With dozens of regulatory approvals worldwide and hundreds of late-stage trials underway, cell and gene therapies (CGTs) have firmly established their clinical efficacy across oncology, rare diseases, and regenerative medicine.
But as the science has advanced, a new reality has emerged: showing that a therapy works in a small-scale clinical setting is no longer enough. To truly reach patients, these therapies must also be commercially viable, and that means tackling some of the industry’s toughest challenges: reducing the cost per dose and scaling production to meet demand.
These challenges raise important questions for the industry: Where are the biggest drivers of cost in CGT manufacturing? Can process design, automation, and scale-up be approached differently to avoid high cost of goods sold (COGS) and achieve commercially viable scale?
Answering these questions requires moving beyond qualitative assumptions and toward rigorous, data-driven modelling of COGS across the full manufacturing lifecycle.
A shift in expectations
As companies in the past decade successfully proved clinical feasibility with impressive clinical trial outcomes, manufacturing was rarely part of the conversation. This has meant that translation to commercial viability at scale has proven an intractable challenge for too many developers.
Hence, the COGS for CGTs remains prohibitively high, often making the cost per dose a barrier to patient access even when there is a clear unmet clinical need. Economies of scale have been harder to achieve than anticipated, leaving the commercial sustainability of many promising therapies uncertain.
Compounding this challenge, current healthcare financing models are ill-equipped for one-time, high-cost treatments, leading to payer resistance, administrative delays, and regulatory barriers that is stalling progress towards commercial viability. As a result, investors, regulators, and payers now expect a credible path to scale alongside clinical proof.
All this means that it’s no longer sufficient for a company to demonstrate that its therapy works; it must also show how it can be produced efficiently, consistently, and at a price that supports broad adoption. This marks a significant shift in the industry mindset, from “can we make it?” to “can we make it commercially feasible?”
Legacy processes as a barrier to scale
Many manufacturing processes for CGTs were developed in an academic context, suitable for the generation of scientific data but without the process robustness and controls needed to manufacture at scale. When companies reach the commercialisation stage, they often find themselves trapped by their own processes.
If a manufacturing process is ‘good enough’ to reach 100s of doses per year, enabling clinical data to be generated, there is a risk that decisions around scaling are deferred to later in the clinical development. With early clinical successes and accelerated approval pathways, developers may unwittingly pass a critical point of no return with a process that is poorly scalable.
In a vicious circle, when it comes to adapting the process to accommodate commercial scales of 1,000-10,000s, the high burden of comparability studies pushes developers into retaining the legacy processes.
New bottlenecks impacting commercial viability
Even with investment in more scalable manufacturing processes, new constraints emerge. Quality control (QC) has become the next major bottleneck. Most QC processes still depend on labour-intensive, end-point testing that creates delays in product release, drives up costs, and restricts throughput.
A range of solutions exist to address these constraints, such as laboratory automation, modular manufacturing, closed consumables, and data-driven QC. However, interdependencies between upstream, downstream, and QC processes remain; making changes in one area often affects several others.
Assessing manufacturing processes holistically calls for skills such as design for automation and workflow assessment, skillsets that are often distinct from those found in the PD and MSAT teams. Even for those teams that have optimised other biologics processes, the realities of working with patient-derived materials, managing complex supply chains, and maintaining tight process control create a need for new approaches.
Without a full understanding of the end-to-end workflow and the manufacturing roadmap, automation risks simply shifting bottlenecks rather than removing them. To truly move the needle, developers need a deep understanding of how value is created, or lost, across the entire manufacturing workflow.
Solving the cost and scale challenge
Such an understanding begins with quantifying those relationships: determining which processes to automate or close, when to scale them, and how each decision affects overall cost and throughput.
The concept of COGS is deceptively simple yet profoundly complex in practice. Every variable going into the sold cost of the product, including materials, labour, equipment, process duration, and logistics, interacts in ways that make optimisation challenging.
Even small adjustments within upstream or downstream processes can influence the entire workflow, changing efficiency, product quality, and overall cost. Taking biopharmaceutical manufacturing as an example, the pitfalls of chasing isolated efficiency gains are clear: in mAb production, intensifying upstream steps can make purification the new rate-limiting step.
Reducing COGS requires system-level thinking and quantitative modelling that links process parameters to economic outcomes. By simulating how different manufacturing strategies affect both performance and cost, developers can identify where investments in automation, equipment, or facility design deliver the greatest return.
Modelling COGS allows developers to explore how process changes interact across the entire workflow, enabling readiness for automation. By anticipating future manufacturing needs before clinical success, biotech companies can plan where to apply automation or redesign for maximum impact, and identify ahead of time where technology gaps still exist. This foundation provides processes that are adaptable, scalable, and economically viable, setting companies on the path to long-term commercial success.
The next generation of CGT success stories will be built not only on clinical innovation, but on scalable, economically sustainable manufacturing. At TTP, we are helping companies get there faster by modelling the COGS, exposing hidden inefficiencies, and designing practical solutions that close the gap between lab and market.
Want to learn more? You can download our Industry Agenda to discover how to avoid the development bottlenecks that are holding others back from achieving scale.
