Dianthus Therapeutics (DNTH) Operating Expenses (2017 - 2026)
Dianthus Therapeutics (DNTH) posted Operating Expenses of $40.68 million for Q3 2025, up 26.9% from $32.07 million a year earlier and up 15.8% from the prior quarter.
Dianthus Therapeutics (DNTH) Operating Expenses (2017 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2025, Operating Expenses at Dianthus Therapeutics was $143.39 million, up 62.4% year-over-year; for FY2024, it was $108.1 million, up 112.0% from FY2023.
- Annual Operating Expenses shows a five-year compound annual growth rate of 5.4% (FY2019 to FY2024).
- In prior years, Dianthus Therapeutics' Operating Expenses was $51 million in FY2023 (+41.2%), $36.12 million in FY2022 (-51.6%), $74.69 million in FY2021 (-5.1%) and $78.7 million in FY2020 (-5.1%).
- The Q3 2025 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2017.
- On a year-over-year basis, Operating Expenses has increased in each of the last nine quarters, with growth averaging 78.4% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2024, with growth of 147.8%; the weakest was Q1 2023, with a decline of 65.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $35.12 million (Q2 2025), $34.34 million (Q1 2025) and $33.24 million (Q4 2024).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,348.13 Bn | 1,321.74 Bn | 20.46 Bn | 15.99 Bn |
| 2 | Johnson & Johnson | 675.90 Bn | 595.76 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 519.45 Bn | 487.50 Bn | 13.12 Bn | 11.14 Bn |
| 4 | Merck | 364.95 Bn | 327.95 Bn | 13.19 Bn | 12.53 Bn |
| 5 | Novartis Ag | 311.58 Bn | 285.16 Bn | - | - |
| 6 | Astrazeneca | 289.34 Bn | 262.94 Bn | 13.26 Bn | 9.00 Bn |
| 7 | Amgen | 251.64 Bn | 203.30 Bn | 7.58 Bn | 6.66 Bn |
| 8 | Gilead Sciences | 212.05 Bn | 187.07 Bn | 6.73 Bn | 4.84 Bn |
| 9 | Pfizer | 167.35 Bn | 115.00 Bn | 12.56 Bn | 7.09 Bn |
| 10 | Dianthus Therapeutics | 5.00 Bn | 4.95 Bn | - | 59.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 59.68 Mn |
| Jun 30, 2026 | 62.24 Mn |
| Mar 31, 2026 | 47.00 Mn |
| Dec 31, 2025 | 69.83 Mn |
| Sep 30, 2025 | 40.68 Mn |
| Jun 30, 2025 | 35.12 Mn |
| Mar 31, 2025 | 34.34 Mn |
| Dec 31, 2024 | 33.24 Mn |
| Sep 30, 2024 | 32.07 Mn |
| Jun 30, 2024 | 24.07 Mn |
| Mar 31, 2024 | 18.72 Mn |
| Dec 31, 2023 | 13.41 Mn |
| Sep 30, 2023 | 16.68 Mn |
| Jun 30, 2023 | 12.75 Mn |
| Mar 31, 2023 | 8.16 Mn |
| Dec 31, 2022 | 11.87 Mn |
| Sep 30, 2022 | 9.43 Mn |
| Jun 30, 2022 | 18.08 Mn |
| Mar 31, 2022 | 23.83 Mn |
| Dec 31, 2021 | 20.14 Mn |
Dianthus 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=DNTH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DNTH", "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=DNTH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();