In collaboration withIn collaboration with

Application of a fractional factorial design for the evaluation of a coating processPoster presented in October at 2015 AAPS Annual Meeting and Exposition

C. Funaro1, J. Mckee2, G. Mondelli1, E. Ammoniaci1, B. Albertini3, S. Politis4, N. Passerini3, D. Rekkas4

1 IMA S.p.A. Active division • v. I° Maggio, 14, 40064 Ozzano dell'Emilia, Bologna, Italy.2 IMA North America Inc • 7 New Lancaster Road, Leominster, IMA USA 01453.3 Dept. of Pharmacy and BioTechnology University of Bologna • v. San Donato 19/2, 40127 Bologna, Italy.4 Dept. of Pharmaceutical Technology, Faculty of Pharmacy • University of Athens, 15771, Athens Greece.

Application of a fractional factorial design for the evaluation of a coating processPoster presented in October at 2015 AAPS Annual Meeting and Exposition

White paper

Purpose

The aim of this work was to gain process knowledge regarding the application of a non functional aqueous coating material on tablets, using a fully perforated pan. For this purpose a 25-1 fractional factorial design was applied in order to screen the critical process parameters, affecting finished product quality and yield.

MethodsRound 6 mm, biconvex placebo 100 mg tablets

were coated by using a water based material (Opadry II pink at 20% concentration) in a fully perforated pan (Perfima Lab IMA, 30 liters drum, Figure 1). The Experimental Design matrix was executed utilizing two different batch sizes closed to the minimum and maximum capacity of the coating drum (12 L and 28 L). For each batch size 16 experiments plus 3 replicates of the center point were performed (Table 1 and 2). Using prior knowledge of the typical operating parameters of the coating pan, the following five candidate Critical Process Parameters (CPPs) were selected and studied at two levels:

Inlet Air Flow Rate (400-700 m3/h), Inlet Air Temperature (65-75°C), Atomization Pressure (1.5-2.5 bar), Spray Flow Rate (40-90 ml/min) and Theoretical Weight Increase (4-7%). Critical Quality Attributes (CQAs) and associated performance indicators were investigated as responses: Tablets Diameter and Thickness Increase, Uniformity of Coating Film and Process Efficiency. The design was generated and analyzed using Design-Expert® (Stat Ease, MN, US).

In collaboration with

Parameter Mu Value

Drum capacity L 30

Pan speed rpm 10

Pan depression Pa -30

Type of gun - Schlick - S75

Number of guns - 2

Nozzles diameter mm 1.2

Gun to bed distance cm 18/20

Pattern pressure bar 2

Figure 1: Perfima Lab

Table 1: Fixed parameters for the Experimental Design (both 12 and 28 L batch)

2

3

Application of a fractional factorial design for the evaluation of a coating process Poster presented in October at 2015 AAPS Annual Meeting and Exposition

Results

Preliminary tests on both batch sizes were performed to investigate factor levels assuring the feasibility of the design. Subsequently the screening design was executed. All experiments resulted in coated tablets free of visible defects and regions with high process efficiency were identified. The ANOVA results showed that adequate mathematical models between the CPPs and CQAs were developed. It was also identified that the various factors, in most of

the cases, affected the responses in a different way when the batch size changed. In general, Air Flow Rate and Atomization Pressure were proven as the CPPs predominantly affecting process efficiency and film quality attributes.The study showed that Process Efficiency was positively influenced by Air Flow Rate and negatively by Atomization Pressure in the 12 L batch while in the 28 L batch Process Efficiency improved when using lower values of Air Flow Rate and Inlet Air Temperature combined with high spraying rates.

In addition the several significant interactions, provided the tools for further understanding the complex phenomena governing the coating process, especially at the marginal manufacturing setting expressed by the small batch size compared to the drum’s capacity.One of the most important findings was that through appropriate factors settings it was feasible to achieve uniform coating for both batch sizes as described by figures from 2 to 5.

