Pharma Mar, S.A (PHMMF) Fair Value & Analysis
Healthcare · US · Market cap $1.4B
Fair value as of: Jun 24, 2026
Analysis
Pharma Mar, S.A (PHMMF) currently trades at $79.49, while our model-based Fair Value estimate is $50.84 — implying the stock looks roughly 36.0% 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: high).
About the company
Pharma Mar, S.A., a biopharmaceutical company, focuses on the research, development, production, and commercialization of bio-active principles for the use in oncology in Spain, Germany, Ireland, France, Switzerland, rest of the European Union, the United States, and internationally. It operates through Oncology and RNA Interference segments. The company offers Yondelis, a synthetic compound derived from the colonial sea squirt ecteinascidia turbinata that treats soft tissue sarcoma and ovarian cancer; Zepzelca, a synthetic compound designed to treat small lung cancer cells; and Aplidin, that is extracted from the ascidian Aplidium albicans to treat patients with multiple myeloma. It also develops LAGOON, which is in Phase III clinical trial for the treatment of small cell lung cancer; SaLuDo, which is in Phase III trial to treat patients with metastatic leiomyosarcoma; as well as PM534 that is Phase I clinical trials for treating solid tumors; PM54, which is in Phase I clinical tri…
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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.