The Hidden Mathematics of Clinical Trials

What 1,000 patient records reveal about the delicate art of trial enrollment

A DATA STORY ABOUT THE GLUCOFIX PHASE 3 TRIAL

Consider patient P0003. A 53-year-old from Maharashtra, diagnosed with Type 2 diabetes eight years ago. BMI: 29.2. HbA1c: 9.0%. On stable metformin for fourteen months. No recent cardiovascular events. No insulin. No SGLT2 inhibitors. Perfect.

Or rather, almost perfect. The one missing piece? Blood pressure measurements. A simple oversight that transforms P0003 from the #1 enrollment candidate into someone who needs one more clinic visit before randomization.

This is the fundamental tension at the heart of clinical trial recruitment: the gap between theoretical eligibility and practical enrollment.

0
Eligibility Rate

The Funnel

Out of 1,000 patients screened from the database, exactly 333 met all inclusion criteria for the Glucofix Phase 3 trial. But that number—stark as it is—conceals a more complex narrative about the architecture of modern drug development.

Total Patients Screened
1,000 patients
Have T2DM Diagnosis
873 patients
On Metformin Therapy
718 patients
Appropriate HbA1c Range
595 patients
No Major Exclusions
452 patients
Meet All Criteria
333 patients

Five Barriers to Enrollment

155
patients excluded
The Metformin Paradox
No metformin prescription found. A trial testing a drug in addition to metformin can only enroll patients who've successfully stayed on metformin for months.
127
patients excluded
The Diagnosis Gap
No Type 2 diabetes diagnosis documented. Trial eligibility isn't just about biology—it's about documentation.
75
patients excluded
The Cardiovascular Shadow
Recent major cardiovascular events. These are precisely the patients who might benefit most, yet proving it is too complex for Phase 3.
63
patients excluded
The Type 1 Mimics
Type 1 diabetes diagnosis found. The protocol can't risk the complexity of fundamentally different biology.
55
patients excluded
The Missing Tests
No renal function tests found. Data gaps are indistinguishable from exclusion criteria failures.
35
patients excluded
The Medication Minefield
Using newer diabetes drugs (SGLT2i, GLP-1). Often receiving the best current care, yet disqualified for having too many confounding variables.
"Clinical trials study simplified patients to draw clean conclusions. The 333 eligible patients represent perhaps 10-15% of the actual diabetes population."

Patient Flow: From Database to Trial

1,000
Patients Screened
→
333
Eligible
→
~200
Expected Enrolled
667
Ineligible Patients

The Critical Insight

Trial eligibility isn't random. It's the deliberate architecture of modern pharmaceutical research. The protocol needs homogeneity to detect signals, simplicity to draw conclusions, and selection to ensure safety. But it means the eventual results will come with an invisible asterisk: effective in patients who meet these precise criteria.

The Perfect Candidates

The top-ranked candidates share a compelling profile: ages 45-60, HbA1c perfectly positioned at 8.5-9.5%, excellent kidney function, on stable metformin monotherapy, and no recent complications. Here are the top 6:

RANK #1
Patient P0003
Age 53 years
HbA1c 9.0%
BMI 29.2
eGFR 103.1
RANK #2
Patient P0894
Age 52 years
HbA1c 9.5%
BMI 27.2
eGFR 83.0
RANK #3
Patient P0825
Age 43 years
HbA1c 9.4%
BMI 25.3
eGFR 103.1
RANK #4
Patient P0828
Age 41 years
HbA1c 9.3%
BMI 31.2
eGFR 98.0
RANK #5
Patient P0830
Age 57 years
HbA1c 8.9%
BMI 28.8
eGFR 85.7
RANK #6
Patient P0228
Age 48 years
HbA1c 8.5%
BMI 26.8
eGFR 97.8

Eligibility Rate Visualization

Only one-third of screened patients qualify for enrollment—a reflection of the stringent requirements necessary for rigorous clinical science.

333 / 1,000 Eligible (33.3%)

The Bottom Line

Clinical trial recruitment is not a simple search for sick patients. It's an elaborate filtering process that balances scientific rigor with practical realities. The Glucofix data reveals this architecture clearly: 333 eligible patients from 1,000 screened, representing a highly selected subset optimized for homogeneity, safety, and statistical power.

These patients aren't the sickest. They're not the healthiest. They're not the most representative.

They're the most enrollable.