Kodiak Sciences (KOD) Operating Expenses (2017 - 2026)
Kodiak Sciences (KOD) recorded Operating Expenses of $66.84 million in Q2 2026, up 20.4% from $55.51 million a year earlier and up 11.8% from the prior quarter.
Kodiak Sciences (KOD) Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Kodiak Sciences' Operating Expenses came in at $246.42 million as of Jun 30, 2026, up 18.8% year-over-year; for FY2025, it came in at $234.39 million, up 25.4% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 11.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $186.85 million in FY2024 (-32.6%), $277.32 million in FY2023 (-18.8%), $341.38 million in FY2022 (+27.8%) and $267.05 million in FY2021 (+96.4%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q2 2023.
- On a year-over-year basis, Operating Expenses has increased for six consecutive quarters, with growth averaging 10.3% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 98.6% in Q4 2021, against a decline of 43.4% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $59.78 million (Q1 2026), $57.45 million (Q4 2025) and $62.35 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 | Kodiak Sciences | 5.65 Bn | 5.65 Bn | - | 66.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 66.84 Mn |
| Mar 31, 2026 | 59.78 Mn |
| Dec 31, 2025 | 57.45 Mn |
| Sep 30, 2025 | 62.35 Mn |
| Jun 30, 2025 | 55.51 Mn |
| Mar 31, 2025 | 59.07 Mn |
| Dec 31, 2024 | 46.18 Mn |
| Sep 30, 2024 | 46.63 Mn |
| Jun 30, 2024 | 47.98 Mn |
| Mar 31, 2024 | 46.06 Mn |
| Dec 31, 2023 | 63.37 Mn |
| Sep 30, 2023 | 54.50 Mn |
| Jun 30, 2023 | 84.83 Mn |
| Mar 31, 2023 | 74.62 Mn |
| Dec 31, 2022 | 74.07 Mn |
| Sep 30, 2022 | 79.48 Mn |
| Jun 30, 2022 | 92.07 Mn |
| Mar 31, 2022 | 95.77 Mn |
| Dec 31, 2021 | 93.05 Mn |
| Sep 30, 2021 | 67.54 Mn |
Kodiak 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=KOD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KOD", "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=KOD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();