Neurocrine Biosciences (NBIX) Change in Accured Expenses (2010 - 2026)
Neurocrine Biosciences (NBIX) recorded Change in Accured Expenses of -$8.5 million in Q2 2026, compared with $15.1 million a year earlier.
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Analysis
Neurocrine Biosciences (NBIX) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Neurocrine Biosciences' Change in Accured Expenses came in at $125.3 million as of Jun 30, 2026, down 6.2% year-over-year; for FY2025, it came in at $160.2 million, up 269.1% from FY2024.
- Annual Change in Accured Expenses has a five-year compound annual growth rate of 42.9% (FY2020 to FY2025).
- Across earlier years, Change in Accured Expenses came in at $43.4 million in FY2024 (-11.4%), $49 million in FY2023 (-57.2%), $114.6 million in FY2022 (+101.8%) and $56.8 million in FY2021 (+111.2%).
- Quarterly Change in Accured Expenses has ranged from -$98.3 million in Q4 2023 to $124.4 million in Q3 2023 over the past five years.
- Peak year-over-year performance for Change in Accured Expenses in the last five years was growth of 279.3% in Q3 2023, against a decline of 73.8% in Q3 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at -$14.3 million (Q1 2026), $76.5 million (Q4 2025) and $71.6 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,076.25 Bn | 1,044.84 Bn | 19.71 Bn | - |
| 2 | Johnson & Johnson | 617.18 Bn | 535.70 Bn | 17.26 Bn | 2.96 Bn |
| 3 | AbbVie | 464.58 Bn | 437.73 Bn | 12.70 Bn | 1.20 Bn |
| 4 | Merck | 356.04 Bn | 310.47 Bn | 12.21 Bn | - |
| 5 | Novartis Ag | 269.07 Bn | 224.94 Bn | 11.24 Bn | -251.00 Mn |
| 6 | Astrazeneca | 243.21 Bn | 216.77 Bn | 12.86 Bn | - |
| 7 | Amgen | 217.88 Bn | 173.28 Bn | 7.24 Bn | 901.00 Mn |
| 8 | Gilead Sciences | 179.62 Bn | 153.74 Bn | 6.22 Bn | 338.00 Mn |
| 9 | Pfizer | 158.45 Bn | 105.40 Bn | 10.94 Bn | - |
| 10 | Neurocrine Biosciences | 14.55 Bn | 10.25 Bn | 935.80 Mn | -8.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -8.50 Mn |
| Mar 31, 2026 | -14.30 Mn |
| Dec 31, 2025 | 76.50 Mn |
| Sep 30, 2025 | 71.60 Mn |
| Jun 30, 2025 | 15.10 Mn |
| Mar 31, 2025 | -3.00 Mn |
| Dec 31, 2024 | 77.30 Mn |
| Sep 30, 2024 | 44.20 Mn |
| Jun 30, 2024 | -59.50 Mn |
| Mar 31, 2024 | -18.60 Mn |
| Dec 31, 2023 | -98.30 Mn |
| Sep 30, 2023 | 124.40 Mn |
| Jun 30, 2023 | 16.20 Mn |
| Mar 31, 2023 | 6.70 Mn |
| Dec 31, 2022 | 37.60 Mn |
| Sep 30, 2022 | 32.80 Mn |
| Jun 30, 2022 | 32.70 Mn |
| Mar 31, 2022 | 11.50 Mn |
| Dec 31, 2021 | 19.10 Mn |
| Sep 30, 2021 | 8.70 Mn |
API Access
Neurocrine Biosciences Change in Accured 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=change-in-accured-expenses&ticker=NBIX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "NBIX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=NBIX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();