Study coordinators spend 60% of their time on tasks that should not require a human. We automate the entire patient qualification, scheduling, data entry, and reporting workflow — so coordinators focus on patients, overhead drops, and CROs select you more.
60%
of coordinator time spent on non-clinical admin tasks
Jeeva Trials / Tufts CSDD 2024
30%
administrative overhead added on top of every per-patient grant
ClinicalTrialPodcast.com
25%
increase in site burden since decentralized trial expansion
Tufts CSDD, SCOPE Summit 2024
$55K
average daily cost of a Phase III trial delay
IntuitionLabs / Tufts CSDD 2024
30%
surge in registered trials since 2020 — no proportional increase in coordinators
ClinicalTrials.gov / PMC 2024
The Full Automated System
From Patient Inquiry to CTMS Record With Zero Manual Steps
Every step of the patient intake and site operations workflow runs automatically. The coordinator receives a single notification when a pre-qualified patient is ready. That is the only touchpoint required.
Automated Workflow — Patient Intake to CTMS Write
📋
Patient Inquiry
Web / referral
→
Supabase Logs
Inquiry stored
→
Twilio SMS Fires
Instant outreach
→
Claude AI Qualifies
SMS conversation
→
GHL Books Appointment
Auto-confirmation
→
Sheets Updates
Enrollment tracker
→
Gemini Reports
Sponsor update
→
CTMS Write
Record logged
→
🔔
Coordinator Notified
One notification
What Each Tool Does
Supabase
Central database. Logs every inquiry, qualification result, appointment, and CTMS record. All data persists and is queryable for sponsor reporting.
Twilio
SMS delivery layer. Fires the initial patient outreach message within seconds of inquiry. Handles all two-way message routing throughout the qualification conversation.
Claude AI
Runs the qualification conversation over SMS. Asks inclusion and exclusion criteria questions, scores eligibility, handles patient questions, and triggers GHL when the patient qualifies.
What Happens After Qualification
GoHighLevel
Creates the patient contact, assigns them to the correct study workflow, books the screening appointment, and sends the confirmation SMS and email automatically.
Google Sheets
Live enrollment tracker updates automatically. Each new patient adds a row with qualification score, appointment time, and study assignment. Visible to the full site team in real time.
Gemini
Pulls enrollment data from Sheets and drafts the weekly sponsor status report automatically. Site director reviews and sends — no manual writing required.
AI Qualification via SMS
Claude AI Qualifies Patients Over SMS Before a Coordinator Sees Their Name
When a patient inquiry comes in, Twilio fires an SMS within seconds. Claude AI runs the full inclusion and exclusion criteria conversation automatically. Qualified patients get booked into GoHighLevel. Screen failures get a polite automated decline. The coordinator sees only qualified patients.
EC
Elite Clinical Network
Research Site · (702) 555-0198
Today 9:04 AM
✓ Patient Qualified — Appointment Booked
GHL created contact · Screening call: Tomorrow 2:00 PM · Confirmation sent
Step 1
Inquiry Received — SMS Fired Instantly
Patient submits a form or is referred by a physician. Supabase logs the record. Twilio fires the opening SMS within seconds — no coordinator involvement.
SupabaseTwilio
Step 2
Claude AI Runs Qualification Conversation
Claude asks inclusion and exclusion criteria questions over SMS. It handles follow-up questions, unclear answers, and patient hesitation naturally. The conversation reads like a human wrote it.
Claude AITwilio
Step 3
Qualified Patient → GHL Books Appointment
Once Claude confirms eligibility, GoHighLevel creates the contact, assigns the study workflow, and books the screening call. Confirmation SMS and email go out automatically. Coordinator notified.
Every Manual Task. What It Costs. What We Replace It With.
The 60% figure is not abstract. Here is exactly which tasks coordinators are doing manually, how many hours each costs per week, and what the automation replaces it with.
How Much Is Manual Operations Costing Your Site Right Now?
Adjust the inputs to match your site. The calculator shows what you are currently spending on admin tasks that should be automated — and what your site could handle instead.
Your Site Inputs
Study coordinators on staff3
Avg fully-loaded coordinator cost / year$95,000
Active concurrent studies5
Avg enrolled patients per study per month8
Based on 60% of coordinator time currently spent on automatable administrative tasks.
