Macrogenics (MGNX) Interest Expenses (2023 - 2026)
Macrogenics (MGNX) recorded Interest Expenses of $4.4 million in Q2 2026, up 448.1% from $802,000 a year earlier but down 10.1% from the prior quarter.
Macrogenics (MGNX) Interest Expenses (2023 - 2026) Analysis & Trends
On a TTM basis, Macrogenics' Interest Expenses came in at $16.9 million as of Jun 30, 2026; for FY2025, it was $8.51 million, up 663.0% from FY2024.
- Across earlier years, Interest Expenses came in at $1.12 million in FY2024 (-22.0%) and $1.43 million in FY2023.
- Quarterly Interest Expenses has ranged from -$24,000 in Q4 2024 to $4.89 million in Q1 2026 over the past five years.
- Per Business Quant, the preceding three quarters came in at $4.89 million (Q1 2026), $4.27 million (Q4 2025) and $3.34 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn | 281.00 Mn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn | - |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn | - |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn | -462.00 Mn |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn | -435.00 Mn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn | 673.00 Mn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn | 247.00 Mn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn | - |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn | - |
| 10 | Macrogenics | 245.67 Mn | -72.10 Mn | - | 4.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.40 Mn |
| Mar 31, 2026 | 4.89 Mn |
| Dec 31, 2025 | 4.27 Mn |
| Sep 30, 2025 | 3.34 Mn |
| Jun 30, 2025 | 802,000.00 |
| Mar 31, 2025 | 91,000.00 |
| Dec 31, 2024 | -24,000.00 |
| Jun 30, 2024 | 6,000.00 |
| Mar 31, 2024 | 1.13 Mn |
| Jun 30, 2023 | 774,000.00 |
| Mar 31, 2023 | 656,000.00 |
Macrogenics Interest 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=interest-expenses&ticker=MGNX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-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=interest-expenses&ticker=MGNX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();