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APELLIS PHARMACEUTICALS, INC.: filings

Every APELLIS PHARMACEUTICALS, INC. annual and quarterly report in the SEC record with the published financial measures it tagged, 36 filings, each linked to its SEC index.

Filings with published measures

Each page shows what one filing reported, as tagged in that filing, with the periods it covered. Later filings can restate a value; the company overview shows the latest-filed value per period.

FormFiledFiscal periodMeasuresFactsSEC accession
10-Q2026-05-07fiscal Q1 202646950001492422-26-000108
10-K2026-02-24fiscal FY 2025501340001193125-26-065179
10-Q2025-10-30fiscal Q3 2025451330001193125-25-257374
10-Q2025-07-31fiscal Q2 2025451290000950170-25-100545
10-Q2025-05-07fiscal Q1 202545950000950170-25-064976
10-K2025-02-28fiscal FY 2024491300000950170-25-029507
10-Q2024-11-05fiscal Q3 2024481390000950170-24-121062
10-Q2024-08-01fiscal Q2 2024481340000950170-24-088938
10-Q2024-05-07fiscal Q1 202448990000950170-24-053921
10-K/A2024-02-29fiscal FY 2023491280000950170-24-023256
10-K2024-02-27fiscal FY 2023491280000950170-24-020614
10-Q2023-11-01fiscal Q3 2023491370000950170-23-057117
10-Q2023-07-31fiscal Q2 2023491330000950170-23-035935
10-Q2023-05-04fiscal Q1 202349990000950170-23-017819
10-K2023-02-21fiscal FY 2022491290000950170-23-003438
10-Q2022-11-07fiscal Q3 2022481340000950170-22-022606
10-Q2022-08-08fiscal Q2 2022481300000950170-22-015500
10-Q2022-05-04fiscal Q1 202243860000950170-22-007374
10-K2022-02-28fiscal FY 2021431070001564590-22-007606
10-Q2021-11-08fiscal Q3 2021421130001564590-21-055235
10-Q2021-08-09fiscal Q2 2021421090001564590-21-042601
10-Q2021-04-28fiscal Q1 202136760001564590-21-021318
10-K2021-02-25fiscal FY 2020421230001564590-21-008800
10-Q2020-11-02fiscal Q3 2020381070001564590-20-049423
10-Q2020-07-30fiscal Q2 202036970001564590-20-034763
10-Q2020-04-29fiscal Q1 202036770001564590-20-019689
10-K2020-02-27fiscal FY 2019371020001564590-20-007350
10-Q2019-11-05fiscal Q3 201937960001564590-19-040063
10-Q2019-07-31fiscal Q2 201937880001564590-19-027462
10-Q2019-05-07fiscal Q1 201937710001564590-19-016638
10-K2019-02-26fiscal FY 201829880001564590-19-004492
10-Q2018-11-13fiscal Q3 201828670001564590-18-029127
10-Q2018-07-31fiscal Q2 201825590001564590-18-018096
10-Q2018-04-30fiscal Q1 201821430001564590-18-009791
10-K2018-03-19fiscal FY 201721660001564590-18-006193
10-Q2017-12-20fiscal Q3 201720520001193125-17-374199

Inspect the source

Entity
APELLIS PHARMACEUTICALS, INC. / CIK 0001492422
Captured
2026-09-21T17:19:23.869Z
SEC response SHA-256
d855a4e81b3da8707e343214abe406f3014a2ed6d4ac72156c893608477710a5

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

Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.

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/0001492422.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"])))