Spero Therapeutics (SPRO) Operating Expenses (2016 - 2026)
Spero Therapeutics' Operating Expenses was $9.93 million in Q2 2026, down 40.3% from $16.63 million a year earlier but up 27.3% from the prior quarter.
Spero Therapeutics (SPRO) Operating Expenses (2016 - 2026) Analysis & Trends
On a trailing twelve-month basis, Spero Therapeutics' Operating Expenses was $40.97 million through Jun 30, 2026, down 61.4% year-over-year; for FY2025, it came in at $60.49 million, down 50.1% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of -7.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $121.34 million in FY2024 (+47.4%), $82.3 million in FY2023 (-14.0%), $95.71 million in FY2022 (-9.9%) and $106.23 million in FY2021 (+20.1%).
- Quarterly Operating Expenses has moved between $7.8 million (Q1 2026) and $36.77 million (Q4 2024) over five years.
- Compared with a year earlier, Operating Expenses has declined for six straight quarters, with an average decline of 26.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2023 (growth of 98.0%); the worst was Q4 2025 (a decline of 73.1%).
- Per Business Quant data, SPRO's Operating Expenses in the three quarters before Q2 2026 was $7.8 million (Q1 2026), $9.89 million (Q4 2025) and $13.36 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.97 Bn | 1,105.55 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 619.72 Bn | 538.25 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 503.40 Bn | 476.52 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 370.15 Bn | 324.53 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 298.64 Bn | 262.63 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.07 Bn | 234.76 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 237.00 Bn | 192.40 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 191.24 Bn | 165.43 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 170.31 Bn | 116.96 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Spero Therapeutics | 68.40 Mn | -127.38 Mn | - | 9.93 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.93 Mn |
| Mar 31, 2026 | 7.80 Mn |
| Dec 31, 2025 | 9.89 Mn |
| Sep 30, 2025 | 13.36 Mn |
| Jun 30, 2025 | 16.63 Mn |
| Mar 31, 2025 | 20.61 Mn |
| Dec 31, 2024 | 36.77 Mn |
| Sep 30, 2024 | 32.06 Mn |
| Jun 30, 2024 | 29.26 Mn |
| Mar 31, 2024 | 23.25 Mn |
| Dec 31, 2023 | 22.99 Mn |
| Sep 30, 2023 | 27.41 Mn |
| Jun 30, 2023 | 15.61 Mn |
| Mar 31, 2023 | 16.30 Mn |
| Dec 31, 2022 | 21.52 Mn |
| Sep 30, 2022 | 13.84 Mn |
| Jun 30, 2022 | 28.07 Mn |
| Mar 31, 2022 | 32.28 Mn |
| Dec 31, 2021 | 30.25 Mn |
| Sep 30, 2021 | 25.59 Mn |
Spero Therapeutics 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=SPRO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SPRO", "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=SPRO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();