Thermo Fisher Scientific (TMO) Capital Expenditures (2009 - 2026)
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Analysis
Thermo Fisher Scientific (TMO) Capital Expenditures (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 257.79 Bn | 234.30 Bn | 5.13 Bn | 437.00 Mn |
| 2 | Abbott Laboratories | 190.83 Bn | 164.70 Bn | 7.39 Bn | 513.00 Mn |
| 3 | Danaher | 162.10 Bn | 141.75 Bn | 3.84 Bn | 255.00 Mn |
| 4 | Intuitive Surgical | 158.05 Bn | 138.34 Bn | 2.08 Bn | 113.10 Mn |
| 5 | Medtronic | 130.31 Bn | 95.56 Bn | 6.34 Bn | 503.00 Mn |
| 6 | Stryker | 124.76 Bn | 110.95 Bn | 4.25 Bn | 237.00 Mn |
| 7 | Boston Scientific | 62.03 Bn | 57.46 Bn | 3.43 Bn | 180.00 Mn |
| 8 | Edwards Lifesciences | 58.73 Bn | 41.94 Bn | 1.35 Bn | 63.60 Mn |
| 9 | Becton Dickinson | 58.33 Bn | 55.48 Bn | 2.32 Bn | 143.00 Mn |
| 10 | Agilent Technologies | 49.29 Bn | 42.18 Bn | 1.04 Bn | 80.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 26, 2026 | 437.00 Mn |
| Jun 27, 2026 | 450.00 Mn |
| Mar 28, 2026 | 376.00 Mn |
| Dec 31, 2025 | 465.00 Mn |
| Sep 27, 2025 | 404.00 Mn |
| Jun 28, 2025 | 294.00 Mn |
| Mar 29, 2025 | 362.00 Mn |
| Dec 31, 2024 | 480.00 Mn |
| Sep 28, 2024 | 272.00 Mn |
| Jun 29, 2024 | 301.00 Mn |
| Mar 30, 2024 | 347.00 Mn |
| Dec 31, 2023 | 405.00 Mn |
| Sep 30, 2023 | 332.00 Mn |
| Jul 1, 2023 | 284.00 Mn |
| Apr 1, 2023 | 458.00 Mn |
| Dec 31, 2022 | 550.00 Mn |
| Oct 1, 2022 | 547.00 Mn |
| Jul 2, 2022 | 506.00 Mn |
| Apr 2, 2022 | 640.00 Mn |
| Dec 31, 2021 | 831.00 Mn |
API Access
Thermo Fisher Scientific Capital Expenditures 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=capital-expenditures&ticker=TMO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "ticker": "TMO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=capital-expenditures&ticker=TMO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();