Radnostix, Inc (INIS) Fair Value & Analysis
Healthcare · US · Market cap $37.0M
Fair value as of: Jun 24, 2026
Analysis
Radnostix, Inc (INIS) currently trades at $0.0800, while our model-based Fair Value estimate is $0.0300 — implying the stock looks roughly 62.5% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).
About the company
Radnostix, Inc. manufactures and sells nuclear medicine calibration and reference standards, cobalt-60 products, sodium iodide I-131 drug product, and radiochemicals for clinical research and life sciences in the United States and internationally. It operates through five segments: Theranostics Products, Cobalt Products, Calibration & Reference Products, Medical Devices, and Fluorine Products. The Theranostics Products segment produces and distributes Iodine-131 generic drug product and various isotopically pure radiochemicals for medical, industrial, and research applications. The Cobalt Products segment produces cobalt-60 products and services, the fabrication of cobalt-60 sealed sources for radiation therapy, industrial and medical applications, and recycling of expended cobalt-60 sources. The Calibration & Reference Products segment manufactures sources and standards associated with single photon emission computed and positron emission tomography imaging, patient positioning, an…
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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.