A Comparison of Three Extrusion Systems (Part II)

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Pharmaceutical Technology, Pharmaceutical Technology-06-02-2011, Volume 35, Issue 6

The authors compare three systems of single-screw extrusion using binary formulations for their suitability for producing pellets of various formulations and under various spheronization conditions.

In the first part of the current study, the influence of water quantity and extrusion speed was investigated for a highly soluble drug product at a fixed concentration in the formula. A design of experiments underlined significant differences between the three extrusion systems (1). This article will continue to compare radial, dome, and axial single-screw extruders in terms of process and pellet quality. This article specifically will investigate the influence of formulation and spheronization variables on process and pellet properties by using a response surface design of experiments, a powerful statistic tool allowing a rational study of the experimental parameters and enhanced process comprehension.

The influence of formulation and spheronization conditions on product properties has been widely described in the literature. Numerous authors have shown the impact of excipient and drug substance properties (e.g., solubility, particle size) or content on the extrusion process and/or pellet quality for one kind of extrusion system (2–16). Other authors have underlined the effect of spheronization time or speed on pellet properties for one system of extrusion (7, 9, 15–26).

These studies show that formulation and spheronization variables allow improved comparison of extrusion systems by providing complementary information about their efficiency under different conditions. Other authors have compared the extrusion of different formula under constant spheronization conditions, the effect of different spheronization conditions on pellet quality for different extrusion systems for the same formulation, and other combinations of conditions to evaluate the extrusion process for axial and radial extruders (14, 27–36).

The research here fully compares the dome extruder with other systems using a design-of-experiments approach to enable full analysis and good process understanding. Three single-screw extrusion systems (radial, dome, and axial) are compared for their capacity to produce good quality pellets of various drug concentrations and solubility, under different spheronization speeds and times. The study analyzes the results against each other, introducing the notions of robustness and flexibility.

Materials and methods

Raw materials. Pellets were prepared from a binary mixture of a drug substance (DS) and microcrystalline cellulose (MCC). Two drug substances, DS1 and DS2 supplied by Pierre Fabre Research Institute, were tested. DS1 corresponded to the antidepressant drug product studied in Part I of the study, and DS2 corresponded to the monohydrate theophylline. The drugs were chosen for their different solubility in water (1250 g/L for DS1 and 8 g/L for DS2). MCC (Avicel PH101), supplied by FMC Biopolymer, is insoluble in water. Three ratios of DS to MCC were tested for both drug substances: 20:80, 36:64, and 52:48 (% w/w). Purified water was used as liquid binder. The optimal water quantity used for each of the six formulations was determined by preliminary experiments and was found to be dependant on drug solubility and concentration. The optimal water level decreased with water solubility and increased concentration of the drug. This effect has been observed before for drugs and excipients (2, 5, 13, 29).

Experimental design and pellet preparation. Pellets were prepared according to the manufacturing conditions described in Part I of the study (1). A response surface design of experiments was built with Design Expert software, version 7.0.1.0 (Stat-Ease). The mathematical model targeted for each response studied was a quadratic model with first-order interactions. Five factors were studied: drug solubility in water (g/L), drug concentration (%), extrusion system, spheronization speed (rpm), and spheronization time (min). To analyze the results, the drug solubility and the extruder system were included as qualitative factors, whereas the others were considered as continuous factors. DS1 and DS2 were both tested at concentrations of 20, 36, and 52%. Spheronization speed was tested at 800, 1000, and 1200 rpm. Spheronization time was tested at 2, 3, and 4 min. These intervals were determined by preliminary trials, beyond these limits, it was difficult to obtain acceptable pellets. All other experimental conditions were constant. The extrusion speed was 40 rpm.

The design of experiments was built as a set of six Box–Behnken designs, each corresponding to one combination of two qualitative factors (i.e., drug solubility and extrusion system). For each of these six designs, three replicates of the central point (level 0, i.e., 36% of drug substance, 1000 rpm of spheronization speed, and 3 min of spheronization time) were run (see Figure 1). The whole experimental design included a total of 96 (6 × 16) experiments. Figure 2 summarizes factors and responses selected for the global design of experiments.

