Pulmonx (LUNG) Operating Expenses (2019 - 2025)
Pulmonx (LUNG) posted Operating Expenses of $30.45 million for Q3 2025, up 4.4% from $29.16 million a year earlier but down 4.9% from the prior quarter.
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Analysis
Pulmonx (LUNG) Operating Expenses (2019 - 2025) Analysis & Trends
For the trailing twelve months through Sep 30, 2025, Operating Expenses at Pulmonx was $124.37 million, up 6.3% year-over-year; for FY2024, it was $119.71 million, up 6.2% from FY2023.
- Annual Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 24.4% (FY2019 to FY2024).
- In prior years, Pulmonx's Operating Expenses was $112.69 million in FY2023 (+14.4%), $98.5 million in FY2022 (+18.8%), $82.93 million in FY2021 (+54.9%) and $53.53 million in FY2020 (+33.0%).
- Quarterly Operating Expenses has run from a low of $16.43 million in Q4 2020 to a high of $32.01 million in Q2 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 21 quarters, with growth averaging 6.3% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 3.4% in Q3 2024 to 73.2% in Q2 2021.
- According to Business Quant data, Operating Expenses for the three prior quarters was $32.01 million (Q2 2025), $30.91 million (Q1 2025) and $31.01 million (Q4 2024).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Pulmonx | 79.60 Mn | -239.63 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 30.45 Mn |
| Jun 30, 2025 | 32.01 Mn |
| Mar 31, 2025 | 30.91 Mn |
| Dec 31, 2024 | 31.01 Mn |
| Sep 30, 2024 | 29.16 Mn |
| Jun 30, 2024 | 30.93 Mn |
| Mar 31, 2024 | 28.61 Mn |
| Dec 31, 2023 | 28.32 Mn |
| Sep 30, 2023 | 28.21 Mn |
| Jun 30, 2023 | 29.17 Mn |
| Mar 31, 2023 | 26.99 Mn |
| Dec 31, 2022 | 25.81 Mn |
| Sep 30, 2022 | 24.08 Mn |
| Jun 30, 2022 | 24.83 Mn |
| Mar 31, 2022 | 23.78 Mn |
| Dec 31, 2021 | 22.62 Mn |
| Sep 30, 2021 | 19.50 Mn |
| Jun 30, 2021 | 21.71 Mn |
| Mar 31, 2021 | 19.11 Mn |
| Dec 31, 2020 | 16.43 Mn |
API Access
Pulmonx Operating Expenses 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=operating-expenses&ticker=LUNG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LUNG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=LUNG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();