Enveric Biosciences, Inc.: selling, general and administrative expense
Enveric Biosciences selling, general and administrative expense: $20.5 million for the year ending 2021-12-31, up 285.1% on the year. 6 values since 2016.
All Enveric Biosciences, Inc. financial histories
At a glance
Enveric Biosciences reported selling, general and administrative expense of $20.5 million for the year ending 2021-12-31, up 285.1% from $5.32 million a year earlier. From 2016 to 2021 it grew at a compound 17.0% a year, from $9.36 million to $20.5 million. Across the last five reported years it ranged from $2.30 million (2019-12-31) to $20.5 million (2021-12-31).
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.
Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. 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 2016-01-01 to 2021-12-31. The SEC response was captured on 2026-09-20.
This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2021-01-01 | 2021-12-31 | 20,499,052 | USD | 2022-03-31 | 10-K · 0001493152-22-008510 SEC |
| 2020-01-01 | 2020-12-31 | 5,322,362 | USD | 2022-03-31 | 10-K · 0001493152-22-008510 SEC |
| 2019-01-01 | 2019-12-31 | 2,296,534 | USD | 2021-04-01 | 10-K · 0001493152-21-007757 SEC |
| 2018-01-01 | 2018-12-31 | 10,794,822 | USD | 2020-08-12 | 10-K/A · 0001493152-20-015385 SEC |
| 2017-01-01 | 2017-12-31 | 18,510,120 | USD | 2019-03-26 | 10-K · 0001140361-19-005573 SEC |
| 2016-01-01 | 2016-12-31 | 9,361,961 | USD | 2018-04-02 | 10-K · 0001140361-18-016275 SEC |
Related ENVERIC BIOSCIENCES, INC. histories
Inspect the source
- Entity
- ENVERIC BIOSCIENCES, INC. / CIK 0000890821
- Captured
- SEC response SHA-256
ed23dbf99f9ce404ef7949b5b1b4b3a643f25caca94a6c8cd8444309157de101
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.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000890821.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"])))