Oncology has never been in a better scientific position. Precision medicines, adaptive study designs, and biomarker-driven cohorts have opened up treatment possibilities that simply did not exist ten years ago. But the complexity of running these trials has grown at much the same pace as the science itself, and that gap between scientific ambition and operational capability is where many programmes quietly struggle.
For sponsors building oncology portfolios, and for the CROs executing them, the operational challenge is no longer a peripheral concern. Getting it right comes down to three things: being consistent enough to build efficiently, agile enough to adapt when the science changes, and scalable enough to manage a growing portfolio without the overhead growing at the same rate.
Medable has worked with sponsors and CROs across many global oncology programmes, spanning thousands of sites and participants. That experience has given us a clear picture of what separates programmes that move well from those that get stuck.
Oncology trials have changed. Trial operations have not kept up.
Oncology is genuinely unlike any other area of drug development. Treatment decisions are shaped by genetic profiling, tumour mutation status, disease stage, and what a patient has already tried. A single patient might start on one combination, develop resistance, and move to a completely different regimen within the same programme. And increasingly, the goal is not to eradicate cancer but to manage it: to help patients live with it across years of treatment rather than reaching a single curative endpoint.
That reality has significant implications for how sponsors need to think about their pipelines. A single compound is not a portfolio strategy in oncology. You need multiple assets targeting different mutation profiles, different indications, different lines of therapy. One compound may work for solid tumours. Another may address a mutation that shows up in both breast and prostate cancer. Each needs to be tested across combinations, across disease stages, across patient populations. The complexity builds fast.
And yet most trial operations were not built for this. Studies are still designed as standalone efforts, with each one essentially starting from scratch. Sites working with the same sponsor across multiple programmes regularly encounter different workflows, different data structures, different expectations. Teams spend time rebuilding instruments and processes that already exist somewhere else in the organisation. Across a single study that is manageable. Across a portfolio it becomes a structural problem.
The numbers make this concrete. Oncology trials run 30 to 40 per cent longer than trials in other therapeutic areas. More than 91 per cent of oncology protocols go through at least one substantial amendment, and the average is closer to four. Each amendment carries a median direct cost running into the hundreds of thousands of dollars. Infrastructure that cannot absorb that level of change without significant disruption is not a minor inconvenience; it is a meaningful drag on both programme cost and timeline.
Sources: Tufts CSDD 2016, Tufts CSDD 2021, Tufts CSDD 2024
Consistency is the efficiency unlock
Standardisation gets a bad name in oncology because it sounds like it means making everything the same. It does not. What it actually means is building a reusable foundation, one that study teams configure for each protocol rather than rebuild from scratch every time. In our experience across oncology programmes, reaching around 70 per cent standardisation within a programme delivers a genuine step change in how efficiently teams can work.
Sites notice it most. When they recognise the structure of a programme across multiple studies, training becomes much less burdensome. Study teams work from validated frameworks rather than building from nothing. And patients move through more consistent, intuitive journeys even as the compounds and indications change around them.
Take patient-reported outcome instruments. A sponsor running across multiple oncology indications will use variations of the same instruments throughout their programme. The questions relevant to a breast cancer study are not identical to those for prostate cancer, but the underlying instrument often is. When that instrument is already built, validated, and available in a library, the work becomes selection and configuration rather than construction. That difference, repeated across every study in a portfolio, adds up considerably.
There is also a longer-term benefit that is easy to overlook. When data structures are consistent across a programme, the portfolio itself becomes analytically richer. Cross-study analysis becomes possible in ways it simply is not when each study has been designed independently.
Scale becomes a competitive advantage, not a burden
Oncology success, for most sponsors, is portfolio driven. You are not developing one drug; you are building a pipeline across tumour types, genetic profiles, lines of therapy, and combination regimens simultaneously. Without a foundation that scales, every new asset added to the portfolio brings overhead rather than momentum.
CROs face a version of the same problem. Building eCOA capabilities on a study-by-study basis creates a cost and resourcing model that gets harder to sustain as programme volume grows. The goal is to reach a point where adding studies to a programme does not mean proportionally adding headcount and overhead to support them.
