HEALTHTECH — CLINICAL TRIALS & PHARMA

AI-accelerated clinical trials

Trial recruitment: 18 months → AI-enhanced: 6-9 months. Automate patient matching, accelerate enrollment, and improve data quality with AI built in weeks.

18 → 6-9

Months recruitment timeline

$2.4B

AI recruitment market by 2030

93%

NLP patient matching accuracy

Performance benchmarks

Where does your trial operation sit? Compare across four critical metrics.

Metric	Industry Average	Top Quartile	AI-Transformed
Recruitment Timeline	12-18 months	9-12 months	6-9 months
Screening Volume	100-200/mo (manual)	500-1,000/mo	2,000-5,000/mo
Enrollment Rate	40-50%	55-60%	65-75%
Data Quality (Clean at Source)	70-80%	85-90%	95%+

Sources: Industry benchmarks 2024. AI recruitment market: $641.6M (2024) → $2.4B (2030) at 24.8% CAGR. Pharma AI market: $1.94B (2025) → $16.49B (2034).

What global leaders are doing

Industry examples from publicly reported initiatives — not Xamun projects. Included to illustrate what AI transformation looks like in this sector.

The world's top pharma and research organizations are deploying AI across the trial lifecycle.

Pfizer

AI-Driven Clinical Development

✓ NLP for patient population identification
✓ Saama partnership: Smart Data Quality platform
✓ AI-powered trial feasibility assessment

GSK

AI Biomarker Discovery

✓ 30% improvement in treatment response via AI stratification
✓ $45M Relation AI partnership (fibrotic diseases)
✓ Proteomic/genomic data for patient cohorts

Mass General / RECTIFIER

RAG-Powered Trial Matching

✓ Enrollment rates ~2x higher than manual screening
✓ AIWithCare spinout company (2024)
✓ Scalable multi-health-system deployment

NIH / TrialMatchAI

End-to-End Patient Matching

✓ TrialGPT: identifies trials + explains eligibility
✓ Processes structured + unstructured clinical data
✓ Automates enrollment identification

The transformation opportunity

What changes when a mid-market CRO or pharma company deploys AI across trials.

⚠ Before — Mid-Market Baseline

✗ Recruitment timeline: 12-18 months
✗ Patient ID: manual chart review, referral-based
✗ Screening: 100-200 manual screens/month
✗ Enrollment success: 40-50% of screened
✗ Eligibility assessment: labor-intensive, error-prone
✗ Diversity: limited to referral pathways

✔ After — AI-Enhanced Trials

✓ Recruitment timeline: 6-9 months
✓ Patient ID: automated EHR mining + AI matching
✓ Screening: 2,000-5,000 automated/month
✓ Enrollment success: 65-75% of screened
✓ Eligibility: automated with human review
✓ Diversity: 30-40% improvement in representation

20-30% reduction in operational costs within 12 months

How Xamun delivers this

From diagnostic to deployed system in weeks — not months.

1. XI Identifies

Trial Operations Gaps

Xamun Intelligence benchmarks your recruitment timelines, screening throughput, enrollment rates, and data quality against AI-enhanced leaders. Identifies highest-ROI automation targets.

2. Software Factory Builds

AI Trial Systems

Patient matching AI with 93%+ accuracy, automated EHR screening, trial feasibility engines, real-time data validation, and diversity analytics — scoped and built in weeks.

3. Measurable Outcomes

3-12 Month Timeline

50-100% faster recruitment. 2-3x screening volume. 25-35% enrollment improvement in 6 months. 40-50% data quality improvement in 3 months.

See XI run a diagnostic on your clinical trials

Book a discovery call to see how your trial operations benchmark against AI-enhanced leaders — and what Xamun can build for you in weeks.

Book a Discovery → Explore the Live Demo →