Assessment of Scaling via CQA Indicator Substance

Figure 6.20 Dependency of residual crystallinity on measured melt temperature at die exit.

The measured residence time at both scales does not explain the discrepancy in measured residual crystallinity. The measured RTD varied in accordance with the well-known influence of varied screw speed and feed rate (136,137) and was similar for both extruders (Figure 6.21), with the MRT slightly higher at the ZSK18 than at the ZSK40. The distributions were also broader at the ZSK18 than at the ZSK40 (Figure 6.22). Due to experimental limitations on the ZSK18 extruder (too little telmisartan blend remaining after ZSK40 experiments), the RTD was only measured for the “same shear rate” scaling method. Simulation results supported the decision to not measure the RTD for all conditions due to the observation that the simulated MRTs from this scaling method were more similar to the ZSK40 MRTs than for the other scaling method (lower half of Figure 6.21). The apparent lack of influence of the RTD on residual crystallinity is supported by the CQA’s strong correlation with melt temperature (Figure 6.20) and, in the previous study, also independently of varying the feed rate and screw speed (Figure 5.8a). However, confirmation of these relationships would require a different experimental design with the possibility to independently vary the melt temperature and RTD.

Figure 6.21 Experimental and simulated MRT vs. processing conditions.

Figure 6.22 Experimental and simulated RTD (dashed lines are simulated).

The fill level, using a simple calculated approximation (equation 2.16), was higher for the ZSK18 than for the ZSK40 (Figure 6.23). Because the fill level in the extruder is challenging to measure directly due to its variation along the length of the extruder (60), although recent advancements have been made (155), and because this was not the primary focus of this study, this simple estimate was used. The exact reason for the discrepancy is not clear, but it could be related to the fact that the volume of the die was neglected in the calculation of the extruder volume, while at the same time, the die was included in the measurement of the RTD and subsequent calculation of MRT. However, the fill level could be related to the effective surface area for cooling; if at one scale relatively more melt is in contact with the inner barrel surface due to greater fill, and the SA:V ratio is greater, then more melt can be effectively cooled. Nevertheless, the relationship between fill level and residual crystallinity is not directly obvious and therefore this discrepancy is simply an observation. In addition, higher fill level in a smaller extruder can support scaling as the surface area to volume ratio changes. For example, perhaps an effective strategy could be to maintain the surface area to fill volume ratio constant.

Figure 6.23 Extruder fill level vs. VSFL and screw speed.

The magnitude of measured and simulated SME is similar independent of extruder scale but the range of measured SME is much broader than for that of the simulated (Figure 6.24). Despite this, the two versions of SME are in the same order of magnitude and correlate similarly with VSFL and screw speed. Although the magnitude of simulated SME is similar for both scales, the range is narrower for the ZSK40 (Figure 6.24 and Figure 6.25). In addition, the melt temperature rise in the most intense shear region of the screw configuration, in this case the 2^nd mixing zone, designated as “DeltaT max-barrel,” is similar for both extruder scales.

However, the temperature rise is more sensitive to changes in simulated SME on the ZSK40 than on the ZSK18, as seen by the steeper slope for the ZSK40 (Figure 6.25).

Despite this difference in sensitivity, which may be more substantial outside the presently explored design space, the similarity in SME at both scales indicates that mechanical energy is not the explanation for differing melt temperatures and resulting differences in residual crystallinity.

Figure 6.24 Experimental and simulated SME vs. VSFL and screw speed.

Figure 6.25 Simulated DeltaT vs. simulated SME for various processing conditions.

The combination of some of the scale-dependent differences may explain the difference in melt temperature and residual crystallinity. While the simulated maximum melt temperature was similar for both scales (Figure 6.14), the simulated screw exit (Figure 6.14) and measured melt temperatures (Figure 6.13) were higher and the MRT was shorter and distribution was narrower for the ZSK40 (Figure 6.21 and Figure 6.22). In addition, the available contact area per unit volume for cooling the melt was lower for the ZSK40 (Table 6.1). Also, both the fill level (Figure 6.23) and the magnitude of simulated cooling conducted energy (Figure 6.16) was greater for the ZSK18. Putting this all together, perhaps the greater surface area and slightly longer residence time on the ZSK18 allowed for greater cooling of the melt, limiting the extent of telmisartan dissolution.

Finally, one simple explanation for differences between scales could be that the real barrel temperature in contact with the melt may differ from the set point. In fact, depending on the location of heating elements in relation to the screw channel and the barrel temperature control thermocouples, the metal closest to the screw channel can vary from the set point. This discrepancy has been observed for the ZSK18 extruder used in this study; in particular, the inner part of the barrel is typically measured to be 7 °C hotter than the set point by inserting melt temperature

thermocouples into the sensor bores. Because of this, the barrel set point was adjusted accordingly, although slight offsets of this type could potentially lead to experimental error. On the other hand, this is again likely not the explanation for the temperature discrepancy because the simulated temperature was also different for both scales.

Depending on the sensitivity of a given CQA to melt temperature in a given formulation, the observed difference of 4-6 °C in melt temperature upon scaling may or may not be problematic. In the case of telmisartan, this temperature difference was great enough to result in a measurable difference in residual crystallinity.

However, at process settings intense enough to eliminate residual crystallinity, such as higher barrel temperatures and higher mechanical energy, the design space may be broader, as was seen in Chapter 5. On the other hand, if a system is thermo-labile or exhibits fast degradation kinetics following dissolution, as was seen with torasemide and other systems (31,128,156), this difference in temperature may not be tolerable. If a narrow temperature range is required for a particular pharmaceutical product, for example one prone to thermal degradation, some options for adjusting the melt temperature could be to adjust the barrel temperature, the screw speed (146), or the volume of material in the extruder, for example, in accordance with the change in surface area available for conduction, as suggested earlier.

The methodology employed here for identifying the quasi-adiabatic point for a formulation for a given hardware setup, i.e. screw configuration, using simulation, and then and using simple scaling approaches coupled with simulation to select ranges for screw speed and feed rate to more precisely inform experimental design could be used to guide scaling approaches in other systems which seek to maintain constant CQAs and simultaneously balance the extruder thermal energy. The two ideas are not mutually exclusive and the relationships between all factors should still hold. Use of a phase diagram plus knowledge of the degradation propensity can support identification of the target melt temperature which will enable meeting the CQA ranges. Simulation can then be used to identify and build a process around the quasi-adiabatic point. Due to all of the inter-dependent and related factors which can affect the melt temperature, and because simulation accounts for these factors, simulation is a promising and useful tool to design a scale-up or -down study. If the

quasi-adiabatic point is too high, or too low, to achieve the required CQAs for a given drug substance, the formulation can be adjusted by addition of a plasticizer or anti-plasticizer, or the screw configuration could be adapted. The feed rate and screw speed, considering their individual impact on the SME, can then be adjusted to tune the process to the quasi-adiabatic point. As was highlighted in Chapter 5, the formulation is not just critical for bio-performance; formulation material properties are also critical to achieve ideal processing performance.