Quality and Reliability Methods - SAS

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300 Degradation Chapter 16 Destructive Degradation Figure 16.21 Plot of Model 18. Select Generate Report for Current Model. 19. At the bottom of the report in the Profiler, enter the following values: – 40 for Newtons – 260 for Weeks – 25 for Degrees C Figure 16.22 Distribution Profiler Results The predicted proportion of units below 40 Newtons after 260 weeks is 0.000151, with a confidence interval of 0.00001 to 0.00153.
Chapter 16 Degradation 301 Stability Analysis Stability Analysis Stability analysis is used in setting pharmaceutical product expiration dates. Three linear degradation models are fit, and an expiration date is estimated following FDA guidelines (Chow 2007, Appendix B). The three models are the following: Model 1 Model 2 different slopes and different intercepts for the batches. common slope and different intercepts for the batches. Example Model 3 common slope and common intercept for the batches. The recommended model is determined by the following procedure: 1. Fit Model 1 with the time effect coming first in the model, followed by the batch effect, then the interaction. Using Type I (Sequential) sums-of-squares, test for equal slopes (Source C in the output). – If the p-value is less than 0.25, the slopes are assumed to be different across batches. The procedure stops and Model 1 is used to estimate the expiration date. – If the p-value is greater than 0.25, the slopes are assumed to be common across batches. The procedure continues to step 2. 2. If the conclusion from step 1 is common slopes, then test for equal intercepts using Type I (Sequential) sums-of-squares from Model 1 (Source B in the output). – If the p-value is less than 0.25, the intercepts are assumed to be different across batches, and Model 2 is used to estimate the expiration date. – If the p-value is greater than 0.25, the intercepts are assumed to be common across batches, and Model 3 is used to estimate the expiration date. When Model 1 (different slopes and different intercepts) is used for estimating the expiration date, the MSE (mean squared error) is not pooled across batches. Prediction intervals are computed for each batch using individual mean squared errors, and the interval that crosses the specification limit first is used to estimate the expiration date. Consider the Stability.jmp data table. The data consists of product concentration measurements on four batches. A concentration of 95 is considered the end of the product’s usefulness. Use the data to establish an expiration date for the new product. To perform the stability analysis, do the following steps: 1. Open the Stability.jmp data table in the Reliability folder of Sample Data. 2. Select Analyze > Reliability and Survival > Degradation. 3. Select Concentration (mg/Kg) and click Y, Response. 4. Select Time and click Time. 5. Select Batch Number and click Label, System ID. 6. Select Stability Test from the Application menu.
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References Abernethy, Robert B. (19
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References 407 Carroll, R.J., Ruppe
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References 409 Haaland, P.D. (1989)
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References 411 Lawless, J.F. (1982)
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Index JMP Quality and Reliability M
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Index 419 Fit SEV 242 Fit Weibull 2
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Index 421 Q Quantiles table 356 R R
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Index 423 Weibull Plot 360 Westgard
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