Garbage In, Garbage Out: The Case for More Accurate Process Modeling in Manufacturing Economics - A case study in capturing indirect costs and benefits. - BioPharm International


Garbage In, Garbage Out: The Case for More Accurate Process Modeling in Manufacturing Economics
A case study in capturing indirect costs and benefits.

BioPharm International
Volume 22, Issue 8


Figure 2. A comparison of the economic effect (NPV: net present value) of calculation errors2
Figure 2 shows the outcome of an analysis done for a retrofit project at a large biotech manufacturer interested in installing a new perfusion-based downstream processing technology. The net present value (NPV) of the scenario was $35 million over five years.2 Figure 2 compares the three most significant causes of error in economic evaluations: incorrect raw materials costing, construction and installation costs, and incorrect estimation of the quantity produced by that scenario. Each of these three categories is altered by 5%, 10%, and 20% respectively, to see their relative effect on the NPV.

As shown, the cost category that is most sensitive to errors is the quantity produced, or supply of material to the production network. Small inaccuracies in this metric produce significant negative impact on the NPV of the scenario in the case of a 20% inaccuracy, actually causing the project to have a negative return. Accurate supply-based models are essential to establish accurate metrics for the value of retrofit scenarios. In the next section, we discuss this type of modeling in a case study involving a major biopharmaceutical manufacturer.


Supply-based planning can be seen in retrofit projects that aim to allow higher titer products to be produced in existing biopharmaceutical manufacturing plants. With the rapid advances in cell culture and fermentation technology, many plants suffer from a bottleneck in downstream (purification) operations. A project with a major biopharmaceutical company was undertaken to establish the most cost-effective means of producing 4 g/L products in a facility designed for the 1–2 g/L range. Although a number of alternatives were considered, the two most practical options were determined to be split batching, in which the fermentation volume is split in two at harvest and processed in two separate lots and partial batching, in which a reduced fermentation volume is prepared, exactly enough for the downstream capacity. Both required similar infrastructure investments and resulted in similar downtimes for retrofit.

The economic comparison of these two scenarios was therefore predicated on their comparative run rates and manufacturing production profiles. However, there was considerable disagreement from subject matter experts on which of the two scenarios was better. Batch-splitting could be performed after the Protein A recovery step, a possible plant bottleneck, but it was unclear whether the material would exceed time at ambient specifications if required to wait for the other half of the "split" batch to complete processing. Partial batching produced less material per batch, but seemed to maximize the downstream plant's capacity for each batch.

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