Inotiv, Inc (NOTV) Fair Value & Analysis
Healthcare · US · Market cap $2.8M
Fair value as of: Jun 26, 2026
Analysis
Inotiv, Inc (NOTV) currently trades at $0.0360, while our model-based Fair Value estimate is $0.0302 — implying the stock looks roughly 16.0% 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: low).
About the company
Inotiv, Inc. provides nonclinical and analytical drug discovery and development services to the pharmaceutical and medical device industries in the United States, the Netherlands, and internationally. The company operates through two segments, Discovery and Safety Assessment (DSA) and Research Models and Services (RMS). The DMS segment manufactures scientific instruments for life sciences research and the related software for use by pharmaceutical companies, universities, government research centers, and medical research institutions under the company's BASi product line. The RMS segment engages in commercial production and sales of research models, diets, bedding, and bioproducts. The company was formerly known as Bioanalytical Systems, Inc. and changed its name to Inotiv, Inc. in March 2021. Inotiv, Inc. was incorporated in 1974 and is headquartered in West Lafayette, Indiana. On June 3, 2026, Inotiv, Inc. along with its affiliates filed a voluntary petition for reorganization un…
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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.