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Arbutus Biopharma Corp: revenue

Revenue for Arbutus Biopharma Corp. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Arbutus Biopharma Corp financial histories

What this measure means

Revenue under this specific accounting concept. A missing value is not zero; filers can use other revenue concepts.

Exact concept: us-gaap:Revenues. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Coverage by original unit

These are separate reported series. A newer period in one unit does not update another unit’s history or establish a currency conversion.

Selected filing history

Revenue in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2012-01-012012-12-3114,107,478CAD2013-03-2720-F · 0001193125-13-129590
2011-01-012011-12-3116,646,943CAD2013-03-2720-F · 0001193125-13-129590
2010-01-012010-12-3121,354,739CAD2013-03-2720-F · 0001193125-13-129590
2009-01-012009-12-3114,428,416CAD2012-03-2720-F · 0001193125-12-134709
2025-01-012025-12-3114,083,000USD2026-03-2310-K · 0001447028-26-000017
2024-01-012024-12-316,171,000USD2026-03-2310-K · 0001447028-26-000017
2023-01-012023-12-3118,141,000USD2025-03-2710-K · 0001447028-25-000083
2022-01-012022-12-3139,019,000USD2024-03-0510-K · 0001447028-24-000035
2021-01-012021-12-3110,988,000USD2023-03-0210-K · 0001447028-23-000018
2020-01-012020-12-316,914,000USD2022-03-0310-K · 0001447028-22-000019
2019-01-012019-12-316,011,000USD2021-03-0410-K · 0001447028-21-000021
2018-01-012018-12-315,945,000USD2020-03-0510-K · 0001447028-20-000038
2017-01-012017-12-3110,700,000USD2019-03-0710-K · 0001447028-19-000006
2016-01-012016-12-311,491,000USD2018-03-1610-K · 0001628280-18-003276
2015-01-012015-12-3123,276,000USD2018-03-1610-K · 0001628280-18-003276
2014-01-012014-12-3114,953,000USD2017-03-2210-K · 0001628280-17-002760
2013-01-012013-12-3115,465,000USD2016-03-0910-K · 0001628280-16-012462
2012-01-012012-12-3114,105,000USD2015-03-1310-K · 0001171843-15-001398
2011-01-012011-12-3116,811,590USD2014-03-2810-K · 0001171843-14-001457

Related financial histories

Inspect the source

Entity
Arbutus Biopharma Corp / CIK 0001447028
Captured
2026-09-20T09:04:49.017Z
SEC response SHA-256
d0c406f420689ef604e97fe778a55d59191ec33b490a85e5747539352bb315a4

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/0001447028.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"])))