Your Site Output
Annual admin cost you are currently paying for
$171,000
Coordinator salary hours spent on tasks that should be automated
Admin hours freed per coordinator per week
28.4 hrs
Hours redirected to patient care, enrollment, and protocol execution
Additional study capacity unlocked
+3 studies
Studies your existing team can now support without new headcount
Sponsor and CRO Selection Metrics
CROs Score Your Site on 6 Metrics. Automation Improves Every Single One.
CROs are now using data-driven site performance metrics to determine which sites get selected for new studies. Sites with documented operational efficiency score higher and get offered more studies. Here is what that looks like in practice.
Metric CROs Score
Manual Site
Automated Site
Enrollment timeline adherence
How consistently the site hits enrollment milestones on schedule
67%
94%
Protocol deviation rate
Percentage of visits or procedures deviating from protocol
8.2%
1.8%
Query response time
Average days to resolve a data query from the CRO monitor
4.7 days
0.9 days
Data submission timeliness
Percentage of visit data entered within the required window
71%
97%
Screen failure documentation accuracy
How completely and accurately screen failures are recorded
62%
99%
Inspection readiness score
Regulatory file completeness and accessibility for FDA or GCP audits
Poor
Excellent
Overall CRO Attractiveness
Low priority
Passed over for new studies
Preferred partner
Offered studies first
Source: CROs now embrace data-driven site performance metrics to refine site selection. Protocol compliance, patient retention, and timely data submission consistently determine which sites get selected for repeat business and new studies. — SFCRI / CRO Selection Research 2024
Why This Matters to Sponsors and CROs
Sponsors Do Not Pick Sites. They Pick Machines That Enroll On Time.
Every sponsor running a Phase 2 or Phase 3 trial is operating under one constraint: time. A delayed trial is not just an inconvenience. It is a direct financial loss. Sponsors pay $55,716 per day for a Phase III trial. Every day a site underperforms on enrollment or compliance costs real money — and the sponsor knows exactly which sites are causing it.
⏱️
Enrollment Speed
86% of trials miss enrollment targets on time. A site that consistently hits milestones gets selected first for future studies and gets offered higher-value protocols. A slow site gets cut mid-trial or dropped from the next one.
📋
Protocol Compliance
Protocol deviations trigger FDA observations and force sponsors to spend money on corrective action. Sites with high deviation rates cost sponsors more per enrolled patient than sites with clean records. CROs track this and sites with poor compliance simply do not get offered new studies.
🗂️
Inspection Readiness
FDA audits happen without warning. A site with automated document management and a clean regulatory binder passes inspection quickly. A site with paper records and manual filing creates findings that can halt enrollment and jeopardize the entire trial submission.
The compound effect
A site that enrolls fast, maintains compliance, and is always inspection-ready does not just survive in the current trial. It gets offered the next study before competitors are even approached. Over time, high-performing sites command better per-patient rates, get access to higher-value therapeutic areas, and become preferred partners across multiple sponsors simultaneously. Automation is how you get there without burning out your team.
GCP Compliance Automation
Automated Compliance Is Not Optional. It Is What Keeps Your Site in Business.
Good Clinical Practice compliance is the regulatory baseline every clinical research site must maintain. Most sites manage it manually — paper binders, coordinator checklists, last-minute document scrambles before a monitor visit. We automate the entire compliance documentation layer.
Manual Compliance — What Goes Wrong
❌
Expired delegation logs — coordinator delegations not updated when staff changes, caught in monitor visit, site gets a finding
Unsigned consent forms — patient enrolled without fully executed ICF, requires protocol deviation report and may require patient withdrawal
❌
Late data entry — visit data entered 12 days after the visit, CRO queries pile up, coordinator spends 3 hours resolving what should have been automatic
Automated Compliance — What We Build
✓
Delegation log auto-alerts — GHL triggers a task and SMS to the PI when any staff credential expires or a role changes. Binder stays current automatically.
✓
AE intake via SMS + Twilio — patient reports a symptom by text, Claude AI captures the structured AE data and timestamps it. Auto-filed in Supabase within minutes of the event.
✓
eConsent workflow in GHL — consent form sent, signed, and timestamped before the patient is enrolled. No coordinator can advance a patient without a completed ICF on record.
✓
Visit data auto-push to Sheets — post-visit data entered via a structured GHL form and pushed to Google Sheets and Supabase same day. CRO query rate drops to near zero.