Figure 1: Factor levels of the experimental design for each qualitative combination. (ALL FIGURES ARE COURTESY OF THE AUTHORS)

Characterizations. Responses specific to this part of the study, shown in italics in Figure 2, are described below. All other responses are described in Part I of the study (1). Pellet dispersion could not be analyzed because the design of experiments was inadequate for the model for this response.

Figure 2: Factors and responses of experimental design.

Roughness. Roughness analysis of the pellet yield fraction was assessed by measuring solidity factor using a Morphologi G2 (Malvern Instruments). Analysis was carried out on around 300 pellets from the usable yield fraction. Solidity factor (S) was calculated according to the formula: S = A÷(A+B) in which, A is pellet area and A+B is the area enclosed by the convex hull (A+B). High solidity is desirable because it corresponds to low roughness; rough pellets may generate fines or have poor flow characteristics. Surface roughness of the pellets is also an important characteristic when considering eventual coating or compression into tablets.

Pycnometric density. Pycnometric density of pellets, Dpycno (g.cm3), was determined using a helium pycnometer (Accupyc 1330, Micromeritics Instrument) Samples were degassed under 6.5 Pa vacuum (VacPrep 061, Micromeritics Instrument) for two days at about 25 °C. Measurements were performed using a 10 cm3 cell, and repeated until the value stabilized. The mean pycnometric density was calculated from the final three stabilized data points.

Results

Design-of-experiments interpretation. The mathematical model generated for each response Y was a quadratic model with first-order interactions, built according to the following equation:

in which Xi and Xj represent the levels of the factors; a0 is the intercept representing the mean of the measured response data; and ai and aj, aii and ajj, and aij correspond to the coefficients of first-order terms, the coefficients of second-order quadratic terms, and the coefficient of second-order interaction terms, respectively. The coefficient corresponding to a factor or interaction shows its importance on the studied response. The symbol ε represents pure error. For the multilevel categoric factors presenting more than two levels (i.e., factor E), the software calculates two coefficients, E(1) and E(2), of the difference between the overall average and the high and low levels, respectively. To simplify the design-of-experiments interpretation, the coefficients of second-order quadratic terms were not presented in this study. The coefficient values were expressed in coded units to compare their relative effect to that of the others.

Analysis of variance (ANOVA) was performed to determine the significance of the model. A probability value lower than 0.05 was considered significant. A probability value greater than 0.10 was regarded as not significant. The effects of factors and main interactions between the factors, deduced from the analysis of the experimental design, are summarized with bar graphs on Figure 3. The red bars correspond to the factors that significantly influenced the response Yx.

Figure 3: Effects of factors and main interactions on various responses.

Influence of formulation. As deduced from the analysis of the experimental design (see Figure 3), the drug substance solubility (D) and concentration (A) had significant influence on all the responses except pellet elongation and roughness index for the drug concentration. Some of these effects can be explained by the different water quantities required for different formulations.

Decreases in drug concentration and solubility both led to a lower extrusion rate and yield. The corresponding water quantity increase should nevertheless facilitate extrusion by an extrusion force decrease due to a lubricant effect (1–3, 5, 10, 28, 32, 37, 38). The observed effect is more likely linked to raw materials properties and facilities to extrude than to associated water quantities. Decreases in drug concentration and solubility also decreased pellet size and the usable yield fraction, and increased true density, friability, and hardness. The drug-solubility decrease also increased pellet elongation and rugosity by decreasing the solidity index. These effects can be explained by the corresponding water quantity increase. Many authors reported that water evaporation from wet pellets during the oven-drying step caused a mechanical shrinkage phenomenon (15, 39–44). Shrinkage proportional to the water-quantity increase led to a particle size reduction (and thus a decrease in usable yield fraction), a decrease in circularity decrease, a roughness increase and subsequent friability increase by attrition, and densification leading to an increase in hardness.

Drug concentration and solubility thus had a similar influence on the responses, including an important effect on drug solubility. Except for pellet friability, an interaction between the two formulation variables was observed for all the responses. Some authors also indicated an interaction between the two formulation variables and observed higher impact of drug solubility on the different responses, because it led to greater differences between the corresponding water quantities than for DS concentration (3, 4). Moreover, drug concentration had more influence for the highly soluble drug, where large changes in water quantity are required for different concentrations, than for the poorly soluble drug, where water quantities remain very similar.

