How to Evaluate the Cost Impact of Using Disposables in Biomanufacturing

To understand the overall cost impact of disposable technologies, it is necessary to build a robust model that covers the entire process.
Jun 01, 2008
Volume 21, Issue 6

Andrew Sinclair
The growing acceptance and adoption of disposable technologies raises the question, What is the cost impact of these technologies? This question sounds simple but hides complexity, in terms of what is included in the cost evaluation and the evaluation methods used.


Disposable technologies have the potential to significantly reduce plant complexity and initial start-up capital costs.1 The benefits of disposable technologies, however, extend beyond reducing start-up costs, and also can include:

  • reduced time to market, based on a quicker build and validation of facilities
  • reduced capital investment, resulting from reduced capital infrastructure
  • reduced cost of operations
  • improved flexibility in operation, in terms of managing process and product change
  • improved compliance
  • simpler material and people flows.

As a result, many companies now wish to understand the broader cost impact of disposables. The critical question is, What is the best evaluation method?

To evaluate costs, a robust cost model is required, in which the methodology and assumptions are transparent. Such a model will provide managers with better insight into the key cost drivers of the manufacturing process and the sensitivity of the overall cost of goods to changes in these key parameters. A good model helps evaluate the cost impact of implementing different technologies and the effect of process changes, such as increasing product titers and yields, and can be validated with financial accounting data.

Some of the commonly used methods for evaluating projects are net present value (NPV), internal rate of return (IRR), return on investment (ROI), and cost of goods sold (COGS). In biopharmaceutical manufacturing, the COGS model is by far the most commonly used method. Although the COGS model has the merit that most people in the industry understand it, it is not the most rigorous or sophisticated method. For example, a COGS model should not be used when there is a need to understand the interplay among the expenditures, timing, and project risk.

The other three methods, NPV, IRR, and ROI, all provide useful tools for decision-making, particularly for capital investment and project approval. NPV and IRR are particularly useful for evaluating potential long-term projects because they account for the upfront investment required as well as the timing of future cash flows and the risk and opportunity cost of the project. Given that disposables can delay and reduce capital expenditure, these methodologies are able to capture that benefit together with the cash flows associated with manufacturing operations.

The NPV methodology is the best technique to analyze alternative technologies and manufacturing strategies, because it accounts for the impact of delays in expenditures and properly accounts for the time value of money.

No matter which manufacturing cost model is chosen, it is important that certain management accounting techniques, such as lifecycle cost analysis and activity-based costing, be incorporated into the model to account for the significant effect manufacturing efficiency has on the cost of goods. For example, the number of successful production runs per year and the cost of facility downtime and batch failure often have a much greater effect on overall manufacturing costs than changes in raw material or labor costs. Also, one should exercise care in comparing cost figures from different sources. Common problems when comparing data relate to consistency in methods and assumptions, especially when it comes to handling capital costs.


Table 1. Operating sequence for a typical reusable column
Once the optimum cost analysis model has been identified, the next step is to define the purpose of the analysis, for example, technology evaluation, supplier evaluation, or operations optimization.

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