4D Molecular Therapeutics (FDMT) Operating Expenses (2020 - 2026)
4D Molecular Therapeutics (FDMT) posted Operating Expenses of $80.81 million for Q2 2026, up 35.9% from $59.47 million a year earlier and up 5.4% from the prior quarter.
4D Molecular Therapeutics (FDMT) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at 4D Molecular Therapeutics was $289.12 million, up 31.2% year-over-year; for FY2025, it came in at $244.76 million, up 30.3% from FY2024.
- Annual Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 28.3% (FY2020 to FY2025).
- In prior years, 4D Molecular Therapeutics' Operating Expenses was $187.88 million in FY2024 (+40.6%), $133.59 million in FY2023 (+18.1%), $113.16 million in FY2022 (+26.6%) and $89.37 million in FY2021 (+27.2%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q1 2020.
- On a year-over-year basis, Operating Expenses has increased in each of the last 22 quarters, with growth averaging 38.4% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 10.1% (Q1 2023) and 57.7% (Q3 2021) over the last five years.
- According to Business Quant data, Operating Expenses for the three prior quarters was $76.67 million (Q1 2026), $70.38 million (Q4 2025) and $61.28 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 | 4D Molecular Therapeutics | 1.02 Bn | -436.78 Mn | - | 80.81 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.81 Mn |
| Mar 31, 2026 | 76.67 Mn |
| Dec 31, 2025 | 70.38 Mn |
| Sep 30, 2025 | 61.28 Mn |
| Jun 30, 2025 | 59.47 Mn |
| Mar 31, 2025 | 53.64 Mn |
| Dec 31, 2024 | 56.12 Mn |
| Sep 30, 2024 | 51.14 Mn |
| Jun 30, 2024 | 42.46 Mn |
| Mar 31, 2024 | 38.16 Mn |
| Dec 31, 2023 | 36.63 Mn |
| Sep 30, 2023 | 34.18 Mn |
| Jun 30, 2023 | 32.38 Mn |
| Mar 31, 2023 | 30.40 Mn |
| Dec 31, 2022 | 29.97 Mn |
| Sep 30, 2022 | 27.00 Mn |
| Jun 30, 2022 | 28.59 Mn |
| Mar 31, 2022 | 27.61 Mn |
| Dec 31, 2021 | 24.86 Mn |
| Sep 30, 2021 | 24.03 Mn |
4D Molecular 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=FDMT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FDMT", "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=FDMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();