Take the Test: Evaluating Commercial Readiness, Pt 2

September 22, 2016 |

Mark Warner HeadshotBy Mark Warner, PE, Founder, Warner Advisors LLC

Special to The Digest

The first installment of the series, here, discussed the need to determine an understanding of what success looks like to be able to adequately evaluate if an advanced biotechnology is ready for commercialization. Now, let’s move into the details of evaluating the state of technology and readiness for commercialization. At the end of the document there is a link to an excel based worksheet that provides a scorecard to evaluate the state of development. The value and reliability of the analysis is significantly affected by the accuracy of the data used, so it is important to remember the “drivers license test” discussed in part 1 when determining the current status for each of these areas.

As an example for demonstration purposes, let’s use the di-methyl glop (DMG) process I have noted in previous series. DMG is an industrial chemical made by fermentation, then separated by centrifugation, purified by crystallization, dried and packaged. We will assume the process is currently operated at a 45,000 pound per year pilot plant and the goal is to build a 2,000,000 pound per year commercial scale facility. A block flow of the process is shown below.

dmg-block-flow

In looking at any advanced biotechnology, there are 5 primary criteria that are used to evaluate readiness for process commercialization as outlined below. None of these criteria individually are a deciding factor, but rather in aggregate are the information needed for the analysis and will be the inputs required for the evaluation tool:

Number of unit operations – The top criteria that usually determines the level of complexity in process development is the total number of unit operations (processing steps) involved in the overall production process. The more unit operations, the higher the level of effort required to make a fully integrated process that functions effectively with them. In the DMG example, there are 5 unit operations, which represents the lower end of the range for most advanced biotechnologies. This is primarily because the DMG process has an organism that excretes the final product. In many processes, the product is inter-cellular and requires the cells to be disrupted (homogenized, bead milled, acid/base, etc.) and then isolated (MF, UF, TFF, chromatography, etc.). This often expands the total unit operations in the overall process to 10 or more.

Scale-up factor – This is the growth in size between where the process is currently operating and the proposed production level. In the case of DMG, the commercial scale facility is proposed for 2,000,000 pounds per year and the pilot plant that has been operating has an annual production rate of 45,000 pounds, so dividing the two give a scale-up factor of 44:1. The larger the scale up factor, the more risk involved. It is also possible to look at the scale-up factor of each unit operation and then average them. This approach can show a lower level of risk where scaling up involves multiple pieces of identical equipment (fermenters, centrifuges, etc.)

Status against key process criteria – Every process has a handful of key criteria that are the most important technical milestones needed for the process to be commercially viable. These are typically the items in the techno-economic model that have the most impact on total manufacturing cost when a sensitivity analysis is run. Fermentation titer, product yield per unit feedstock and overall recovery yield of product are some of the most common examples. To determine the overall status against process criteria, divide the the current status of each criteria against its target, then average them. For the DMG example, in the case of titer, the target is 50 grams per liter, but the pilot is currently operating at 35 grams per liter, so the ratio is .70 or 70% of target. Example calculation for each criteria and overall averaging is shown below:

key-criteria

The risk in key criteria comes both from how far any individual criteria is from the target and also how far the overall average process criteria is from the target. In cases where there is a significant difference of importance between criteria, the individual criteria can be weighted in the calculation, as appropriate.

Fully integrated versus independent operation – It is critical when gathering data at bench or pilot scale for a process, that the process is fully integrated, meaning it is run in a continuous manner in the same location from feedstock to final product. This is the desired standard. In some cases, the process needs be broken into pieces with some portions of it (say fermentation) happening at one site, with broth shipped to another site for downstream recovery. While the second approach does demonstrate the process can produce product, the data generated is of less value than a fully integrated process.

Length of testing at previous stage – The length of time that a process is operated in a continuous manner is very important to determine the quality of data for minimizing risk in scale-up. As contaminants can build up in a process over time, it is common for some problems not to be demonstrated until after weeks of operations. 1,000 hours of continuous operation of the process at the planned conditions is the industry standard. Processes can (and have) been scaled with less operational time, but it does come with higher risk.

When conducting an assessment of process readiness, it is usually helpful to generate a framework diagram showing the block flow of the process at pilot, demonstration scale and commercial, with corresponding production levels. This allows for a more intuitive visual assessment of the magnitude of scale up and highlights if any of the unit operations have changed at the different stages of development.

scale-up-framework

Commercialization Readiness Scorecard

The link here is to an excel based scorecard that takes the key information discussed in this series and provides feedback on state of readiness. A pdf example for the DMG process is also shown below. Given the level of information required, it is a high level assessment, but can provide key insight to which areas are of highest risk and where resources are best spent to close technical gaps. For more information or insight on your individual scorecard, contact the author to discuss.

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Mark Warner is a registered professional engineer with 30 years of experience in process commercialization, focusing for the last 10 years on taking first-of-a-kind-technologies from bench-top to commercial operation. He has worked for four companies who have held the #1 spot in biofuels digest’s top company list, in a range of advanced biotechnologies including biodiesel, cellulosic ethanol, phototrophic algae, heterotrophic algae and innovative food products. He is the founder of Warner Advisors, providing consulting services and acting in interim engineering leadership roles for advanced bioeconomy clients. He can be reached at [email protected] or visit www.warneradvisorsllc.com.

 

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