Influence of the extrusion system. The extrusion system had a significant effect on all responses. Significant interactions between the extrusion system and drug substance solubility and concentration and their effect on the responses necessitated that formulations were analyzed as distinct designs of experiments. This method enabled identification of the extruder type that gave the best results in terms of process and pellet quality, according to the formula (see Table I).

Table I: Analysis of the influence of extrusion system on responses to drug substance solubility and concentration.

For example, in the formulation constituting 36% DS1, the dome system had the highest extrusion rate, and the axial system had the lowest extrusion rate. Analysis of the extrusion system influence showed different results according to the formulation tested. The extrusion systems presented more significant differences for DS2 than for DS1 on pellet properties. Overall, the axial system presented the best results in terms of pellet yield, mechanical properties, and roughness, followed by the dome system for productivity and pellet circularity. The radial system produced the worst results irrespective of the formulation.

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Influence of spheronization conditions. The design of experiments showed a significant effect of spheronization speed and time on some pellet characteristics, as shown on Figure 3. An increase in spheronization speed influenced the pellet usable yield fraction, roughness index, and hardness, whereas spheronization time influenced pellet size, elongation, roughness index, true density, and hardness. Both factors increased pellet hardness to the same degree, as observed previously (26, 46–48). This result most likely can be explained by pellet densification caused by the pellet water migration during spheronization, which decreases pellet porosity after drying (21). An increase in spheronization speed decreased the usable yield fraction, probably because of the phenomenon of attrition linked to increases in rugosity (28, 35). On the other hand, as reported by other authors, spheronization time increased pellet size and quality by improving pellet roundness and decreasing pellet rugosity (17, 22, 26, 28, 34, 36, 49). Nevertheless, spheronization time decreased the pycnometric density, which can be explained by pores closing on the surface during spheronization, thus creating internal porosity.

Discussion

The ideal extrusion system gives the best results in terms of productivity and pellet quality, but also has the least influence on those same properties when the formula used changes (i.e., robustness), and allows pellet properties to be adjusted or improved with spheronization variables (i.e., flexibility). The extruders were analyzed as distinct designs of experiments (see Table II) to study the significant effects of other factors in order to assess which extruder presented the best robustness and flexibility.

Table II: The effect of formulation and spheronization variables on responses.

Robustness study. A nonsignificant effect of an extrusion system when the formulation changed confirmed extruder robustness. For example, an increase in DS concentration caused an increase or decrease in pellet size for axial and dome extrusion respectively but had no significant effect for the radial system, which, therefore, is the most robust (see Table II). The influence of DS solubility and DS concentration was also extrusion system dependent. In the radial system, DS solubility had no significant effect on extrusion yield or pellet hardness, and DS concentration showed no significant effect on pellet size, circularity, yield, roughness or friability. In the dome system, DS concentration had no significant influence on pellet circularity or roughness, whereas DS solubility had significant effect on all responses. In the axial system, DS solubility had no significant influence on pellet friability, and DS concentration showed no significant effect on pellet circularity, roughness or friability. The influence of DS solubility and concentration was significant for all the other cases. The radial system, therefore, was the most robust formulation variability (particularly in terms of pellet size).

Flexibility study. A significant effect of the extrusion system when spheronization conditions changed confirmed extruder flexibility. For example, an increase in spheronization time increased pellet size in the dome system but had no significant effect in the other systems, which showed the dome system to be the most flexible (see Table II). The influence of spheronization time and speed also dependended on extrusion system. In the radial system, spheronization speed affected mechanical pellet properties (e.g., friability and hardness), whereas spheronization time influenced roundness, roughness, and true density. In the dome system, spheronization speed had a significant effect on usable yield, and spheronization time influenced pellet size, roughness and true density. In the axial system, spheronization time affected pellet roughness. Overall, the radial and dome systems were more flexible. The dome system presented good flexibility, notably on pellet size when spheronization time varied. In the axial system, changes in spheronization parameters did not compensate for bad pellets properties. Other authors have also concluded that the type of extruder influenced pellet characteristics and that axial extruders were more difficult to use because of their lower flexibility (36).

