Cambridge Nutritional Sciences plc (CNSL) Fair Value & Analysis
Healthcare · GB · Market cap 4.3M GBX
Fair value as of: Jun 26, 2026
Analysis
Cambridge Nutritional Sciences plc (CNSL) currently trades at p0.0175, while our model-based Fair Value estimate is p0.0284 — implying the stock looks roughly 62.5% 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: medium) — always confirm before acting.
About the company
Cambridge Nutritional Sciences plc, together with its subsidiaries, develops, manufactures, and distributes medical diagnostics products for the food sensitivity testing market. The company is involved in the research, development, and production of kits for detection of immune reactions to food under the FoodPrint brand. It also provides clinical analysis to the general public, clinics, and health professionals; and supplies Food Detective, a food sensitivity test. In addition, the company offers My Health Tracker, a health app for tracking symptoms, accessing FoodPrint results, and managing gut health; and CNS Lab, which provides laboratory services for food sensitivity. It serves the government, private hospitals and clinics, reference laboratories, nutritionists, naturopaths, consumers, and functional medicine healthcare practitioners in the United Kingdom, rest of Europe, North America, South/Central America, India, rest of Asia and the Far East, Africa, and the Middle East. Th…
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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.