Macrogenics (MGNX) Operating Expenses (2012 - 2026)
Macrogenics (MGNX) recorded Operating Expenses of $46.68 million in Q2 2026, down 6.8% from $50.09 million a year earlier and down 13.9% from the prior quarter.
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Analysis
Macrogenics (MGNX) Operating Expenses (2012 - 2026) Analysis & Trends
On a TTM basis, Macrogenics' Operating Expenses came in at $208.43 million as of Jun 30, 2026, down 11.2% year-over-year; for FY2025, it came in at $222.34 million, down 14.7% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -1.2% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $260.54 million in FY2024 (+14.8%), $226.99 million in FY2023 (-17.0%), $273.36 million in FY2022 (-2.5%) and $280.24 million in FY2021 (+18.8%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q3 2023.
- On a year-over-year basis, Operating Expenses has declined for six consecutive quarters, with an average decline of 4.4% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 31.9% in Q4 2021, against a decline of 31.2% in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $54.21 million (Q1 2026), $53.32 million (Q4 2025) and $54.2 million (Q3 2025).
Peer Set
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 | Macrogenics | 258.40 Mn | -59.37 Mn | - | 46.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.68 Mn |
| Mar 31, 2026 | 54.21 Mn |
| Dec 31, 2025 | 53.32 Mn |
| Sep 30, 2025 | 54.20 Mn |
| Jun 30, 2025 | 50.09 Mn |
| Mar 31, 2025 | 55.82 Mn |
| Dec 31, 2024 | 72.19 Mn |
| Sep 30, 2024 | 56.52 Mn |
| Jun 30, 2024 | 68.98 Mn |
| Mar 31, 2024 | 62.85 Mn |
| Dec 31, 2023 | 60.07 Mn |
| Sep 30, 2023 | 45.90 Mn |
| Jun 30, 2023 | 58.10 Mn |
| Mar 31, 2023 | 62.92 Mn |
| Dec 31, 2022 | 61.12 Mn |
| Sep 30, 2022 | 66.69 Mn |
| Jun 30, 2022 | 67.82 Mn |
| Mar 31, 2022 | 77.74 Mn |
| Dec 31, 2021 | 72.38 Mn |
| Sep 30, 2021 | 68.65 Mn |
API Access
Macrogenics 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=MGNX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MGNX", "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=MGNX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();