Enrollment timelines. That's what wins and loses CRO contracts. Hekma gives you AI-matched patient populations, data-backed feasibility, and white-label CTMS β so you stop estimating and start guaranteeing.
75% of global clinical trials are run by CROs β and 85% still miss their enrollment targets. (Tufts CSDD / Thermo Fisher)
100% match confidence
080% match confidence
050% match confidence
0Time to first patient
0 days
3Γ
fewer screen failures with AI pre-screening
5 days
feasibility report turnaround from protocol receipt
60% β 20%
screen failure rate with Hekma-screened patients
Weeks
not months to deploy CTMS β white-label available
Patient recruitment is not your product β it is your constraint. You win bids by promising timelines, but every timeline depends on patients showing up at sites. When they do not, your contract is at risk. Your relationship with the sponsor is at risk. Your reputation is at risk.
The tools available to most CROs today β site-based outreach, investigator networks, social media ads β were built for a world where patients lived near trial sites, had time, and knew trials existed. That world is gone.
54%
decline in non-oncology Phase 3 enrollment rates 2012β2023
McKinsey, 2024
60%
average screen failure rate industry-wide
Tufts CSDD
$37K
average daily cost of a delayed trial to the sponsor
Tufts CSDD
THE HEKMA DIFFERENCE
AI matching against real EHR networks, PAG communities, and social media. Pre-screened, eligibility-scored patients delivered to your sites. This is not a list of names β it is a verified patient pool.
Protocol distribution, adverse event tracking, blinded study management, 21 CFR Part 11 audit trail, multi-site coordination. White-label it under your brand.
Point solutions solve one step. Hekma owns identification, matching, summarisation, execution, and engagement β in one platform with one data layer.
HOW IT WORKS
| Step | What Happens | Output |
|---|---|---|
| 1 β Upload Protocol | You provide the trial protocol or we pull it from ClinicalTrials.gov. Our AI parses all I/E criteria automatically. | Protocol loaded in < 1 hour |
| 2 β Map Patient Population | Hekma runs criteria against hospital EHRs, PAG communities, and H360 database. Returns tiered match report. | 100/80/50% confidence population report |
| 3 β Use It In Your Bid | Match report becomes your feasibility evidence. Your proposal goes in with real data, not estimates. | Data-backed proposal β differentiated bid |
| 4 β Patients Delivered To Sites | We run recruitment campaigns. Pre-screened candidates with eligibility scores arrive at your sites. | Coordinators enroll, not screen |
BEFORE / AFTER
| Without Hekma | With Hekma | Outcome |
|---|---|---|
| Social media ads β unqualified responses, 60% screen failure | EHR matching + AI summarisation β only likely-eligible patients surface | Screen failure: 60% β under 20% |
| Internal feasibility estimates β educated guesses | Real patient population counts against your specific I/E criteria | Data-backed bid β win rate improves |
| Veeva CTMS β $250K+ minimum, 6β12 month implementation | CTMS live in days β white-label, connect to recruitment layer | Trial running before competitors set up |
| SiteRx limited network for rare disease | H360 patient app + 50+ PAG rare disease communities | Find patients no site network can reach |
TARGET THERAPEUTIC AREAS
Heart failure, hypertension, AFib, atherosclerosis β large patient pools, high trial volume
Solid tumors, hematologic malignancies, immuno-oncology β deepest EHR network coverage
Alzheimer's, Parkinson's, MS, depression, rare neurological β complex I/E, Hekma specialises
Ultra-specific patient populations where traditional site outreach consistently fails
Patient Recruitment
5 simultaneous sourcing channels β EHR, H360, PAG, social, hospital
Feasibility Intelligence
Data-backed population reports in 5 days β not estimates
Trial Match (OpenSquare)
White-label the hospital patient network for your pharma clients
CTMS for CROs
Deploy in days. White-label. Connected to recruitment.
AI Summarisation
Review 1,000 records in the time it takes to review 10
Give us one trial protocol. We'll run it against our network and show you the patient population size, match confidence breakdown, and estimated time to first patient β before you commit to anything.