LeonaBio (LONA) Operating Expenses (2019 - 2026)
LeonaBio's Operating Expenses was $19.45 million in Q2 2026, up 166.8% from $7.29 million a year earlier and up 13.0% from the prior quarter.
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Analysis
LeonaBio (LONA) Operating Expenses (2019 - 2026) Analysis & Trends
On a trailing twelve-month basis, LeonaBio's Operating Expenses was $122.11 million through Jun 30, 2026, up 96.9% year-over-year; for FY2025, it was $102.27 million, up 1.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 38.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $100.9 million in FY2024 (-19.6%), $125.47 million in FY2023 (+20.6%), $104.02 million in FY2022 (+62.5%) and $64.02 million in FY2021 (+220.2%).
- Quarterly Operating Expenses has moved between $6.87 million (Q3 2025) and $78.57 million (Q4 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 46.7% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2025 (growth of 404.7%); the worst was Q3 2025 (a decline of 76.8%).
- Per Business Quant data, LONA's Operating Expenses in the three quarters before Q2 2026 was $17.21 million (Q1 2026), $78.57 million (Q4 2025) and $6.87 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn | 2.09 Bn |
| 10 | LeonaBio | 84.70 Mn | -147.60 Mn | - | 19.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19.45 Mn |
| Mar 31, 2026 | 17.21 Mn |
| Dec 31, 2025 | 78.57 Mn |
| Sep 30, 2025 | 6.87 Mn |
| Jun 30, 2025 | 7.29 Mn |
| Mar 31, 2025 | 9.54 Mn |
| Dec 31, 2024 | 15.57 Mn |
| Sep 30, 2024 | 29.62 Mn |
| Jun 30, 2024 | 28.03 Mn |
| Mar 31, 2024 | 27.69 Mn |
| Dec 31, 2023 | 29.01 Mn |
| Sep 30, 2023 | 35.04 Mn |
| Jun 30, 2023 | 31.64 Mn |
| Mar 31, 2023 | 29.77 Mn |
| Dec 31, 2022 | 32.93 Mn |
| Sep 30, 2022 | 24.13 Mn |
| Jun 30, 2022 | 23.57 Mn |
| Mar 31, 2022 | 23.39 Mn |
| Dec 31, 2021 | 18.78 Mn |
| Sep 30, 2021 | 17.83 Mn |
API Access
LeonaBio 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=LONA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LONA", "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=LONA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();