SELLAS Life Sciences (SLS) Operating Expenses (2010 - 2026)
SELLAS Life Sciences (SLS) posted Operating Expenses of $10.63 million for Q2 2026, up 54.6% from $6.87 million a year earlier and up 14.9% from the prior quarter.
SELLAS Life Sciences (SLS) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at SELLAS Life Sciences was $35.22 million, up 29.6% year-over-year; for FY2025, it came in at $28.27 million, down 10.3% from FY2024.
- Annual Operating Expenses has declined for three consecutive years, though with a five-year compound annual growth rate of 8.4% (FY2020 to FY2025).
- In prior years, SELLAS Life Sciences' Operating Expenses was $31.51 million in FY2024 (-16.8%), $37.87 million in FY2023 (-11.8%), $42.95 million in FY2022 (+30.6%) and $32.89 million in FY2021 (+74.2%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q1 2023.
- On a year-over-year basis, Operating Expenses has increased in each of the last three quarters, with growth averaging 4.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 123.2%; the weakest was Q1 2025, with a decline of 37.1%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $9.25 million (Q1 2026), $8.26 million (Q4 2025) and $7.08 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | SELLAS Life Sciences | 2.34 Bn | 2.34 Bn | - | 10.63 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 10.63 Mn |
| Mar 31, 2026 | 9.25 Mn |
| Dec 31, 2025 | 8.26 Mn |
| Sep 30, 2025 | 7.08 Mn |
| Jun 30, 2025 | 6.87 Mn |
| Mar 31, 2025 | 6.06 Mn |
| Dec 31, 2024 | 6.92 Mn |
| Sep 30, 2024 | 7.33 Mn |
| Jun 30, 2024 | 7.62 Mn |
| Mar 31, 2024 | 9.65 Mn |
| Dec 31, 2023 | 8.18 Mn |
| Sep 30, 2023 | 9.36 Mn |
| Jun 30, 2023 | 9.05 Mn |
| Mar 31, 2023 | 11.28 Mn |
| Dec 31, 2022 | 9.45 Mn |
| Sep 30, 2022 | 7.15 Mn |
| Jun 30, 2022 | 8.62 Mn |
| Mar 31, 2022 | 17.74 Mn |
| Dec 31, 2021 | 11.62 Mn |
| Sep 30, 2021 | 6.98 Mn |
SELLAS Life Sciences 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=SLS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SLS", "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=SLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();