Data analysis batch operation variability

Based on the analysis of the preformulation data, likely excipients are selected and small batches may be produced. The number and size of the batches depend on the availability of the drug substance. The batches are intended to assess the feasibility of the formulation, including the types and levels of excipients, as well as the process and its operational variables, such as order of addition, mixing times, compression force, granulation time, etc. The goal is to develop a formulation and process that meets the criteria set forth earlier under Objectives. 

In some cases, an actual process variable (such as yield) can be the objective function, and no process model is required. Instead, the process variables are varied systematically to find the best value of the objective function from the specific data set, sometimes involving design of experiments as discussed by Myers and Montgomery (2002). In this way, improvements in the objective function can be obtained gradually. Usually, only a few variables can be optimized in this way, and it is limited to batch operations. Methods used in industrial batch process applications include EVOP (evolutionary operation) and response surface analysis (Edwards and Jutan, 1997 Box and Draper, 1998 Myers and Montgomery, 2002). 

Data from 23 normal operating batch runs are available. The variables measured during the run of the batch process are added, amount of hydrogen, pressure and temperature. The process data are collected at 101 equidistant points in time. The point of the melting curve related to a temperature of 35 °C is chosen as the quality variable. Hence, a problem results of relating a quality variable y (23 x 1) with a three-way array of process variables X (23 x 3 x 101). Prior to analysis, X and y are centered and scaled across the batch direction (see Chapter 9). Subsequently, both X and y are scaled to unit sum of squares. 

The hrst part serves as an introduction to the subject title and contains chapters dealing with history, process variables, basic operations, chemical kinetic principles, and stoichometry and conversion variables. The second part of the book addresses traditional reactor analysis chapter topics include batch, CSTRs, and tubular flow reactors, plus a comparison of these classes of reactors. Part IH keys on reactor applications that include thermal elfects, interpretation of kinetic data, non-ideal reactors, and reactor design. The book concludes with other reactor topics chapter titles include catalysis, catalytic reactions, fluidized and fixed bed reactors, biochemical reactors, open-ended questions, and ABET-related topics. An Appendix is also included. 

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