Batch size Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

12 L 18 L A: Inlet Air Flow Rate B: Inlet Air Temperature C: Atomization Pressure D: Spray Rate E: Theoretical Weight Gain

Std. m3/h °C bar ml/min %

1A 1B 400 65 1.5 40 7

2A 2B 700 65 1.5 40 4

3A 3B 400 75 1.5 40 4

4A 4B 700 75 1.5 40 7

5A 5B 400 65 2.5 40 4

6A 6B 700 65 2.5 40 7

7A 7B 400 75 2.5 40 7

8A 8B 700 75 2.5 40 4

9A 9B 400 65 1.5 90 4

10A 10B 700 65 1.5 90 7

11A 11B 400 75 1.5 90 7

12A 12B 700 75 1.5 90 4

13A 13B 400 65 2.5 90 7

14A 14B 700 65 2.5 90 4

15A 15B 400 75 2.5 90 4

16A 16B 700 75 2.5 90 7

CP1A CP1B 700 65 2.5 90 4

CP2A CP2B 400 75 2.5 90 4

CP3A CP3B 700 75 2.5 90 7

Table 2: Experimental Design including relevant central point

4

Conclusions

Using an economical statistical experimental design within the Quality by Design (QbD) framework a deeper systematic knowledge of the coating process was gained for the formulation studied.Therefore, the pillars for a sequential process optimization through rationalized factor number reduction and new level selection were established

Table 6: Coated tablets

References

[1] Cahyadi C., Heng P. W. S., Chan L.W., Optimization of Process Parameters for a Quasi-Continuous Tablet Coating System Using Design of Experiments, 2011; AAPS PharmSciTec, Vol12, N°1, March, pp 119-131.

[2] Korakianiti E., Rekkas D., Statistical Thinking and Knowledge Management for Quality-Driven Design and Manufacturing in Pharmaceuticals, 2011; Pharm Res 28, pp 1465-1479.

[3] Porter S. C., Verseput R. P., Cunningham C. R., Process Optimization Using Design of Experiments, 1997; Pharmaceutical Technology, ottobre, pp 1-7.

[4] Teckoe J., Mascaro T., Farrel T. P., Rajabi-Siahboomi A. R., Process Optimization of a Novel Immediate Release Film Coating System using QbD Principles, 2013; AAPS PharmSciTech, Vol 14 N° 2, pp 531-540.

[5] Vesey C. F., Rizzo M., Rajabi-Siahboomi A. R., Identification and Influence of Critical Coating Process Parameters on Drug Release from a Fully Formulated Aqueous Ethylcellulose Dispersion, 2007; poster AAPS Annual Meeting.

Figure 3: Contour plot 28 L coating uniformity

Figure 5: Perurbation plot 28 L coating uniformity

Batch 12 LΔ Thickness/ Δ Diameter

Ato

miz

atio

n pr

essu

re

Inlet Air Temperature

2.50

2.30

2.10

1.90

1.70

1.5065.00 67.00 69.00 71.00 77.00 79.00

1.30

1.20

1.10

1.00

0.90

Ato

miz

atio

n p

ress

ure

0.60

0.80

1.00

1.20

Batch 28 LΔ Thickness/ Δ Diameter

2.50

2.30

2.10

1.90

1.70

1.50

Inlet Air Temperature

65.00 67.00 69.00 71.00 77.00 79.00

Application of a fractional factorial design for the evaluation of a coating process Poster presented in October at 2015 AAPS Annual Meeting and Exposition

Figure 2: Contour plot 12 L coating uniformity

Figure 4: Perturbation plot 12 L coating uniformity

1.2

1.1

1.0

0.9

0.8

-1.000-1.000 -0.500 0.000 0.500 1.000

Δ Th

ickn

ess/

Δ D

iam

eter

Batch 12 L

1.2

1.1

1.0

0.9

0.8

0.7

0.6

0.5

-1.000 -0.500 0.000 0.500 1.000

Δ Th

ickn

ess/

Δ D

iam

eter

Batch 28 L