Puma Biotechnology (PBYI) Non Operating Interest Expenses (2018 - 2026)
Puma Biotechnology (PBYI) recorded Non Operating Interest Expenses of $180,000 in Q2 2026, down 90.2% from $1.84 million a year earlier and down 75.4% from the prior quarter.
Puma Biotechnology (PBYI) Non Operating Interest Expenses (2018 - 2026) Analysis & Trends
On a TTM basis, Puma Biotechnology's Non Operating Interest Expenses came in at $3.52 million as of Jun 30, 2026, down 63.9% year-over-year; for FY2025, it came in at $6.62 million, down 46.8% from FY2024.
- Annual Non Operating Interest Expenses has a five-year compound annual growth rate of -14.0% (FY2020 to FY2025).
- Across earlier years, Non Operating Interest Expenses came in at $12.45 million in FY2024 (-6.6%), $13.33 million in FY2023 (+15.0%), $11.59 million in FY2022 (-9.5%) and $12.81 million in FY2021 (-8.8%).
- The Q2 2026 figure is the lowest quarterly Non Operating Interest Expenses in data going back to Q1 2018.
- On a year-over-year basis, Non Operating Interest Expenses has declined for eight consecutive quarters, with an average decline of 47.0% over the last eight quarters.
- Peak year-over-year performance for Non Operating Interest Expenses in the last five years was growth of 24.3% in Q1 2023, against a decline of 90.2% in Q2 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at $731,000 (Q1 2026), $1.12 million (Q4 2025) and $1.49 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,082.65 Bn | 1,051.23 Bn | 19.71 Bn | - |
| 2 | Johnson & Johnson | 623.68 Bn | 542.21 Bn | 17.26 Bn | 281.00 Mn |
| 3 | AbbVie | 459.43 Bn | 432.59 Bn | 12.70 Bn | - |
| 4 | Merck | 354.80 Bn | 309.23 Bn | 12.21 Bn | - |
| 5 | Novartis Ag | 269.16 Bn | 225.03 Bn | 11.24 Bn | -462.00 Mn |
| 6 | Astrazeneca | 244.40 Bn | 217.97 Bn | 12.86 Bn | -435.00 Mn |
| 7 | Amgen | 220.17 Bn | 175.57 Bn | 7.24 Bn | 673.00 Mn |
| 8 | Gilead Sciences | 183.05 Bn | 157.16 Bn | 6.22 Bn | 247.00 Mn |
| 9 | Pfizer | 160.27 Bn | 107.22 Bn | 10.94 Bn | - |
| 10 | Puma Biotechnology | 502.85 Mn | 115.49 Mn | 44.03 Mn | 180,000.00 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 180,000.00 |
| Mar 31, 2026 | 731,000.00 |
| Dec 31, 2025 | 1.12 Mn |
| Sep 30, 2025 | 1.49 Mn |
| Jun 30, 2025 | 1.84 Mn |
| Mar 31, 2025 | 2.18 Mn |
| Dec 31, 2024 | 2.62 Mn |
| Sep 30, 2024 | 3.10 Mn |
| Jun 30, 2024 | 3.37 Mn |
| Mar 31, 2024 | 3.36 Mn |
| Dec 31, 2023 | 3.35 Mn |
| Sep 30, 2023 | 3.34 Mn |
| Jun 30, 2023 | 3.33 Mn |
| Mar 31, 2023 | 3.31 Mn |
| Dec 31, 2022 | 3.28 Mn |
| Sep 30, 2022 | 2.95 Mn |
| Jun 30, 2022 | 2.70 Mn |
| Mar 31, 2022 | 2.66 Mn |
| Dec 31, 2021 | 2.72 Mn |
| Sep 30, 2021 | 3.12 Mn |
Puma Biotechnology Non Operating 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=non-operating-interest-expenses&ticker=PBYI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "PBYI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=PBYI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();