Design Therapeutics (DSGN) Operating Expenses (2020 - 2026)
Design Therapeutics (DSGN) posted Operating Expenses of $22.18 million for Q2 2026, up 2.8% from $21.57 million a year earlier and up 12.5% from the prior quarter.
Design Therapeutics (DSGN) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Design Therapeutics was $79.36 million, up 5.9% year-over-year; for FY2025, it was $79.47 million, up 27.4% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 56.2% (FY2020 to FY2025).
- In prior years, Design Therapeutics' Operating Expenses was $62.38 million in FY2024 (-20.2%), $78.19 million in FY2023 (+15.7%), $67.59 million in FY2022 (+88.6%) and $35.83 million in FY2021 (+318.8%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q2 2023.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 13.6%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 371.8%; the weakest was Q1 2024, with a decline of 33.5%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $19.71 million (Q1 2026), $18.17 million (Q4 2025) and $19.31 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 | Design Therapeutics | 773.49 Mn | -82.54 Mn | - | 22.18 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 22.18 Mn |
| Mar 31, 2026 | 19.71 Mn |
| Dec 31, 2025 | 18.17 Mn |
| Sep 30, 2025 | 19.31 Mn |
| Jun 30, 2025 | 21.57 Mn |
| Mar 31, 2025 | 20.42 Mn |
| Dec 31, 2024 | 16.69 Mn |
| Sep 30, 2024 | 16.25 Mn |
| Jun 30, 2024 | 15.04 Mn |
| Mar 31, 2024 | 14.40 Mn |
| Dec 31, 2023 | 15.12 Mn |
| Sep 30, 2023 | 18.82 Mn |
| Jun 30, 2023 | 22.60 Mn |
| Mar 31, 2023 | 21.65 Mn |
| Dec 31, 2022 | 19.39 Mn |
| Sep 30, 2022 | 19.19 Mn |
| Jun 30, 2022 | 15.64 Mn |
| Mar 31, 2022 | 13.37 Mn |
| Dec 31, 2021 | 11.13 Mn |
| Sep 30, 2021 | 11.34 Mn |
Design 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=DSGN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DSGN", "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=DSGN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();