By Dr. Alex Brindle
There is little doubt that the effects of process analytical technology (PAT) and quality by design (QbD) are starting to affect the way the life sciences industry operates. PAT and QbD will significantly influence the development process, submissions, manufacturing, and quality systems if implemented to their full capabilities.
PAT and QbD can create immense financial impacts on organizations. Facilities will run at much higher throughputs due to improved overall equipment effectiveness and improved operator efficiency. Scrap levels will be reduced significantly, saving not only material costs but the quality effort in corrective actions. The real-time release of product will reduce stock levels. Development will supply processes to manufacturing with design spaces that explain the understanding of the process so that manufacturing is 100% effective from day one and requires no ramp-up period.
Despite all these major advantages — which are undoubtedly worth billions of dollars annually — there has been only a relatively steady uptake of QbD and PAT, typically by big pharma, and even then only on selected projects. So why the slow adoption of QbD and PAT? Perhaps one of the key reasons is that the people who first championed PAT and QbD within organizations were the scientists themselves. Consequently, there has been an emphasis on the scientific benefits of pursuing PAT and QbD. This is at the expense of the more business-minded reasons, which can typically be traced back to financial benefits in some way.
There have been numerous examples of proposals for PAT & QbD projects that talk a lot about process understanding that completely miss the business drivers. I’m not suggesting that there is only one way to obtain QbD and PAT project funding, but it is quite normal for projects to not move forward because of financial constraints. This is simply because the typical organization has only a few projects that it can afford to pursue at any one time. Therefore, the projects that do receive money have made the best case to receive funding — this is usually the strongest business case. A good business case should quantify:
Discussions of being at the forefront of technology, innovative science, and process understanding are all very nice, but they will typically fail as a robust business case (though there are exceptions where investment boards believe it is the right thing to do) unless the above points are identified and quantified.
Building A Financial Model
From an analysis perspective, building a financial model is a balance of costs compared to benefits. Project costs are generally:
The project costs should consider the key aspects of implementation. It is obvious to think of costs in terms of purchase of equipment, but true costs are always much more significant than this; the equipment is only a minor percentage of the implementation costs. For example, a small project for implementing a NIR (near infrared) device will cost much more than the equipment itself. There are all the costs of development, engineering (getting the probe into the tank — who will design the fittings and fabricate?), validation, control system integration, project management, and probably numerous others. The true cost of implementation can be four to seven times the cost of the NIR device.
Operational costs should also be considered (especially for large implementations) so a true life cycle picture of costs can be determined. Timelines are crucial to determine how the project will fit into the portfolio of projects. The timeline also tells you cash flow and project/facility resources are needed. Timelines can, of course, be compressed or lengthened due to business need. Quite often, timelines are useful to have buy-in from management at the start, as there is a tendency for small projects to “drift” — there are many examples where a simple installation which should have taken four months from development to validation ended up taking years to complete because it gets depriortized. Any business case should strive to quantify the financial investment benefits, operational financial benefits, and other financial benefits.
The Benefits Of QbD & PAT
The financial investment benefits of QbD and PAT are potentially huge. This is especially true when it comes to reduction of investment in new or upgrading of facilities. That’s because QbD and PAT are making production more efficient, so they are squeezing more out of the current facility or impacting the design to give a much smaller new facility. There are examples where QbD and PAT have negated the need to build entire facilities because of the operational improvements in the current facility.
There are numerous financial operational benefits from QbD and PAT, such as increased yield, less routine analysis, and ease of technical transfer. It will take time to assign a financial number to these benefits, but it is worth the effort because the numbers can be big. The bigger the financial benefits, the smaller the initial investment looks. (Any logical investor likes this.)
There are numerous simple financial models to assess how good an investment looks compared to its return. ROI models are extremely simple and provide a payback time of the initial investments. ROI models are very useful for simple projects as they can easily gauge how “good” an investment is. Net present value (NPV) is another useful technique, as it shows the cash flow over the expected life cycle (both investment negatives and benefit positives).
There are many other types of financial models that clearly display the investment value of what QbD and PAT bring to an organization. The key is to find what works best with the people who control the investments and use the model that they expect to see.
We live in a complex world, so it is not always possible to put a financial value on everything. In this case, it should be possible to list perceived benefits and detractions to QbD and PAT projects. An example of a positive could be improved workforce morale, as they will be working with a cutting-edge methodology instead of old-fashioned, routine work. (It is my experience that PAT, in particular, can bring a new sense of excitement to bored analytical scientists.) The flip-side is the danger to the organization of adapting to widespread technology changes. In other words, are multiple people ready to accept and successfully use QbD and PAT (hence the need for careful planning, communication, and change management to be successful)?
There are also the business risks to the investment or benefits. These may include the possibility of the project costing more, taking longer, or even failing.
While it is useful to list out these benefits (or so-called “soft” factors) and risks, it is much more worthwhile to use semiquantitative techniques to understand how they rank against each other to assist in decision making. Often, projects are chosen using visualization of all of the previous techniques mentioned. For example, an investment cost can be combined with financial benefits and operational costs in a life cycle NPV and then ranked against soft factors and risk. This can be the best way to select the right portfolio of projects, since it distills all the numerous data and feelings into two simple numbers that can be visualized. So, the best combination of financials and risk/soft factors can be used to choose the right projects in as objective a fashion as possible.
Beyond these operational considerations, there are also the higher level strategic directions of the company to consider. This could be a drive to improve quality or an increased use of outsourcing for manufacturing. Any project should be understood in this wider strategic context. For example, the use of QbD and PAT could greatly improve technology transfer to CMOs as either would greatly enhance process knowledge and the drive toward turning this knowledge into data, which is much easier to transfer. In contrast, it should be determined whether the CMO is ready for advanced QbD and PAT if they have not invested in it already. Understanding companywide strategic drivers will greatly assist QbD and PAT projects as they typically have the company’s best interests at heart — the projects just have to be placed in the right context so the links to these strategic drivers can be made.
About The Author
Dr. Alex Brindle is the director of consulting for NNE Pharmaplan in North America with responsibility for offices in Boston; Philadelphia; Raleigh-Durham, NC; and San Francisco. His main interests include capital investment programs in life sciences, 21st century life sciences technology and methodology, and influencing development, operations, engineering, and facility design to take advantage of better ways of doing business.