Neogenomics (NEO) EV to EBITDA (2010 - 2026)
Neogenomics' (NEO) quarterly EV to EBITDA came in at 176.11 in Q2 2026, down 979.55% on a YoY basis from 20.02 in Q2 2025, and down 293.74% quarter-over-quarter from 44.73 in Q1 2026.
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Neogenomics (NEO) EV to EBITDA (2010 - 2026) Analysis & Trends
Neogenomics (NEO) has reported EV to EBITDA for 17 consecutive years, with 176.11 the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, EV to EBITDA fell 979.55% year-over-year to 176.11; the trailing twelve-month figure through Jun 2026 stood at 25.14 (down 272.3% YoY), and the FY2025 full-year result was 11.71, up 37.46% from the prior year.
- EV to EBITDA fell to 176.11 in Q2 2026 per NEO's latest filing, from 44.73 in the prior quarter.
- Across five years, EV to EBITDA topped out at 14.06 in Q2 2022 and bottomed at 176.11 in Q2 2026.
- Historically, EV to EBITDA has averaged 55.63 across 5 years, with a median of 49.65 in 2023.
- The sharpest annual moves came in 2022 and 2026: EV to EBITDA soared 93.81% in 2022, then slumped 979.55% in 2026.
- Over 5 years, EV to EBITDA stood at 27.85 in 2022, then sank by 218.16% to 88.6 in 2023, then fell by 5.81% to 93.74 in 2024, then fell by 7.94% to 101.18 in 2025, then tumbled by 74.05% to 176.11 in 2026.
- According to Business Quant data, EV to EBITDA over the past three periods registered 176.11, 44.73, and 101.18 for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Natera | 53.05 Bn | 51.95 Bn | 486.15 Mn |
| 2 | Quest Diagnostics | 27.19 Bn | 26.87 Bn | 1.03 Bn |
| 3 | Labcorp Holdings | 25.93 Bn | 25.81 Bn | 1.11 Bn |
| 4 | Guardant Health | 23.97 Bn | 22.91 Bn | 219.03 Mn |
| 5 | Tempus AI | 13.64 Bn | 12.82 Bn | 274.25 Mn |
| 6 | Caris Life Sciences | 8.47 Bn | 7.68 Bn | 182.38 Mn |
| 7 | Sotera Health | 5.35 Bn | 4.99 Bn | 177.96 Mn |
| 8 | BillionToOne | 4.96 Bn | 4.41 Bn | 77.11 Mn |
| 9 | Adaptive Biotechnologies | 4.55 Bn | 4.21 Bn | 51.39 Mn |
| 10 | Neogenomics | 2.55 Bn | 2.40 Bn | 91.88 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -176.11 |
| Mar 31, 2026 | -44.73 |
| Dec 31, 2025 | -101.18 |
| Sep 30, 2025 | -30.76 |
| Jun 30, 2025 | -16.31 |
| Mar 31, 2025 | -30.91 |
| Dec 31, 2024 | -93.74 |
| Sep 30, 2024 | -70.82 |
| Jun 30, 2024 | -63.14 |
| Mar 31, 2024 | -52.95 |
| Dec 31, 2023 | -88.60 |
| Sep 30, 2023 | -48.07 |
| Jun 30, 2023 | -54.66 |
| Mar 31, 2023 | -51.23 |
| Dec 31, 2022 | -27.85 |
| Sep 30, 2022 | -16.35 |
| Jun 30, 2022 | -14.06 |
| Mar 31, 2022 | -19.87 |
| Dec 31, 2021 | -89.47 |
| Sep 30, 2021 | -136.01 |
API Access
Neogenomics EV to EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=NEO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "NEO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=NEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();