DATATRAK International, Inc (DTRK) Fair Value & Analysis
Healthcare · US · Market cap $10.8M
Fair value as of: Jun 24, 2026
Analysis
DATATRAK International, Inc (DTRK) currently trades at $0.4000, while our model-based Fair Value estimate is $0.6000 — implying the stock looks roughly 50.0% undervalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
DATATRAK International, Inc., a technology and services company, provides unified clinical solutions and related services for the clinical trials industry. The company offers DATATRAK ONE Unified Experience, a clinical enterprise solution that allows clinical users and service providers to design, deliver, and manage clinical trials. Its products include UX CTMS 360 for planning and managing trials; UX Trial to streamline design-to-deployment process using a tool; UX EDC & Medical Coding for capturing and delivering data; UX Randomization and Trial Supply Management to randomize patients and automate supply; UX Patient Data Capture; UX Safety; and UX Training to train users and track certificates. The company also provides DATATRAK Clinical Consulting Services, such as training, support, learning center, Software as a Service hosting, standards, and trial design services. It serves contract research organizations, pharma and biotech companies, and clinical trial device companies. DA…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.