GCP compliance is not a checklist. It is a live operational state. Automation keeps it that way without coordinator effort.
ICH E6(R3) alignedFDA 21 CFR Part 11 ready
Live Operations Dashboard
What Your Site Looks Like to a CRO Monitor After Automation
This is a simulated view of a clinical research site running full AI operations automation. Every data point is automatically updated. No coordinator manually entered any of this.
Elite Clinical Network — Site Operations Dashboard
Concomitant medication update — Patient: RA-0027 · RA Phase 3 Study
Coordinator Review
Sponsor Reports — Auto-Generated by Gemini
Weekly Enrollment Update — GLP-1 Obesity Study
Auto-generated · Ready to send
Monthly Safety Summary — RA Phase 3
Auto-generated · Ready to send
Screen Failure Log — T2D CVOT · Week 18
Auto-generated · Ready to send
From Our Founder
"Clinical research sites are bleeding margin on tasks that a well-built automation system handles in milliseconds. Every hour a coordinator spends chasing a document or drafting a status email is an hour not spent on the work that actually moves a trial forward. When we build these systems for a site, two things happen immediately: overhead drops and CRO selection rates climb. Those are not separate outcomes. They are the same outcome — a site that runs like a machine attracts the studies that pay like one."
Josh Leavitt
Founder, Omni Online Strategies
Ready to Automate Your Site Operations
Cut Overhead. Win More Studies. Run a Leaner Site.
We build and manage the full AI operations automation stack for your clinical research site or SMO network. Patient qualification via SMS, appointment booking, data tracking, and sponsor reporting — all automated. First workflow live in under 2 weeks.
This is an interactive demonstration only. All company names, patient data, study names, dashboard figures, and performance metrics shown are fictional and for illustrative purposes only. No numbers presented in this demo constitute a promise, guarantee, or projection of results. Actual savings, efficiency gains, and CRO selection outcomes depend on site size, therapeutic area, protocol complexity, existing infrastructure, and operational maturity. Statistics cited are sourced from Jeeva Trials, Tufts Center for the Study of Drug Development (CSDD), ClinicalTrialPodcast.com, IntuitionLabs, ClinicalTrials.gov, and PMC 2024. Omni Online Strategies builds and delivers automation infrastructure — operational outcomes depend on the site's implementation, team adoption, and clinical operations.
About This System
AI-Powered Clinical Trial Site Operations — Automating Coordinator Workflows
This system automates the recurring operational workflows that consume clinical trial coordinators' time — patient scheduling, protocol deviation logging, adverse event flagging, regulatory document tracking, and sponsor communication — by connecting the site's CTMS to a workflow automation layer that handles routine tasks automatically and surfaces exceptions requiring coordinator attention. Built for clinical research sites, SMOs, and academic medical centers running 3 or more concurrent studies whose coordinators spend 40 to 60% of their time on administrative tasks that do not require their clinical expertise.
System Facts
Category
Detail
Manual Process Replaced
Coordinators manually scheduling patient visits, sending reminders, logging protocol deviations, tracking regulatory document expiration dates, and drafting sponsor communication from scratch
Trigger
Patient visit completion logged in CTMS, document expiration date approaching, protocol deviation identified, or scheduled workflow trigger at configured intervals
What the System Does
Automates patient visit scheduling and reminders, flags protocol deviations for logging, tracks regulatory document expiration and renewal, drafts sponsor communication from CTMS data, and generates visit completion reports
Who Uses It
Clinical trial coordinators, site managers, principal investigators, regulatory affairs staff at clinical research sites, SMOs, and academic medical centers
Integrations
RealTime eClinical, CRIO, Veeva SiteVault, or other CTMS (via API or data export); GoHighLevel or Saleshandy (patient and sponsor communication); n8n (workflow automation); Google Sheets (reporting)
Output
Automated visit reminders, deviation logs, regulatory tracking alerts, sponsor status emails, and visit completion reports — all generated without coordinator manual effort
Time Saved
Sites running 5 or more concurrent studies typically recover 15 to 20 coordinator hours per week from administrative task automation — reducing burnout and enabling coordinator capacity expansion without hiring
Regulatory Context
FDA 21 CFR Part 312 and ICH GCP E6(R2) require meticulous documentation of protocol deviations, adverse events, and regulatory document currency — a documentation burden that automated logging reduces while improving accuracy
Tasks that follow clear rules and do not require clinical judgment are the primary candidates: patient visit scheduling (calculating next visit window based on protocol schedule and last visit date), visit reminders (sending reminder communications to patients at configured intervals before visits), protocol deviation logging (flagging visits that occurred outside the protocol window and pre-populating the deviation log), regulatory document tracking (monitoring expiration dates for IRB approvals, GCP certifications, lab certifications, and investigator CVs), sponsor status emails (generating weekly or monthly status reports from CTMS data), and invoice generation from visit completion records.
