De-risking FOAK

If you mention to a potential investor, partner, or even vendor that your process is first-of-a-kind (FOAK), emerging, new, novel, or nascent, their initial response may involve the word risk. How do you know it will work? What happens if it does not? What can go right – and what can go wrong?

Scaling can be a complex process, fraught with risks, and a single misstep can be costly – or even catastrophic. Add that you are working with an emerging or FOAK technology or process, and you have the scenario for a potential disaster. However, scaling risk can be controlled or reduced, even when working with a new process.

Intentional, deliberate planning is important to reduce risk on an emerging or FOAK project. Although the specific technology or process may yield unexpected results, how you plan and react to the broader goal will directly impact your success.

The basics of initiating a project – such as a project charter and identifying stakeholders – are helpful here, followed closely by a project execution plan, design basis, and risk plan. In particular, the design basis can serve as the foundation, laying the groundwork for decisions and project approach, and should be regularly reviewed and updated for any changes. When dealing with uncertainty, you might wonder how to handle the unknown specifics in the design basis. Some areas will have more certainty than others. Use ranges for quantitative items as needed and let this be a guide for identifying critical areas for further experimentation and confirmation to refine the range to something reasonable and actionable.

Scaling risk can be controlled or reduced, even with a new process

When working on planning and design, identify areas where uncertainty is present or change may occur, and focus on design strategies to accommodate. For example, while we may not know how a particular process will react, we can address specifying the relevant equipment (such as the size of a pump for a viscosity which varies) and consider what factors are known. In this case, consider how to size the required utility equipment (such as electrical feed and control, water or pneumatic requirements, etc) to support the underlying uncertain equipment. The process equipment could be sized based on a range, with the ensuing utility equipment and feeds designed to accommodate that. Some common approaches include upsizing electrical equipment, water and wastewater treatment, and compressed air to react to changes in the served equipment. Often, upsizing this equipment initially is significantly less expensive than selecting the minimum requirement and having to upsize later.

The decision to scale up or scale out can have a broader impact, and the specifics are more complex than can be addressed here. Still, considering both options and the impact it will have on your project is important. Scale out could generally be considered more straightforward. You are making something in a lab or pilot environment, and if you use the same equipment, you should get the same results – so to produce more, use a linear relationship and multiply as needed to reach the desired end result. The challenge, though, is the unit cost is unlikely to improve significantly, and there could be greater variability between different batches or production runs. Scaling up would involve changing the underlying equipment. With biological processes, this may not be as simple as ‘doubling the recipe’ by increasing the size of the process and the equipment by a certain factor, as the behavior of the process may change. But a potential benefit may be unlocking lower unit costs and more consistent batches, as they are larger.

In both these examples (addressing specific uncertainty, and the fundamental decision to scale up or scale out), identify what is known and what is unknown. Are there
any ranges that can be used as constraints? Have experiments been performed at slightly larger quantities, so you have a general idea of the result of larger ones? Perhaps, most importantly, identify and document what is known, and use what is unknown as an area to concentrate further experimentation to refine potential outcomes.

A thoughtful and regularly reviewed and updated risk plan is important alongside the project design basis. What happens if a certain piece of equipment, or a process parameter, needs to be larger or smaller? What is the likelihood, and what is the impact? How can you respond to it? Back to the specific example of uncertainty of viscosity – if you can identify a range, however large – you could consider upsizing equipment, which would have a defined impact (larger equipment which costs more and may require larger utility equipment). Now you have a known impact and can respond accordingly. In a best-case scenario, perhaps for a nominal cost, you can turn an unknown into a known.

Although it may not be possible to remove all risk from an emerging or first-of-a-kind process, with careful and deliberate planning, it is possible to navigate these challenges and accelerate your path to commercial scale manufacturing.

David Ziskind is the Managing Partner at Mach Global Advisors. He helps companies planning for or have recently secured Series A or B funding to launch emerging or first-of-a-kind projects successfully. This article is republished from the Q1 2025 edition of Protein Production Technology International, the industry's leading resource for alternative proteins. To subscribe to all future editions, please click here