Sponsors and contract research organizations (CROs) screen multi-therapeutic sites indication by indication.
November 7, 2026
7
min read
By
Julio G. Martinez-Clark, CEO, bioaccess®
I see this pattern from both sides of feasibility. As chief executive officer (CEO) of bioaccess®, a first-in-human (FIH) CRO running trials anywhere from Canada down to Argentina, I review site questionnaires for sponsors. As CEO of Amavita Research Services, a Miami cardiovascular research site operated for seven years with zero United States Food and Drug Administration (FDA) Form 483 findings, I complete those questionnaires as a site. A focused site and a multi-therapeutic site are judged by the same rule: proof is read per indication, never in aggregate.
Why site totals fail the first screen
A multi-therapeutic site often introduces itself with its largest numbers: total patients in its database, total studies completed, total years in operation. Each number can be accurate and still be useless to the person screening the site.
Feasibility is not a judgment about the site in general. It is a prediction about one protocol: will this site, in this indication, with this eligibility profile, screen and randomize enough participants, fast enough, with clean data? A database total mixes indications the protocol will never touch. A lifetime study count mixes phases, decades, and teams that may no longer be at the site. Years in operation say nothing about whether the clinic that treats this condition has research capacity this quarter.
Screeners know this, so they discount totals immediately and start hunting for the per-indication numbers underneath. If those numbers are not in the response, the screener has to ask, wait, and often move on to a site that supplied them. In a competitive shortlist, the delay alone can end the site's chances.
Enrollment proof, indication by indication
The core of a credible response is enrollment history in the protocol's indication, stated narrowly and recently. For that indication, a sponsor wants the number of patients the site screened and randomized in comparable studies, the time period, and the recruitment sources that produced those participants.
Break the answer down until it matches the protocol. If the study is in heart failure, a cardiology total is not enough: separate heart failure from hypertension, atrial fibrillation, and lipid studies. If the study is in a specific tumor type, separate that tumor type from general oncology. Then add the layer screeners check next: how many patients in the site's own records match the protocol's broad age, diagnosis, and prior-treatment profile today, before any advertising or outside referral is assumed.
Sources matter as much as counts. A site that can say its participants in an indication came from its own clinic population, named referral partners, and a documented database search is making a testable claim. A site that projects enrollment from population size in its city is making a hope. Sponsors have been disappointed by hopes often enough that they price them at zero.
At Amavita Research Services, our cardiovascular focus makes this discipline unavoidable. A documented population of more than 18,000 active cardiology patients only helps us when we can narrow it, indication by indication, to the patients a specific protocol can actually enroll, and show our screening history in that same indication. A multi-therapeutic site needs the same narrowing, repeated for every therapeutic area it wants to be considered for.
Startup timelines are per-indication too
Sites often quote one startup timeline as if it applied to every study. Screeners do not read it that way, because startup in one indication is not startup in another. The principal investigator (PI) differs, the departments whose approvals are needed differ, the equipment and laboratory arrangements differ, and the contract and budget reviewers may weigh a complex indication differently from a routine one.
A stronger answer gives recent, indication-specific startup history: for the last studies in the same or a closely related indication, how long from feasibility response to site selection, from selection to activation, and from activation to first participant screened. Where a step was slow, say why. A documented delay with a cause and a fix is more reassuring than a fast average with no detail behind it.
This history also exposes capacity honestly. If the indication's clinic is already running two competing studies, the startup answer should say so, name the competing studies, and explain how screening for the new protocol will be staffed. Competing studies in the same indication are one of the most common reasons a confident feasibility projection fails, and screeners ask about them directly. Answering before they ask is a credibility advantage.
Screen-failure and data experience in the indication
Per-indication proof extends past enrollment counts. Sponsors ask what the site learned in the indication: its screen-failure rate and the top reasons for failure, the protocol deviations it has seen, and how quickly it enters data and answers queries in that clinic's workflow.
These details cannot be borrowed from another therapeutic area. Eligibility pitfalls are indication-specific: a laboratory threshold, a prohibited medication common in that population, an imaging requirement the local workflow handles slowly. A site that names the top screen-failure reasons in the indication, and what it now checks at pre-screening to catch them early, demonstrates the kind of experience a study total never shows.
Training should be presented the same way. Current training in Good Clinical Practice (GCP) is a baseline for the whole team. What persuades a screener is indication-specific readiness: the named coordinator who will run the study day to day, the PI's clinical practice in that condition, and the backup coverage when either is away.
How a multi-therapeutic site should structure its response
The fix is presentational as much as operational. A multi-therapeutic site should maintain a one-page evidence sheet for each indication it actively seeks, and answer every questionnaire from the relevant sheet instead of from a general capability deck. Each sheet should carry:
- Enrollment history: Patients screened and randomized in the indication in the last three years, with comparable protocols named by phase.
- Eligible population today: A count drawn from the site's own records against the incoming protocol's broad eligibility profile, with the date and method of the count.
- Startup history: Recent timelines in the indication, from selection to activation to first participant screened, with delays explained.
- Screen-failure profile: The rate in the indication and the top failure reasons, plus the pre-screening checks now in place.
- Named team and capacity: The PI, the dedicated coordinator, and backups for the indication, plus competing studies in the same population.
- Recruitment sources: The clinic, referral, and database channels that produced participants in the indication before.
Six short sections, updated quarterly, answer nearly every question a screener will ask. They also force an honest internal decision: if a sheet is thin, the site does not yet have proof in that indication, and it is better to say so and propose how it would build the capability than to hide the gap inside a site total.
The shortlist rule
Multi-therapeutic breadth is not a disadvantage. It becomes one only when breadth is offered as a substitute for depth. Sponsors shortlist the site that proves, in the single indication in front of them, that it has enrolled before, started on a documented timeline before, and knows exactly where its next participants will come from.
That per-indication standard is the one we apply at bioaccess® when we build shortlists for sponsors, and it is the standard behind the conversations on Global Trial Accelerators, the podcast I founded, hosted by Jesús E. Moreno. Whether a site runs one therapeutic area or twelve, feasibility is won the same way: one indication, proved with numbers, at a time.
Julio G. Martinez-Clark is chief executive officer (CEO) of bioaccess\u00AE, a first-in-human contract research organization running early-phase trials anywhere from Canada down to Argentina, and of Amavita Research Services, a Miami cardiovascular research site he has operated for seven years with zero United States Food and Drug Administration (FDA) Form 483 inspection findings. He founded Global Trial Accelerators\u2122, a podcast for medtech and biotech founders navigating first-in-human studies.