Personalis, Inc (PSNL) Fair Value & Analysis
Healthcare · US · Market cap $1.1B
Analysis
Personalis, Inc (PSNL) currently trades at $10.06, while our model-based Fair Value estimate is $11.22 — implying the stock looks roughly 11.5% 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: low) — always confirm before acting.
About the company
Personalis, Inc. develops, markets, and sells advanced cancer genomic tests and services in the United States and internationally. The company offers NeXT Personal, a tumor-informed liquid biopsy test for detection of minimal residual disease (MRD), therapy response and recurrence monitoring in solid tumor cancers; and ImmunoID NeXT, a tissue-based service that combines whole exome and whole transcriptome sequencing data with advanced analytics to provide a multi-dimensional view of the tumor and the tumor microenvironment from a single sample. It also provides NeXT Personal Dx, a tumor-informed liquid biopsy test for the detection of MRD; and NeXT Dx, a tumor profiling test that is used to help select therapy for a cancer patient and identify potential clinical trials for a patient. In addition, the company performs whole exome sequencing of cancer tissue and matched blood samples for diagnostic companies as an input to their products; and whole genome sequencing on human samples f…
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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.