The ambition for leading sponsors is a connected programme: a body of studies that share structure and data architecture and build on each other over time, rather than a collection of independently designed trials that each start fresh. The operational infrastructure needs to support that ambition, not work against it.
Medable works with many of the world’s leading pharma sponsors and CROs across their oncology programmes. The depth of those relationships reflects something straightforward: there is a meaningful difference between working with a platform built for oncology at scale and working with one that is being adapted for it.
Agility is what makes it all work in practice
Consistency and scale matter, but they are not enough on their own. Oncology trials change, often substantially, and the infrastructure running them needs to change with them.
Phase I oncology studies are a good illustration of what that looks like in practice. A study might start with six patients at an initial dose, evaluate tolerance, then expand to ten at the next level, then fifteen, before branching into separate cohorts for different indications: breast cancer, head and neck, and gastric. Each gate review opens a new cohort that needs to be activated, monitored, and eventually closed without disrupting everything else running in parallel.
Managing that kind of dynamic study on traditional systems means repeated change orders, manual reconfiguration, and delays at every decision point. It is not a coincidence that oncology has been slower than other therapeutic areas to move away from paper and fragmented legacy platforms. The pace of change in an adaptive oncology study is genuinely difficult for systems not designed to handle it.
Medable’s platform is built around this reality. A cohort built once can be cloned for the next. New cohorts can be activated as needed without reconfiguring the study from scratch. When patients take treatment breaks (which in oncology happens often, as patients manage toxicity), schedules automatically rebaseline from the restart date rather than requiring manual intervention. Assessments can be configured so that pre-visit and post-visit data capture reflects how clinics actually work, rather than fitting into artificial visit structures.
None of this is cosmetic. These are the capabilities that make running an adaptive oncology study on a digital platform genuinely viable, rather than a workaround that generates as many problems as it solves.
Supporting patients through the full journey
Oncology patients are a specific population, and the demands placed on trial platforms reflect that. Treatment weeks can be brutal: a patient may simply not be able to complete assessments during a particularly difficult period. They may need a caregiver, family member, or nurse to step in on their behalf for a time. And unlike many therapeutic areas, these patients may be enrolled for years, continuing in long-term follow-up well after active treatment has ended.
Regulators have increasingly pointed to electronic consent as particularly important in oncology, precisely because these study designs are so complex. Medable supports this through consent tools that give patients and their families a clear, visual explanation of what participation involves. Resource centres provide educational support throughout the study rather than only at enrolment. Caregiver delegation allows a trusted person to step in for a defined period, with proper auditable authority, and hand back when the patient is ready.
These are not edge-case features. In oncology, they are part of what makes it possible to run a study properly across a treatment journey that may span years.
Looking beyond the individual trial
As oncology moves further towards a chronic disease model, the limitations of a trial-by-trial approach become more apparent. Patients cycling through multiple therapies over many years generate insights that are only visible if the data architecture connects across studies and over time. A series of independently designed trials cannot deliver that; the longitudinal picture simply does not exist.
Sponsors who build their programmes with this in mind, treating the portfolio as a connected data asset rather than a sequence of separate studies, will be better placed to generate the kind of cross-programme insights that inform the next round of development decisions.
The future belongs to those who can execute
The science in oncology is moving fast. The sponsors and CROs who lead the next decade will be those who have built the operational infrastructure to keep up: moving quickly, adapting as protocols evolve, and managing complex portfolios without the overhead consuming the gains. Breakthroughs still need to be executed, and execution is an operational challenge just as much as a scientific one.
Medable is built to support that execution, through a validated instrument library, adaptive cohort management, and a portfolio model designed to get more efficient over time, not less.
To speak with Medable’s oncology team about your programme, visit medable.com or contact your Medable account partner.
All statistics and case study data referenced in this document are drawn from Medable programme data and publicly available industry research. Tufts CSDD data cited: 2016, 2021, 2024.
