Strategic Approaches to Process Optimization and Scale-up - Almac

The standard experimental design notation is presented in Figure 8, where X is thenumber of levels being investigated. A level is a particular parameter value. In thecase of compression speed, the two levels could be the maximum and minimum turretspeed that would potentially be used in an operation. K is the number of parametersbeing investigated. P is the degree of fractioning that is being performed in order toreduce the number of experiments. A full factorial design would not have a value for pdisplayed.For example, 25 would be a two-level design covering 5 parameters. This wouldrequire 32 experiments to investigate the parameter effects. 25-1 is a fractional designof this example where the number of experiments required is halved to 16. As the degree of fractioning increases thequality of information obtained from the design decreases. A typical approach would be to use a high-quality (highresolution) design for optimization and in-depth study of a process and use a low-resolution design for initial screening inorder to determine critical parameters. The design would then generate a number of experiments that detail the exactparameters to set for a manufacturing operation. Each experiment would be completed and the subsequent productattributes would be determined. Statistical software is used to analyze the effect of the process parameters on the productattributes and determine how critical each parameter is.Figure 9: The influence of granulator finalscreen size and roller pressure on tablethardness.screen size decreases, the tablet hardness increases.In the described example, the results of the experimental design allowed the numberof potential critical parameters for the initial screening to be reduced to eight. Theseeight parameters were then investigated using a more comprehensive 3-level design.This type of design, also referred to as a response surface method (RSM), will requiremore experiments. The previous 2-level screening design is used to minimize thenumber of parameters investigated so as to minimize the number of experiments atthe 3-level design stage. In this example, the results of the 3-level design enabledstatistically significant models to be calculated showing the effects of the criticalparameters on a number of product attributes. A graphical example of a modeldisplaying the influence of granulator final screen size and roller pressure on tablethardness is shown in Figure 9. As can be seen, as the roller pressure and granulatingStep 5: Design space. The linkage between the process inputs (input parameters and process parameters) and theCQAs can be described in the design space. The risk-assessment and process-development experiments described cannot only lead to an understanding of the linkage and effect of process inputs on product CQAs, but also help identify theparameters and their ranges within which consistent quality product can be achieved.Approach 3: Hybrid method combining elements of approaches 1 and 2.Figure 8: Standard experimental designnotation.The use of a full design of experiments approach can result in a significant amount of batches being manufactured tocover the design space. As the number of batches required to describe the design space increases, the developmenttime and cost increases. A third method combining elements from approaches 1 and 2 optimizes the balance betweendevelopment time and cost and maintains a good understanding of the manufacturing process. This hybrid approach canbe achieved by breaking the manufacturing process into defined sections. The initial blending step can be performedusing Approach 1. The blend could be manufactured to specification, and end-product testing will show the quality (e.g.blend uniformity/assay). Parameters such as blending time and blending speed can be determined by intensive blenduniformity and bulk-assay analysis allowing blending windows to be established. A second confirmatory batch could bemanufactured using the parameters obtained from the initial batch that could provide additional confidence in themanufacturing process.The blend will have been shown to meet specification and can then be progressed to the next processing steps. Anexperimental design approach can then be performed. For example, the next steps could involve dry granulation followedby compression into tablets. As described in approach 2, following completion of a full risk assessment and subsequentcause and effect diagram detailing the potential process parameters, a structured design of experiments plan can bePharmaceutical Tech ‐ Sep 10 ‐ Process Opt & Scale‐Up