Strategic Approaches to Process Optimization and Scale-up - Almac

More documents

Recommendations

Info

Step 2: Ranking of process parameters in order of importance. The list wasanalyzed using a risk-assessment approach to prioritize the parameters. Parametersgraded as high risk were progressed for investigation. An example parameter ratingform is presented in Figure 3. The example shows a parameter rating form focusing onthe nine parameters from the dry-granulation stage that may have an effect on theCQAs. A separate rating form would be completed for each stage of the manufacturingprocess. A scoring system, ranging from 1 being minimal effect, 3 being moderate,and 9 having a major effect on product attributes, was used. This scoring approachapplies a much greater weighting to parameters deemed to impact a product'sattributes significantly, thus increasing the necessity to further study the effect of theparticular variable.Figure 4: Example results parameterrating form.Figure 4 shows an example of results following the compilation of the scoring process.The example illustrated focuses on a single product attribute (tablet hardness) and asingle processing step (dry granulation). The full exercise produces individual tablescompiling project team views regarding each processing parameter in relation to eachCQA.Figure 5 shows how decisions can be made onwhich parameters may be investigated at the nextstage. The total score is the sum of the scoresobtained for process parameters across all theCQAs. This will provide a rank order of parametersthat may have an effect on CQAs. Using prior experience coupled with knowledge ofthe intended process, the number of parameters can be minimized. The number ofparameters investigated using experimental design will significantly increase thenumber of batches required.Figure 6: Detail of parameter riskassessment.Step 3: Assessing the impact of parameters on the product. The parameters werefurther screened by considering the higher ranked parameters in each processing stepas having a high influence on each CQA. Also, every parameter having a score of 40or more was classified as having a high influence on CQAs. An example matrixshowing the impact assessment for the drygranulation step is presented in Figure 6.Step 4: Determine the parameters to beinvestigated experimentally. Following a full analysis using prior knowledge andexperience of the formulation and the manufacturing techniques, conclusions will bedrawn from the risk-based classification process to list the parameters to beinvestigated using a first-screening experimental design (see Table II).The parameters were investigated using a 2-level screening design of experiments. Inthis example, 10 parameters were chosen to be screened.Figure 3: Example parameter rating form.Figure 5: Parameter evalution todetermine which parameters should beinvestigated.Table II: Parameters to be investigated inexample analysis.Figure 7: The relationship between thenumber of parameters and resolution ofdesign to the number of experimentsrequired.The number of parameters, in addition to the desired resolution of the design, impactson the number of experiments required in determining the critical parameters. Figure 7shows the relationship between number of parameters and resolution with number ofexperiments required. Additional considerations such as time and activepharmaceutical ingredient constraints may also influence the number of experimentsthat are possible at this stage.Pharmaceutical Tech ‐ Sep 10 ‐ Process Opt & Scale‐Up
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
Page 1 and 2: Strategic Approaches to Process Opt
Page 3: The tablet cores are progressed for

Strategic Approaches to Process Optimization and Scale-up - Almac

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?