There are FDA-approved therapies on the market today that can permanently resolve a disease in a single administration, for a price of one to three million dollars. The reimbursement system responsible for covering that cost was built around medications that people take every day for the rest of their lives. That structural mismatch has already produced real consequences: companies with approved, effective therapies have stopped producing them.
I am a Partner at Blue Matter Consulting, where I work directly with pharmaceutical and biotech companies on R&D strategy and transformation. Over the past several years, I have watched the science of cell and gene therapy mature at a pace that would have seemed unlikely a decade ago, and I have also watched the commercial, manufacturing, and regulatory infrastructure around it struggle to keep up. Understanding where those gaps are and why they exist matters for anyone building R&D portfolios, evaluating life sciences investments, or thinking carefully about where medical innovation actually goes from here.
What These Therapies Are Built to Do
Most medications work by managing a disease rather than resolving it. A patient with high blood pressure or a thyroid condition takes a medication every day to activate or suppress a particular biological pathway consistently enough to maintain health over time. That model has produced extraordinary outcomes across many diseases, and it has also shaped the entire economic architecture of healthcare: insurance premiums, reimbursement structures, and generic pricing all assume ongoing maintenance as the standard.
Cell and gene therapy approach the underlying problem from a different starting point. Gene therapy introduces, alters, or replaces genetic material in the body. If a disease is caused by a missing or damaged gene, a functioning copy can be delivered to address the source. Cell therapy transfers living cells into the body to restore or establish normal biological function. CAR-T cell therapy, the field’s most visible example, extracts immune cells from a patient, engineers them to recognize and destroy cancer cells, and reintroduces them. In successful cases, the result is a single administration that addresses the disease at its biological root.
The scientific progress here has been substantive. Therapies for sickle cell disease and several blood cancers are now approved and in practice. Researchers are actively studying CAR-T beyond oncology, examining its potential in autoimmune diseases, which carry significant population-level implications given how many people worldwide manage autoimmune conditions through chronic immunosuppression with systemic side effects. CRISPR-based gene editing has moved from fundamental research into clinical application: a recent case at the Children’s Hospital of Philadelphia, in which a therapy was developed and administered to a patient in approximately six months, demonstrated what becomes possible when manufacturing readiness, scientific urgency, and regulatory clarity converge. The science, in a growing number of cases, works.
Where the Infrastructure Has Not Kept Pace
Despite those advances, several companies holding FDA-approved cell and gene therapies have been unable to sustain commercial viability and have stopped producing those therapies entirely. The challenge in each case is structural, and it plays out in two distinct places.
The first is manufacturing. Many of these therapies are produced on what amounts to an individual basis: cells are extracted from a specific patient, prepared, and reintroduced. Scaling that process reliably requires chemistry, manufacturing, and control infrastructure that the industry has not yet fully built — facility standards, process validation requirements, and quality systems designed for a production model that did not previously exist at this scale. Scientific progress in this space has moved ahead of manufacturing readiness, and the gap between them carries real cost and operational consequences.
The second is reimbursement. A one-time therapy priced at two to three million dollars creates a cost equation that payers have not yet developed a sustainable model to absorb. In the US, individuals change health insurance with notable frequency. A payer who covers a three-million-dollar one-time cure may not retain that patient the following year, and the return on that investment does not hold under current actuarial assumptions. In government-administered healthcare systems outside the US, the challenge takes a different form: population-level budget decisions make it difficult to justify a single high-cost administration for a limited patient population, even when the clinical evidence is strong. Payer evidence thresholds are rising in response to price, placing an increasing burden on sponsors to demonstrate provable, durable efficacy before access is granted.
These are structural constraints, and they have contributed to some of the most significant commercial failures in this space. They reflect a mismatch between what science has become capable of producing and what the surrounding system was designed to support.
What Changes Over Time
There is a reasonable basis for optimism about the long-term cost trajectory. If AI tools have a measurable effect on the pace of drug development and the cost of clinical trials, therapies priced today at two to three million dollars may be priced differently in a decade. AI-discovered compounds are beginning to enter later-stage clinical trials, and if those results are positive, they will represent the first real evidence of how compressed development timelines affect drug economics at scale. For cell and gene therapy specifically, where development costs and manufacturing complexity both contribute to the pricing that makes reimbursement so difficult, that kind of shift would be consequential. The shift from the currently-dominant autologous cell therapy paradigm to allogenic cell therapies also has the potential to reduce costs and make these therapies more accessible.
There are also policy signals worth watching. Regulatory changes at the FDA over the past year have reflected a clear interest in accelerating development timelines and approval pathways. If that direction holds, the administrative burden on sponsors decreases, and the time from discovery to patient access shortens. That matters both for individual therapies and for the broader question of whether the commercial model around one-time curative treatments becomes viable at scale.
What This Means for R&D Strategy
For organizations building R&D portfolios, the question worth working through carefully is which part of the problem a given program or partnership is actually positioned to solve. Scientific discovery has advanced. Spatial biology, improved genomic analysis tools, and AI-accelerated target identification are changing what is biologically possible. The constraint on getting transformational therapies to patients at scale is now downstream of discovery, in manufacturing infrastructure, evidence generation for payers, and commercial model design.
In my experience working across these functions, the organizations that close this kind of gap are the ones that treat regulatory strategy, market access planning, manufacturing readiness, and clinical evidence generation as an integrated challenge rather than a sequential handoff. Depth of knowledge in any one of those domains compounds in value when it is developed in genuine dialogue with the others. The science of cell and gene therapy has demonstrated that some diseases can be resolved at their source. The work ahead is building the systems capable of delivering that resolution to the patients who need it.
Author Bio
Tara Austraat-Churik, Partner and R&D strategy leader, Blue Matter Consulting
Tara Austraat-Churik is a Partner and R&D strategy leader working at the intersection of drug discovery, clinical development, and AI-driven transformation. At Blue Matter Consulting, she helps pharmaceutical and biotech executives make decisions that align science, clinical development, and execution from bench to bedside. Her career spans the FBI, IBM Watson Health, and EY, and she holds an MSc in Translational Medicine from the University of Edinburgh. Passionate about inspiring rising professionals, she believes that scientific and career breakthroughs alike are built where disciplines converge.
