Straight answers on site selection, feasibility, bid defense, real patient data, privacy and how working with us actually goes. If yours is not here, ask us and we will answer it directly.
Who we are and how the work gets delivered.
We help clinical trial teams pick the sites and investigators that will actually enroll a study. Every recommendation is built on real, patient-level data rather than inferred estimates, and delivered as a finished answer for your protocol by a forward-deployed team, not another dashboard to run yourself.
Two things. The data: most tools infer feasibility from partial or public data everyone already has. We count from the real patient record, national and longitudinal. The approach: most tools tell you either where the patients are or who has the best track record. We weigh both, because a site full of patients that cannot enroll, or a great investigator with no patients, is only half the picture. Then we deliver it forward-deployed: ranked sites and investigators for your protocol, not a dashboard you are left to run alone. How AI site selection works →
A forward-deployed solution: an expert team plus AI that produces the ranked sites and investigators you need for feasibility and bid defense. Most partners want the finished answer delivered to them, and a self-serve option is available as you scale. A solution, not a subscription you are left to operate.
Days, not a feasibility cycle. Send us the protocol and we come back with the qualifying patient count, the sites that can reach those patients, and the reasoning behind each rank. Send us a protocol →
How the site selection and feasibility work gets done.
It is using AI over real evidence to score and rank sites and investigators for a given protocol, on both their proven trial track record and the qualifying-patient evidence for the indication, so you select the sites most likely to actually enroll instead of guessing from partial data. AI site selection →
On two things that most approaches treat separately: a proven track record, and real patient-level evidence that the right patients are actually there. Track record tells you who can run your trial; patient access tells you who actually has the patients. You need both, on the same investigator. We rank on the combination, and every rank comes with its reasoning rather than a broker’s list.
We use both, but the difference is what sits underneath. Public and open datasets are the floor everyone in the category builds on. What sits under ours is different: real, patient-level evidence and our own curated site intelligence. That is the difference between knowing and inferring. Real patient data →
No. Traditional feasibility leans on questionnaires, with sites self-reporting their own capacity, which is exactly what produces the over-optimistic picks that then under-enroll. We start from real evidence, so the ranking reflects what is actually there, not what a site hopes to deliver.
Feasibility asks whether and where a trial can enroll. Site selection turns that into the ranked list you will actually use. The same real evidence base underpins both, which is why they should not run on different data. Clinical trial feasibility →
We work across therapeutic areas. We are not boxed into a handful of indications the way tools built on a single hospital network tend to be. Rare and orphan disease is a particular strength, because that is exactly where inference from public data falls apart.
Yes, it is a strength. When patients are few and scattered, inference from public data breaks down. Working from real, patient-level evidence is how you find the sites and investigators that can actually enroll a rare-disease study. Rare disease site selection →
Yes. In a recent rare-disease program we measured what each eligibility criterion cost in qualifying patients and showed the sponsor where the protocol could safely open up. The final protocol qualified nearly three times the patients of the initial draft, with the same scientific intent. Read the case study →
Yes, and our country-level coverage is expanding. For global programs we weigh what actually decides a country’s fit for your study, including cost, the regulatory path where you intend to seek approval, and whether the disease is really there, rather than one country’s data alone.
What you walk into the room with.
A bid defense is the meeting where a CRO presents and defends its proposal to a sponsor, above all the sites and investigators it will use to enroll the trial. It is where the contract is won or lost, and it usually turns on one question: can these sites actually enroll this study? How to win a bid defense →
Yes. For an RFP you get a fast feasibility read on your proposal. For the bid defense itself you get the full answer: every proposed site and investigator with qualifying patient counts, a measured track record and the reasoning behind its rank. A faster, more defensible answer than an inferred estimate.
A ranked, defensible site list, one page per site: the site and principal investigator with contact information and startup readiness; the qualifying patient counts at the facility and under the investigator’s direct care; a measured enrollment track record for each investigator; a composite score that ranks the list, with the reasoning behind each rank; whether the site is a recognized center of excellence for the indication; and why each site made the list and why some marquee names did not. The deliverable →
Built to clear a security and legal review, not just the sales call.
Our analysis runs on real, patient-level real-world evidence: national, longitudinal data sourced through a premier data partner and assembled specifically for clinical-trial feasibility. That is what lets us follow the right patients to the right sites. Every ranking traces back to that evidence, not to a public dataset everyone already shares.
The de-identified record of what actually happened to real patients, across every institution that treated them, over time. In site selection it means the counted number of protocol-qualifying patients an investigator can reach, not a therapeutic-area estimate or a registry sample. Why real beats inferred →
Your protocol and study details stay yours. Every analysis is scoped to your engagement, runs on our own sourced evidence, and is never pooled with another client’s work. The signals and methods behind our scores stay confidential as well.
We show you the reasoning behind every rank: the qualifying patient counts, the investigator’s track record, and why a site made the list or was cut. That is what you defend in the room. The model itself, the signals it weighs and how it weighs them stay ours, the same way your protocol stays yours. Explainable, or it is useless →
No. We do not hold your enrollment data, so it cannot be used to train anyone else’s model. Your edge stays yours.
CROs, biotech and sponsors, and where an audit fits.
Yes, CROs are our core partner. We embed with your feasibility and business-development teams to deliver ranked sites and investigators for RFPs and bid defense. What we do for CROs →
Yes. Sponsors use us to pressure-test where a trial will actually enroll before committing budget and timeline. What we do for biotech →
Yes. Even teams with their own data use us as a low-cost audit: a fast, independent second set of eyes on a feasibility read before a go or no-go. It is a light lift to run and an easy way to de-risk a big decision. Ask about an audit →
What a wrong site actually costs, with sources.
A site that never enrolls still costs its activation fee, months of a flat enrollment curve, a rescue site bolted on late, often a protocol amendment at a median direct cost of $141K to $535K, and a timeline slip that pushes the whole program. One miss runs to hundreds of thousands of dollars and months of delay. The full cost of guessing →
Tufts CSDD analysis of roughly 16,000 sites across 151 Phase II and III trials found about 37% under-enroll and about 11% never enroll a single patient. Nearly half of activated sites fall short of what was promised at feasibility. Sources →
Plain-English answers to the questions people search most.
Clinical trial feasibility is the assessment of whether a planned study can realistically enroll enough of the right patients, at the right sites, within the timeline. It weighs the eligible patient population, site and investigator capability, competing trials and operational risk before a sponsor commits. Done on real patient-level data rather than estimates, it is the difference between a plan that enrolls and one that stalls. Clinical trial feasibility →
Site selection criteria are the factors used to decide which research sites and investigators to activate: typically the eligible patient population for the protocol, the investigator’s track record in the indication, site capacity and staffing, regulatory and quality history, and competing trials for the same patients. We score sites on real evidence of both proven track record and real qualifying-patient access, then rank them.
Real-world data is health data generated outside a controlled trial, from routine clinical care, claims and registries. In feasibility and site selection, real, patient-level RWD shows which investigators treat the right patients, instead of inferring from partial or public datasets. It is the evidence base our rankings are built on. Real patient data →
How a partnership begins.
The fastest path is a short conversation about a live protocol or RFP. From there we can run a lightweight feasibility read so you see the output on your own work before committing to anything. Talk to us →
A program for a small number of CROs and sponsors who run feasibility at scale: your own enrollment engine, built inside your own cloud. Details are coming soon in the Newsroom. If you want an early conversation, get in touch. The Newsroom →
No question matches that yet. Ask us directly →
The fastest answer is a short conversation about a study you are actually working on. Bring the protocol or the RFP and we will show you the qualifying patients and the sites that can reach them.