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16 Pharmaceutical Technology BIOLOGICS AND STERILE DRUG MANUFACTURING 2018 P h a r mTe c h . c o m tion, but there is considerable variation in peak VCD, with some very low VCD runs shown by the smaller markers in Figure 3. The micro+ scale (red markers in Figure 3) demonstrates extensive variation in its process performance with large variation in peak VCD. Diagnostic analytics Subsequent to descriptive analytics, diagnostic analytics can be performed. In this case study, the batch-scale comparison model is interrogated to uncover why any differences detected (shown in Figure 3) occured. A data scientist could here be interested in comparing batches between scales. Given the deviating cluster on the micro+ scale, an equally relevant scenario would be to first try to interpret the split of the batches on this scale. Regardless of interpretation objective, similar di- agnostics pathways are used. Figure 4 shows a plot often used in diagnostic an- alytics denoted "contribution plot". This plot was created to find sources of variation contributing to the deviating cluster of micro+ batches framed in the top of Figure 3. Figure 4 shows that this cluster of batches started with a higher-than-average sodium trajectory (brown line) and a lower-than-average osmolality profile (purple line), for example; other interesting features are also revealed. Conceptu- ally, similar plots can be readily created to interpret scale differences. Predictive analytics The third stage of the data analytics continuum corresponds to predictive analytics. The term predictive analytics may carry different connota- tions for different people. In one aspect, predic- tive analytics may refer to the act of, given a fresh set of batch process measurements, "classifying" Process Modeling Figure 2: Control chart from a data analytics model capturing batch evolution. The horizontal axis shows batch lifetime in days. The vertical axis is the charted statistic (t), which is a parameter of the data analytics model. The red dashed lines represent upper and lower control limits. Each batch is represented by a single line. As long as a batch line stays within the control limits, normal operating conditions are inferred.