CLINICAL TRIAL RETENTION DEMONSTRATION

TrialForge Concept

A demonstration of how Forge Theory could be applied to predict patient dropout risk in clinical trials using engagement signal decay modeling. Illustrative example only.

Important Notice

This is a proof-of-concept demonstration for illustrative purposes. Actual clinical trial retention predictions require validated data, IRB-approved methodology, and clinical expertise. Not intended for medical decisions or trial management.

120
Patients Enrolled
84
Currently Active (70%)
18
High Risk of Dropout (15%)
18
Already Dropped Out (15%)

Example Patient Profile

Adjust these illustrative inputs to see how patient dropout risk changes. These are example values only.

Example: Protocol Factors
72% Protocol Adherence
Example: Taking study drug as prescribed
Example: Recording symptoms/diaries
Example: Demographic Factors
Medium Baseline Risk

Example Retention Interventions

Select example interventions to see their illustrative impact on retention decay.

Transportation Support
Provide taxi/ride-share credits for site visits to reduce travel burden.
Example Retention Boost
+15%
Example Cost
~$500/patient
Digital Engagement Platform
Mobile app with reminders, symptom tracking, and direct study team communication.
Example Retention Boost
+22%
Example Cost
~$300/patient
Care Coordination Support
Dedicated coordinator to help navigate trial requirements and address concerns.
Example Retention Boost
+18%
Example Cost
~$800/patient
Flexible Visit Scheduling
Evening/weekend appointments and virtual visit options when possible.
Example Retention Boost
+12%
Example Cost
~$200/patient
76%
Example 6-Month Retention Probability
Target: 85% Retention
Example Dropout Risk Level
Medium
15-30% risk
Example Site Average*
72%
+4% better
Example Industry Average*
68%
+8% better
Example Critical Threshold
60%
Above
Example Dropout Prediction
With current engagement levels, here's an illustrative prediction timeline:
6-8 weeks
Illustrative time to predicted dropout without intervention
+22%
Example retention improvement with selected interventions
~$45k
Example cost savings from avoiding dropout (per patient)*
*Based on published clinical trial cost estimates for illustration

Illustrative Engagement Decay Visualization

Disclaimer: This chart shows an illustrative example of how exponential decay modeling could be applied to patient engagement in clinical trials. Actual engagement trajectories would depend on disease area, protocol complexity, patient population, and numerous other factors.
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Illustrative Clinical Trial Value

Important: These figures represent example value estimates based on industry research on clinical trial retention. They demonstrate the potential financial impact of improved retention strategies.

~30-40%
Example dropout rates in Phase III trials*
(industry average)
$600k-8M
Example cost per patient dropout*
(depending on trial phase)
~$1M/day
Example cost of trial delay*
(for blockbuster drugs)
Clinical Context: Patient dropout is a major contributor to trial delays and failures. Predictive analytics could enable proactive retention strategies. This demonstrates the potential value that Forge Theory could deliver to clinical trial operations.

The Forge Theory Platform

Same mathematical framework applied across different domains. TrialForge represents the clinical trial application.

TrialForge
CarbonForge
EmissionsForge
DopeDecay
TyreForge
ToothForge
Universal decay modeling: engagement(t) = initial_engagement × e^(-k × t)