The conclusions of robustness and flexibility studies, combined with the quality study described previously identified the ideal extrusion system at lab scale (3, 4). The extruder systems that presented the best results for each of the three approaches are highlighted in Table III.

Table III: Identification of ideal extrusion system in terms of quality, robustness, and flexibility.

Regardless of spheronization parameter levels, the axial system presented the best results in terms of mechanical pellet properties and roughness, but disappointing results for process robustness and flexibility. The dome system showed the best results in terms of productivity, pellet morphology, and process flexibility, but disappointing results for process robustness. Despite the worst results in terms of process and pellet properties, the radial system presented good results for process robustness and flexibility (see Table III).

Conclusion

The objective of this study was to identify critical parameters and to select the extruder that gives the best results in terms of productivity and pellet characteristics (product quality), the one that shows the least influence on these same properties when the formulation changes (robustness), and the one that allows the adjustment of spheronization variables to improve pellet properties (flexibility).

In spite of good pellet quality results, the axial extruder seems to be the most difficult to use because of its lack of flexibility. Perfect knowledge of the initial wet mass composition and plasticity is required because its results depend on formulation. The pellet manufacturing ability of the radial extruder is not heavily influenced by the formulation, and adjustment of spheronization variables control pellet properties. For the formulations and process variables studied, the design of experiments identified the radial system as the easiest to use because of its higher robustness and flexibility—two important requirements for the development and scale-up of formulation by extrusion–spheronization. The final part of this work will validate these results at industrial scale.

Amélie Désiré* is a doctoral student at École des Mines d'Albi-Carmaux and the Centre de Recherche et de Développement Pierre Fabre, 3 ave. Hubert Curien, 31035 Toulouse Cedex 01, France tel. +33 05 34 50 62 79, fax +33 05 34 30 32 72, amelie.desire@pierre-fabre.com. Bruno Paillard is head of solid dosage forms, and Joël Bougaret is director of the Pharmaceutical Technology Department, both at the Centre de Recherche et de Développement Pierre Fabre. Michel Baron is head of the Pharmaceutical Engineering Department at école des Mines d'Albi-Carmaux, and Guy Couarraze is head of the Pharmaceutical Physics Department at the Université Paris Sud.

*To whom all correspondence should be addressed.

