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Protalix BioTherapeutics, Inc.: interest expense

Protalix BioTherapeutics interest expense: $3.55 million for the year ending 2015-12-31, unchanged on the year. 3 values since 2013. In original units.

All Protalix BioTherapeutics, Inc. financial histories

At a glance

Protalix BioTherapeutics reported interest expense of $3.55 million for the year ending 2015-12-31, unchanged from a year earlier. Across the last three reported years it ranged from $1.01 million (2013-12-31) to $3.55 million (2014-12-31). That was 81.3% of revenue ($4.36 million) for the same year.

Computed from the values in the table below, in USD; each links to the filing it came from.

What this measure means

Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.

Exact concept: us-gaap:InterestExpense. 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 2013-01-01 to 2015-12-31. 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

Interest expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2015-01-012015-12-313,549,000USD2016-03-0810-K · 0001144204-16-086642 SEC
2014-01-012014-12-313,549,000USD2016-03-0810-K · 0001144204-16-086642 SEC
2013-01-012013-12-311,015,000USD2016-03-0810-K · 0001144204-16-086642 SEC

Related Protalix BioTherapeutics, Inc. histories

All 51 Protalix BioTherapeutics histories

Inspect the source

Entity
Protalix BioTherapeutics, Inc. / CIK 0001006281
Captured
SEC response SHA-256
5022eb9c9008f3ac21090b4bd34c0341e843ccbd807493dfa2a9e5fc19632a16

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.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

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

with urlopen("https://canlicapital.com/company-data/0001006281.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"])))