Guest Column | August 20, 2020

Cell And Gene Therapy Manufacturing As Large-Scale Biology

By Mitch Finer, Ph.D., Chief Scientific Officer, ElevateBio

Working In Lab

The cell and gene therapy space is undergoing an exponential expansion. The FDA approved the first cell and gene therapies in 2017 and there are now 17 approved to treat half a dozen different diseases.[i],[ii] In the U.S., nearly 500 U.S. companies have over 350 cell and gene therapies in clinical testing for multiple diseases.[iii] Valuations of the sector vary, but pegged the market size at around $2 billion in 2018 and projected increases to $8 billion or more by 2025.[iv],[v].[vi]

Regardless of the precise numbers, the growth of the cell and gene therapy (CGT) space is rapidly changing the way we think about medicines. More importantly, I believe it is changing the way we must think about making medicines.

While there are many brilliant scientists driving the research and innovation behind the exciting CGT products on the market and in the pipeline, few know how to scale them up and deliver them at an affordable cost. This knowledge gap leaves CGTs well beyond the reach of most patients and, indeed, most of the world. Unless we make major strides in our ability to scale CGTs, we will not be able to “democratize” these medicines and make them accessible to as many patients as possible. Bridging that gap calls for innovation in CGT manufacturing.

Scaling the production of a few million living cells in the lab to manufacturing the billions of cells needed to treat patients comes with its own unique array of complexities. Those complexities require thinking about CGT manufacturing as large-scale biology, a concept that has developed in my mind across my 35 years of working with cell and gene therapies.

Large-scale biology has two dimensions. The vertical dimension encompasses the traditional challenges of making product quantities large enough for clinical testing or the marketplace. The horizontal dimension encompasses the CGT-specific challenges of linking culture conditions to a product’s clinical performance.

Many CGT companies have not yet recognized and adopted this new mode of thinking. They apply the small molecule approach to scaling by waiting to address manufacturing issues until their products are moving towards the clinic. Instead, companies should begin considering the challenges of large-scale biology — vertical and horizontal — at the earliest stages of development.

Vertical Challenges in Scaling CGTs

The vertical challenges of scaling production to meet the needs of clinical testing and the marketplace are familiar to drug companies with small molecules and biologic dugs, and this is where they focus most of their manufacturing efforts.

Manufacturing is more challenging for biologics than for small molecules. CGT manufacture is even more complex, and not simply because biologics companies have had the last 20 years to design, develop, and master their processes. There are distinct differences between CGTs and biologics that put them on two very different learning curves in terms of manufacturing.

First and foremost, unlike biologics and small molecules, CGTs are “living drugs.” This phrase has become something of a cliché but is nevertheless true. As living cells, CGTs are subject to many positive and negative influences — ex vivo in culture and in vivo as therapies — on how they differentiate, grow, and function.

Second, for many reasons, the culture conditions for a cell product do not ramp up linearly between the lab and manufacturing plant. For example, cells can be cultured in suspension (solution) or on plates (adhesion); but not all cell types can be cultured both ways. Cell types also vary in their proliferation rates and the number of times expansion they can undergo while retaining their potency. Other variabilities include differences between cells derived from different donors (for allogeneic therapies) or different patients (for autologous therapies). Additionally, many CGTs are developed in the lab using technologies that are not scalable at all.

It also impractical to scale the manufacture of allogeneic and autologous cell products in the same way, because differing quantities of each are needed for therapeutic purposes. Allogeneic products are manufactured by multiplying the volume of a bioreactor to yield a single, large batch of product that will treat multiple patients — an approach known as scaling up. Autologous products are manufactured by multiplying the number of bioreactors to produce small, individual batches of patient-specific products in parallel — an approach known as scaling out. Each approach has specific challenges.

The more significant and often overlooked complexity in scaling CGT products is that they typically contain a mixture of cells and cell subtypes. For example, a T cell-based therapy may contain both CD4 T cells and CD8 T cells, as well as T memory cells, and T regulatory cells (Tregs) and other specific subtypes of CD4 and CD8 T cells. The relative proportions of subtypes in the final product are subject to many factors and can influence the product’s clinical performance.

In short, it all comes down to the culture. Even if the process for generating two products looks the same on paper, such as putting essentially the same gene construct in a cell — the clinical performance of the end products could be very different depending on the cell source, type and culture conditions. You can’t simply follow the recipe and assume the results will be consistent from one product to the next.

Going Wide: The Horizontal Dimension CGT Manufacture

The horizontal dimension of large-scale biology is largely unfamiliar to most CGT companies, and so it receives little or no attention as they move into manufacturing. This dimension involves learning the biology of CGT manufacturing by testing how specific cell culture conditions influence the properties of the end product and translate to its clinical performance.

Learning the biology of CGT manufacture requires studying a broad range of products; one product, or even a few products, will not reveal the associations between the culture conditions and therapeutic efficacy. It also requires collecting a wide range of detailed analytics on each product, correlating those analytics with performance, and pooling them into a database that can be used to identify which properties of a CGT product are linked to clinical performance – good or bad.

At present, most CGT biotechs have neither the product number or range, nor the big data infrastructure, to gather the broad and deep analytics necessary to conduct large-scale biology. While CDMOs do handle a wide range of products, collecting detailed analytics on each one and applying those learnings to other products is not part of their business model.

At ElevateBio, we gather a breadth of data on CGT products that others do not or cannot collect. We do this for the products from our portfolio companies and from our strategic partners; in return, we apply our collective learnings across multiple products and clients, so that all benefit from the breadth and depth of data we collect. This approach enables us to make specific recommendation to a portfolio company or client, such as “you should look for this marker on this type of cell” as a signal of performance.

To take a concrete example of the application of large-scale biology: an ongoing question in CGT research focuses on identifying the optimum ratio of CD4 to CD8 T cells in a final product. Literature studies do not describe a consistent approach for addressing this problem. Some companies take whatever ratio of the cells their culture conditions yield. Others aim for a 1-to-1 ratio: they sort CD4 T cells from CD8 T cells in the donor (or patient) samples, culture the cell types separately, then recombine them in equal numbers to yield the final product. But no one has done the experiment of generating products both ways, testing each version in a small number of patients, and seeing which gives the better clinical response.

If we were to run that experiment on T cell products at ElevateBio, our broad and deep analytics might reveal that the ratio of specific subsets of CD4 and CD8 T cells are key to a product’s optimum clinical performance, or that the optimum cell ratio varies according to product type.

The two-dimensional concept of large-scale biology underpins ElevateBio’s business model and the ways we address the inherent challenges of CGT manufacturing. We’re developing efficient, cost-effective manufacturing systems that enable our portfolio companies and our strategic partners to make CGTs as potent as possible, so the therapeutic dose – and the associated cost – is as low as possible. We want to take these products to the world so that everyone can benefit.

The biology of CGT will continue to evolve as the space continues to grow, and success in the clinic will always depend on success in manufacturing. We believe companies must therefore balance the thinking that drives innovation against the thinking required to scale the biology, because CGT manufacturing is the far more complex piece of the CGT value chain.