Cell and gene therapy has solved problems that seemed intractable a decade ago. The science of editing genomes, replacing defective genes, and engineering patient cells to fight disease has matured faster than most predictions. More than 3,900 cell and gene therapy products are now in development, according to analysis of the CGT clinical trial landscape. Yet programs continue to stall, timelines slip, and trials close before enrollment completes.
The bottleneck has shifted. Programs that reach Phase 2 have cleared the hardest scientific questions. What breaks them now is execution: the operational infrastructure required to identify eligible patients, confirm eligibility through molecular testing, and sustain data collection across years of follow-up. When these elements are built separately, programs fragment, and that fragmentation shows up as delayed enrollment, protocol amendments, and evidence that has to be reassembled retrospectively. That gap between proven science and operational delivery is the precision medicine execution deficit.
For rare disease programs, patient identification starts from a deficit. A 2024 EURORDIS Rare Barometer survey of more than 10,000 patients found that people living with a rare disease face an average diagnostic journey of nearly five years from symptom onset to confirmed diagnosis. The report behind this campaign puts the upper end of that range at up to six years. Either figure describes the same structural problem: patients exist, but they are not visible to the clinical development system until a diagnosis places them on the map.
That delay is not neutral time. The diagnostic odyssey drives inappropriate clinical management and missed treatment windows, and for genetically defined trials the molecular confirmation that actually qualifies a patient often lags behind the clinical diagnosis by additional months. The eligible population is smaller than it appears on paper and slower to reach than enrollment models assume.
Sponsors who recognize this early design diagnostics into their enrollment strategy rather than waiting for referrals to arrive. For example, Sarepta's Decode Duchenne program provides free genetic testing to patients with suspected Duchenne or Becker muscular dystrophy, removing cost and access barriers that delay molecular confirmation. Novartis leans on newborn screening for Zolgensma so that presymptomatic infants can be treated before symptoms and permanent damage set in. In both cases, testing becomes part of identification, which shortens the path from suspected case to confirmed enrollment instead of waiting for the diagnostic gap to close on its own.
Execution complexity extends well beyond enrollment. For certain cell and gene therapies, the FDA may mandate long-term follow-up of up to 15 years to monitor for delayed adverse events and assess durability of effect. For programs treating pediatric patients, that means tracking outcomes from childhood into adulthood.
This requirement creates a structural demand for sustained engagement and data continuity that most trial infrastructures are not built to support. Over a decade and a half, patients change providers, move geographies, and transition between insurers. Retaining patients across that period places significant burden on both sites and patients, and without infrastructure designed for longitudinal collection, sponsors face gaps in exactly the evidence regulators and payers rely on to judge long-term benefit and risk.
Programs that treat data architecture as a downstream operational task tend to discover this constraint too late. Designing patient engagement and data collection before protocols are locked is what allows the infrastructure for 15-year follow-up to exist from the first patient onward. Sano has written about how sustained engagement can become a reusable asset across a portfolio in why precision trials should not start from zero every time.
The third constraint is site readiness. Cell and gene therapy protocols demand more of sites than most trials: Advanced Therapy Medicinal Product (ATMP) studies can require more than 15 visits per patient, some visits often run longer than six hours each, and rare, genetically stratified studies frequently carry screen-failure rates above 75 percent. That is a heavy operational load, and it lands on teams that are already stretched.
Site capacity is not expanding to meet it. In its 2024 Clinical Research Site Challenges Report, a survey of more than 850 sites, WCG found that 38 percent of sites now name the growing complexity of clinical trials as their single biggest issue. Complex programs with narrow eligibility, specialized procedures, and long-term follow-up commitments are precisely the studies that ask the most of these teams.
The result is a compounding challenge. The same complexity that makes cell and gene therapy scientifically valuable makes it operationally demanding to deliver. Sponsors who reduce site burden through better technology integration, clearer study design, and centralized testing support find more willing and capable partners. At-home genetic testing, for example, can move eligibility confirmation off the critical path and reduce site burden while improving referral quality.
For sponsors developing cell and gene therapies, the question is no longer whether the science works. The question is whether the operational infrastructure exists to translate that science into durable evidence and patient access. That infrastructure spans patient identification systems that account for diagnostic delay and molecular eligibility, data architecture designed for decade-long follow-up, and site partnerships built on realistic assessments of capacity and burden.
The execution deficit is a choice rather than an inevitability. It reflects a decision to build these foundations in silos rather than as a coordinated system, and it is usually made by default rather than on purpose. Programs that integrate diagnostics, longitudinal data, and site readiness before protocol finalization position themselves to execute. Those that treat them as downstream details tend to stall.
Sano Genetics connects patient identification, genetic testing, and long-term engagement within a single platform, so the operational foundations a program depends on are designed to work together from the start.
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