Lantheus Holdings (LNTH) Operating Expenses (2014 - 2026)
Lantheus Holdings (LNTH) recorded Operating Expenses of $58.84 million in Q2 2026, down 47.5% from $112 million a year earlier and down 39.3% from the prior quarter.
Lantheus Holdings (LNTH) Operating Expenses (2014 - 2026) Analysis & Trends
On a TTM basis, Lantheus Holdings' Operating Expenses came in at $403.04 million as of Jun 30, 2026, up 11.0% year-over-year; for FY2025, it was $452.43 million, up 25.1% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 25.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $361.79 million in FY2024 (+78.1%), $203.17 million in FY2023 (-54.4%), $445.27 million in FY2022 (+127.9%) and $195.36 million in FY2021 (+36.7%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q4 2023.
- On a year-over-year basis, Operating Expenses rose in six of the last eight quarters, with growth averaging 22.0%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 322.4% in Q4 2022, against a decline of 81.7% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $96.91 million (Q1 2026), $117.37 million (Q4 2025) and $129.92 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Lantheus Holdings | 6.51 Bn | 4.68 Bn | 241.86 Mn | 58.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 58.84 Mn |
| Mar 31, 2026 | 96.91 Mn |
| Dec 31, 2025 | 117.37 Mn |
| Sep 30, 2025 | 129.92 Mn |
| Jun 30, 2025 | 112.00 Mn |
| Mar 31, 2025 | 93.13 Mn |
| Dec 31, 2024 | 93.19 Mn |
| Sep 30, 2024 | 64.66 Mn |
| Jun 30, 2024 | 108.01 Mn |
| Mar 31, 2024 | 95.92 Mn |
| Dec 31, 2023 | 57.12 Mn |
| Sep 30, 2023 | 50.19 Mn |
| Jun 30, 2023 | 42.05 Mn |
| Mar 31, 2023 | 53.80 Mn |
| Dec 31, 2022 | 311.87 Mn |
| Sep 30, 2022 | 36.28 Mn |
| Jun 30, 2022 | 47.33 Mn |
| Mar 31, 2022 | 49.79 Mn |
| Dec 31, 2021 | 73.82 Mn |
| Sep 30, 2021 | 39.80 Mn |
Lantheus Holdings 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=LNTH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LNTH", "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=LNTH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();