Korro Bio (KRRO) Operating Expenses (2018 - 2026)
Korro Bio's Operating Expenses was $20.11 million in Q2 2026, down 29.8% from $28.66 million a year earlier and down 1.6% from the prior quarter.
Korro Bio (KRRO) Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Korro Bio's Operating Expenses was $112.56 million through Jun 30, 2026, up 7.4% year-over-year; for FY2025, it came in at $128.25 million, up 36.2% from FY2024.
- Operating Expenses has now increased for three consecutive years, with a five-year compound annual growth rate of 14.7% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $94.18 million in FY2024 (+11.4%), $84.53 million in FY2023 (+43.3%), $59 million in FY2022 (-39.9%) and $98.1 million in FY2021 (+52.0%).
- The Q2 2026 figure marks the lowest quarterly Operating Expenses since Q3 2023.
- Compared with a year earlier, Operating Expenses was higher in four of the last eight quarters, with growth averaging 12.4%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2025 (growth of 104.2%); the worst was Q2 2026 (a decline of 29.8%).
- Per Business Quant data, KRRO's Operating Expenses in the three quarters before Q2 2026 was $20.44 million (Q1 2026), $51.69 million (Q4 2025) and $20.33 million (Q3 2025).
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 | Korro Bio | 145.73 Mn | -250.91 Mn | - | 20.11 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 20.11 Mn |
| Mar 31, 2026 | 20.44 Mn |
| Dec 31, 2025 | 51.69 Mn |
| Sep 30, 2025 | 20.33 Mn |
| Jun 30, 2025 | 28.66 Mn |
| Mar 31, 2025 | 27.57 Mn |
| Dec 31, 2024 | 25.31 Mn |
| Sep 30, 2024 | 23.29 Mn |
| Jun 30, 2024 | 24.13 Mn |
| Mar 31, 2024 | 21.45 Mn |
| Dec 31, 2023 | 26.89 Mn |
| Sep 30, 2023 | 19.15 Mn |
| Jun 30, 2023 | 18.41 Mn |
| Mar 31, 2023 | 20.09 Mn |
| Dec 31, 2022 | -5.81 Mn |
| Sep 30, 2022 | 20.28 Mn |
| Jun 30, 2022 | 21.27 Mn |
| Mar 31, 2022 | 23.26 Mn |
| Dec 31, 2021 | 21.36 Mn |
| Sep 30, 2021 | 24.99 Mn |
Korro Bio 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=KRRO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KRRO", "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=KRRO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();