Coya Therapeutics (COYA) Operating Expenses (2022 - 2026)
Coya Therapeutics (COYA) posted Operating Expenses of $7.29 million for Q2 2026, up 10.8% from $6.58 million a year earlier but down 7.6% from the prior quarter.
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Analysis
Coya Therapeutics (COYA) Operating Expenses (2022 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Coya Therapeutics was $31.17 million, up 35.3% year-over-year; for FY2025, it came in at $30.5 million, up 46.6% from FY2024.
- Annual Operating Expenses has increased for four consecutive years, with a four-year compound annual growth rate of 58.2% (FY2021 to FY2025).
- In prior years, Coya Therapeutics' Operating Expenses was $20.8 million in FY2024 (+49.6%), $13.91 million in FY2023 (+41.7%), $9.81 million in FY2022 (+101.5%) and $4.87 million in FY2021.
- Quarterly Operating Expenses has run from a low of $1.7 million in Q1 2022 to a high of $9.99 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in five of the last eight quarters, with growth averaging 31.5%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2025, with growth of 144.7%; the weakest was Q2 2023, with a decline of 5.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $7.89 million (Q1 2026), $9.99 million (Q4 2025) and $6 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,146.94 Bn | 1,115.53 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 624.96 Bn | 543.49 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 510.15 Bn | 483.27 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 366.13 Bn | 320.51 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 297.75 Bn | 261.74 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.93 Bn | 235.62 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 236.51 Bn | 191.91 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 194.27 Bn | 168.47 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 171.74 Bn | 118.39 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Coya Therapeutics | 99.34 Mn | -69.54 Mn | - | 7.29 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.29 Mn |
| Mar 31, 2026 | 7.89 Mn |
| Dec 31, 2025 | 9.99 Mn |
| Sep 30, 2025 | 6.00 Mn |
| Jun 30, 2025 | 6.58 Mn |
| Mar 31, 2025 | 7.93 Mn |
| Dec 31, 2024 | 4.08 Mn |
| Sep 30, 2024 | 4.45 Mn |
| Jun 30, 2024 | 6.66 Mn |
| Mar 31, 2024 | 5.61 Mn |
| Dec 31, 2023 | 4.19 Mn |
| Sep 30, 2023 | 3.56 Mn |
| Jun 30, 2023 | 3.25 Mn |
| Mar 31, 2023 | 2.90 Mn |
| Dec 31, 2022 | 2.00 Mn |
| Sep 30, 2022 | 2.66 Mn |
| Jun 30, 2022 | 3.45 Mn |
| Mar 31, 2022 | 1.70 Mn |
API Access
Coya 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=COYA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "COYA", "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=COYA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();