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NEUROCRINE BIOSCIENCES INC: current assets

Current assets for NEUROCRINE BIOSCIENCES INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NEUROCRINE BIOSCIENCES INC financial histories

What this measure means

Assets classified as current under the normal operating cycle or one-year boundary. Not all current assets can be converted immediately into cash.

Exact concept: us-gaap:AssetsCurrent. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Current assets in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2025-12-312,522,700,000USD2026-02-1110-K · 0000914475-26-000007
At date2024-12-311,724,700,000USD2026-02-1110-K · 0000914475-26-000007
At date2023-12-311,607,000,000USD2025-02-1010-K · 0000914475-25-000037
At date2022-12-311,453,500,000USD2024-02-0910-K · 0000914475-24-000054
At date2021-12-31972,800,000USD2023-02-0910-K · 0000914475-23-000011
At date2020-12-311,016,200,000USD2022-02-1110-K · 0000914475-22-000013
At date2019-12-31831,000,000USD2021-02-0510-K · 0000914475-21-000020
At date2018-12-31737,777,000USD2020-02-0710-K · 0001564590-20-003773
At date2017-12-31554,919,000USD2019-02-0810-K · 0001564590-19-002328
At date2016-12-31310,442,000USD2018-02-1310-K · 0001193125-18-042794
At date2015-12-31384,074,000USD2017-02-1410-K · 0001193125-17-043838
At date2014-12-31198,203,000USD2016-02-1110-K · 0001193125-16-459862
At date2013-12-31148,462,000USD2015-02-0910-K · 0001193125-15-039176
At date2012-12-31189,264,000USD2014-02-1110-K · 0001193125-14-045619
At date2011-12-31132,476,000USD2013-02-0810-K · 0001193125-13-045687
At date2010-12-31133,051,000USD2012-02-0910-K · 0001193125-12-048679

Related financial histories

Inspect the source

Entity
NEUROCRINE BIOSCIENCES INC / CIK 0000914475
Captured
2026-09-20T05:07:04.284Z
SEC response SHA-256
7e9732999d54c7ad0c4b2ed55776e124744b1ccfe4813cfa38325dcda176702c

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000914475.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))