Submitted: Feb. 23, 2011. Accepted: May 4, 2011

References

1. A. Désiré et al., Pharm. Technol. 35 (1), 56–65 (2011).

2. C. Lustig-Gustafsson et al., Eur. J. Pharm. Sci. 8 (2), 147–152 (1999).

3. G. Tomer, F.Podczeck, and J.M. Newton, Int. J. Pharm. 217 (1–2), 237–248 (2001).

4. G. Tomer, F. Podczeck, and J.M. Newton, Int. J. Pharm. 231 (1), 248–257 (2002).

5. J.J. Sousa et al., Int. J. Pharm. 232 (1–2), 91–106 (2002).

6. J. Chatchawalsaisin, F. Podczeck, and J.M. Newton, Eur J Pharm Sci. 24 (1), 35–48 (2005).

7. D. Lutchman, C.M. Dangor, and D. Perumal, J. Microencapsul. 22 (6), 643–659 (2005).

8. F.O. Costa, A.A.C.C. Pais, and J.J.S., Int. J. Pharm. 270 (1–2), 9–19 (2004).

9. G.A. Hileman et al., Int. J. Pharm. 100 (1–3), 71–79 (1993).

10. L. Baert and G.R.B. Down, Int. J. Pharm. 107 (3), 219–222 (1994).

11. L. Alvarez et al., Eur. J. Pharm. Biopharm. 55 (3), 291–295 (2003).

12. R. Gandhi et al., Pharm. Technol. 29 (2). 68–86 (2005).

13. L. Rahman et al., STP Pharm. Sci. 1 (5), 294–299 (1991).

14. E. Nürnberg, and J. Wunderlich, Pharm. Technol. Eur. 11 (3), 30-34 (1999).

15. S. Galland, T. Ruiz, and M. Delalonde, Int. J. Pharm. 337 (1–2), 239–245 (2007).

16. S. Galland, T. Ruiz, and M. Delalonde, Powder Technol. 190 (1–2), 48–52 (2009).

17. J.F. Pinto and C.N. Abreu, Drug. Dev. Ind. Pharm. 32 (9), 1067–1078 (2006).

18. L. Hellén, J. Yliruusi, and E. Kristoffersson, Int. J. Pharm. 96 (1–3), 197–204 (1993).

19. L. Hellén, J. Yliruusi, and E. Kristoffersson, Int. J. Pharm. 96 (1–3), 205–216 (1993).

20. L. Hellén, J. Yliruusi, and E. Kristoffersson, Int. J. Pharm. 96 (1–3), 217–223 (1993).

21. A.M. Juppo et al., Eur. J. Pharm. Biopharm. 44 (2), 205–214 (1997).

22. V.R. Sinha et al., AAPSPharmSciTech, 8 (1), E1–E5 (2007).

23. S. Galland et al., Powder Technol. 157 (1–3), 156–162 (2005).

24. D. Sonaglio et al., Int. J. Pharm. 115 (1), 53–60 (1995).

25. E.I. Hamedelniel, J.Bajdik, and K.Pintye-Hódi, Chemical Engineering and Processing: Process Intensification 49 (1), 120–124 (2010).

26. A. Häring, K. Krejcova, and M. Rabiskova, Farm. Vestn. 54 (special issue), 437–438 (2003).

27. L. Baert et al., Int. J. Pharm. 86 (2–3), 187–192 (1992).

28. L. Baert et al., Int. J. Pharm. 99 (1), 7–12. (1993).

29. C. Schmidt, H. Lindner, and P. Kleinebudde, Eur. J. Pharm. Biopharm. 44 (2), 169–176 (1997).

30. K. Thoma and I. Ziegler, Drug Dev. Ind. Pharm. 24 (5), 401–411 (1998).

31. K. Thoma, and I. Ziegler, Drug Dev. Ind. Pharm. 24 (5), 413–422 (1998).

32. D. Sonaglio, B. Bataille, and M. Jacob, Pharm. Acta Helv. 72 (2), 69–74 (1997).

33. C. Schmidt, and P. Kleinebudde, Eur. J. Pharm. Biopharm. 45 (2), 173–179 (1998).

34. J.M. Newton, S.R. Chapman, and R.C. Rowe, Int. J. Pharm. 120 (1), 101–109 (1995).

35. D. Sonaglio et al., Pharmazie 52 (2), 129–134 (1997).

36. P. Costa and J.M. Sousa Lobo, Eur. J. Pharm. Sci. 13 (2), 123–133 (2001).

37. E. Jerwanska et al., Int. J. Pharm. 121 (1), 65–71 (1995).

38. P. Kleinebudde and H. Lindner, Int. J. Pharm. 94 (1–3), 49–58 (1993).

39. A.B. Bashaiwoldu, F. Podczeck and J.M. Newton, Eur. J. Pharm. Sci. 21 (2–3), 119–129 (2004).

40. B. Song, S.L. Rough, and D.I. Wilson, Int. J. Pharm. 332 (1–2), 38–44 (2007).

41. J.P. Perez and M. Rabiskova, Int. J. Pharm. 242 (1–2), 349–351 (2002).

42. J.J. Sousa et al., Int. J. Pharm. 144 (2), 159–169 (1996).

43. J. Berggren and G. Alderborn, Int. J. Pharm. 219 (1–2), 113–126 (2001).

44. P. Kleinebudde, Int. J. Pharm. 109 (3), 209–219 (1994).

45. P. Kleinebudde, Int. J. Pharm. 109 (3), 221–227 (1994).

46. B. Bataille, K. Ligarski, and M. Jacob, Pharm. Acta Helv. 65 (12), 334–337 (1990).

47. K. Ligarski et al., STP Pharma Sci. 1 (4), 256–261 (1991).

48. B. Bataille et al., Drug Dev. Ind. Pharm. 19 (6), 653–671 (1993).

49. K. Umprayn, P. Chitropas, and S. Amarekajorn, Drug Dev. Ind. Pharm. 25 (1), 45–61 (1999).

Citation: When referring to this article, please cite it as "Amelie Desire, Bruno Paillard, Joel Bougaret, Michel Baron, Guy Couarraze, "A Comparison of Three Extrusion Systems (Part II)," Pharmaceutical Technology 35 (6) 56-61(2011)."