 60 80 0 0 100 30 40 10 60 60.000 B: Silicone 0.000 Crystal Growth 50.000 C: Oleyl Alcohol 40 60.000 B: Silicone 0.000 Droplet Size 50.000 C: Oleyl Alcohol 60.000 B: Silicone 0.000 Droplet Distribution 50.000 C: Oleyl Alcohol Crystal Growth Droplet Size Droplet Distribution Range 6

Optimization Constrains Solutions Lower Upper Lower Upper Name Goal Limit Limit Weight Weight Importance A:Acrylate is in range 0 70 1 1 3 B:Silicone is in range 10 60 1 1 3 C:Oleyl Alcohol is in range 0 10 1 1 3 Tack maximize 0.3 0.41 1 1 3 Shear Adhesion maximize 5.0 30. 1 1 3 Crystal Growth is target = 0 0 10.0 1 1 5 Droplet Size minimize 3.75 40 1 1 3 Droplet Distribution minimize.5 70 1 1 3 Number Acrylate Silicone Oleyl Alcohol Tack Shear Adhesion Crystal Growth Droplet Size Droplet Distribution Desirability 1 0. 59.8 0.0 0.41 6.19 4.81 7.3 5.0 0.750 45.0 35.0 0.0 0.31 1.89 0.53 10.9 4.4 0.540 7

Optimization A: Acrylat 70.000 0.000 10.000 0.600 0.00 0.400 3 Prediction 0.540 0.400 0.600 Prediction 0.750 60.000 B: Silicone 0.000 Desirability 50.000 C: Oleyl Alcohol 8

Conclusion Is there a sticky sweet spot? No, there is not. But 9

Conclusion We know that: Oleyl alcohol neither stabilizes the polymer-polymer interaction nor the polymer-api interaction. Oleyl alcohol decreases the adhesion properties in most cases. Wet mixes with equal amounts of polymer tend to be less stable. The best results were found at the periphery of the design space. Crystal growth correlates with droplet size and droplet distribution. No profit of oleyl alcohol, the addition is unnecessary. Limited processing time must be taken into account for scale up. Design space needs to be augmented. Do process variables such as mixing speed or viscosity of the wet mix have an influence on crystal growth? (combined design) 30

Thank you! 31