Shin Nippon Biomedical Laboratories, Ltd (SBLOF) Fair Value & Analysis
Healthcare · US · Market cap $381M
Fair value as of: Jun 24, 2026
Analysis
Shin Nippon Biomedical Laboratories, Ltd (SBLOF) currently trades at $9.16, while our model-based Fair Value estimate is $12.07 — implying the stock looks roughly 31.8% 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
Shin Nippon Biomedical Laboratories, Ltd., a contract research organization, engages in the pharmaceutical development, transactional research, and medipolis businesses in Japan and internationally. It offers non-clinical testing and non-clinical regulatory consulting for the development of pharmaceuticals, medical devices, or regenerative medicine products, including safety and pharmacology testing, and pharmacokinetic studies. The company also engages in licensing activities for proprietary products which utilize unique intranasal formulation delivery technology, discovery of future seeds, and business promotion activities; and development of artificial seed production for Japanese eels. In addition, it operates hotels accommodations facilities under the Villa Amafuru Oka and HOTEL Freesia names; and develops and operates geothermal and hot spring thermal power plants. Shin Nippon Biomedical Laboratories, Ltd. was founded in 1957 and is headquartered in Kagoshima, Japan.
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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.