The system integrates with RealTime eClinical via the RealTime API, CRIO via webhook and export, Veeva SiteVault via the Vault REST API, and Clinical Conductor via data export. For CTMS platforms without public APIs, the system uses scheduled data exports (CSV or Excel) triggered by n8n to pull current patient and visit data. All extracted data is written back to the CTMS via API where supported, or logged to a parallel tracking system (Google Sheets, Supabase) where it is not.
A protocol deviation occurs when a study procedure does not occur as specified in the protocol — a patient's visit window is missed, a blood draw is not collected at the required time, or a prohibited medication is not caught in the screening process. These deviations must be documented, classified by severity, and reported to the IRB and/or sponsor. Automated flagging monitors the CTMS for visits that occurred outside the protocol window or required procedures that were not recorded as completed, and pre-populates the deviation log template for coordinator review and submission — reducing the time to log each deviation from 30 to 45 minutes to 5 to 10 minutes of coordinator review.
The system maintains a tracking database of all time-sensitive regulatory documents at the site — IRB approval letters (with annual continuing review deadlines), GCP certification records for all study staff (typically 2 or 3 year cycles), laboratory certification documents (CLIA, CAP), investigator CVs and medical licenses, and protocol-specific training logs. Expiration dates are monitored and escalating alerts fire at 90 days, 60 days, and 30 days before expiration — giving the regulatory coordinator enough lead time to initiate renewal without creating a last-minute compliance risk.
Automated patient communications include: visit reminder messages (configurable timing — 7 days, 3 days, and 1 day before scheduled visit), visit confirmation messages after scheduling, screening appointment reminders, missing visit follow-up messages (configured to fire when a patient misses a scheduled visit without cancellation), and end-of-study thank-you communications. All patient communications are reviewed and approved by the site's IRB as part of the study protocol — the automation sends pre-approved messages, not AI-generated content, to patients.
Many sponsors require weekly or biweekly status updates from sites — enrollment counts, screen failures, active patient count, upcoming visit schedule, and protocol deviation summary. These reports previously required coordinators to manually pull data from the CTMS, compile into a report template, and email the sponsor. The automation pulls current data from the CTMS on a configured schedule, populates the sponsor's required report template, and sends or queues the report for coordinator review and send — reducing each report from 30 to 60 minutes of coordinator time to 5 minutes of review.
No. The automation system is a layer that connects to the existing CTMS via API or data export — it does not replace the CTMS. All patient data, visit records, and regulatory documents remain in the CTMS as the system of record. The automation reads from the CTMS, triggers external workflows (scheduling, communication, alerts), and writes back to the CTMS where supported. Sites keep all existing CTMS functionality and add automation on top of it.
How It Works
STEP 01
CTMS connected via API or data export
The site's CTMS is connected to n8n via API (RealTime, CRIO, Veeva) or scheduled data export. Patient, visit, and regulatory document data begins syncing.
STEP 02
Protocol visit windows configured per study
Each active study's protocol visit windows (acceptable date range for each visit) are configured in the system to enable deviation flagging.
STEP 03
Automated visit reminder workflows activated
n8n workflows configured to send patient reminders at defined intervals before each scheduled visit, using the site's pre-approved communication templates.
STEP 04
Protocol deviation monitoring enabled
Daily scan of CTMS visit records checks each visit against the configured protocol window. Out-of-window visits flagged and deviation log templates pre-populated.
STEP 05
Regulatory document tracking database built
All site regulatory documents catalogued with expiration dates. Escalating alert schedule configured — 90/60/30 day alerts to the regulatory coordinator.
STEP 06
Sponsor report automation configured
Sponsor-required report template configured with CTMS data field mappings. Automated report generation scheduled and queued for coordinator review before sending.
