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Petros Pharmaceuticals, Inc (PTPI) Fair Value & Analysis

Healthcare · US · Market cap $254K

Price$0.0060
Fair Value$0.0060
Upside+0.1%
Quality95/100
Evidence: Medium Range $0.0059 – $0.0061

Fair value as of: Jun 26, 2026

Analysis

Petros Pharmaceuticals, Inc (PTPI) currently trades at $0.0060, while our model-based Fair Value estimate is $0.0060 — implying the stock looks roughly 0.1% 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

Petros Pharmaceuticals, Inc., a healthcare technology company, focuses on developing and licensing proprietary software as a service (SaaS) platform and Software as a medical device web application designed to assist pharmaceutical companies. The company is based in New York, New York.

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Frequently asked questions

Is Petros Pharmaceuticals, Inc (PTPI) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $0.0060 versus a price of $0.0060 — about +0% (undervalued). Model-based estimate, not financial advice.
What is the fair value of PTPI?
Our 21-model fair value for Petros Pharmaceuticals, Inc is $0.0060 (as of Jun 26, 2026), built from audited fundamentals. The current price is $0.0060.
What is the quality score of PTPI?
Petros Pharmaceuticals, Inc has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.