Enrollment is fine, yet deviations rose and the interim slipped
Question
Our Phase III enrollment curve is tracking plan and the CRO status reads green. But screen failures jumped at a few sites, protocol deviations increased, data queries are piling up near cycle end, and the interim analysis date has slipped twice. Everyone says it’s “within tolerance,” yet the trial feels shaky. Why is this happening?
Answer ✅
Hitting the enrollment curve can hide trial-process instability. If inclusion/exclusion is applied unevenly, if data entry lags near visit windows, or if monitoring gets bunched, totals stay on plan while quality and cadence deteriorate. SSM-Audit adds a stability band beside the trial KPIs you already track, showing whether execution is calm and repeatable or fragile and delay-prone—before it risks the interim or database lock.
What the bands would have shown 📊
• Screen-failure stability sliding from A+ to A0 / A- at specific sites
• Protocol deviation rate degrading to A- / A– (visit windows, dosing, prohibited meds)
• Query cycle time worsening to A- (queries bunched near cutoffs)
• Data entry timeliness tilting A+ -> A0 (lag from visit to EDC entry)
• Monitoring visit adherence slipping to A- (RBM triggers not actioned on time)
• IP handling stability softening (A0 -> A-) (temperature excursions, reconciliation gaps)
• Dropout/withdrawal stability weakening in a few cohorts (A-)
What to do now 🛠️
- Band by site and cohort: screen failures, deviations, query cycle time, data-entry lag, monitoring adherence.
- Target retraining: focus on sites with A- / A– bands for inclusion/exclusion and visit windows; add job aids.
- Pull queries forward: mid-cycle mini-locks; enforce 72-hour EDC entry to stabilize query/entry bands.
- RBM discipline: escalate when monitoring adherence drops below A0; schedule catch-up visits now.
- Protect interim: freeze non-critical CRF changes; require A0+ bands across data-entry and queries before interim cut.
- IP logistics: tighten cold-chain checks at A- sites; pre-position spares and reconciliation audits.
How SSM-Audit helps (practicalities) 🌟
- No additional infrastructure: runs beside your EDC/CTMS exports and CRO dashboards.
- Numbers unchanged: enrollment and endpoints stay the same; stability is a read-only overlay.
- Easy to use: spreadsheet/BI friendly; one lightweight weekly panel at study and site level.
- Universal language: A++ / A+ / A0 / A- / A– aligns sponsor, CRO, sites, QA, and safety quickly.
CLI 💻 — try our mini Calculator to identify the drift
(Mini CLI Download Page)
Feed your trial CSVs and see bands and drift at a glance (numbers unchanged).
# Screen-failure stability (per site)
ssm_audit_mini_calc clinical.csv --kpi "Screen-Failure Rate" \
--out bands_screen.csv --plot_kpi "Screen-Failure Rate" --build_id hls
# Protocol deviation rate
ssm_audit_mini_calc clinical.csv --kpi "Protocol Deviation Rate" \
--out bands_deviation.csv --plot_kpi "Protocol Deviation Rate" --build_id hls
# Query cycle time (open -> close)
ssm_audit_mini_calc clinical.csv --kpi "Query Cycle Time" \
--out bands_query.csv --plot_kpi "Query Cycle Time" --build_id hls
# Data entry timeliness (visit -> EDC entry lag)
ssm_audit_mini_calc clinical.csv --kpi "Data Entry Timeliness" \
--out bands_entry.csv --plot_kpi "Data Entry Timeliness" --build_id hls
# Monitoring visit adherence (planned vs actual)
ssm_audit_mini_calc clinical.csv --kpi "Monitoring Adherence" \
--out bands_monitor.csv --plot_kpi "Monitoring Adherence" --build_id hls
# IP handling stability (temp excursions/reconciliation)
ssm_audit_mini_calc clinical.csv --kpi "IP Handling Stability" \
--out bands_ip.csv --plot_kpi "IP Handling Stability" --build_id hls
Outputs you will get:
- CSVs with stability bands for each timestamp (e.g.,
bands_query.csv). - Drift charts per KPI (
--plot_kpi) showing where trial cadence gets fragile. - Optional alerts if you enable thresholds in your setup.
Technical notes
Representation: x = (m, a) with a in (-1, +1)
Collapse parity: phi((m,a)) = m
Order-invariant pooling:
U = sum(w_i * atanh(a_i))
W = sum(w_i)
a_out = tanh( U / max(W, eps_w) )
Typical bands (example):
A++: a >= 0.75
A+: 0.50 - 0.75
A0: 0.25 - 0.50
A-: 0.10 - 0.25
A--: a < 0.10
Navigation
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Page disclaimer
Illustrative scenario for research and education. Observation-only; do not use for critical decisions without independent validation.
SHUNYAYA 