Greenwich LifeSciences (GLSI) Change in Accured Expenses (2019 - 2026)
Greenwich LifeSciences' Change in Accured Expenses was -$224,114 in Q1 2026, compared with $8,446 a year earlier.
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Analysis
Greenwich LifeSciences (GLSI) Change in Accured Expenses (2019 - 2026) Analysis & Trends
On a trailing twelve-month basis, Greenwich LifeSciences' Change in Accured Expenses was $134,978 through Mar 31, 2026, down 56.4% year-over-year; for FY2025, it came in at $367,538, up 20.0% from FY2024.
- Change in Accured Expenses shows a five-year compound annual growth rate of 38.1% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was $306,281 in FY2024, -$3,971 in FY2023, -$122,267 in FY2022 and $104,960 in FY2021 (+43.4%).
- The Q1 2026 figure marks the lowest quarterly Change in Accured Expenses in data going back to Q4 2019.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last four quarters, with growth averaging 45.4%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q3 2023 (growth of 646.7%); the worst was Q3 2022 (a decline of 86.2%).
- Per Business Quant data, GLSI's Change in Accured Expenses in the three quarters before Q1 2026 was $236,620 (Q4 2025), $123,982 (Q3 2025) and -$1,510 (Q2 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,076.25 Bn | 1,044.84 Bn | 19.71 Bn | - |
| 2 | Johnson & Johnson | 617.18 Bn | 535.70 Bn | 17.26 Bn | 2.96 Bn |
| 3 | AbbVie | 464.58 Bn | 437.73 Bn | 12.70 Bn | 1.20 Bn |
| 4 | Merck | 356.04 Bn | 310.47 Bn | 12.21 Bn | - |
| 5 | Novartis Ag | 269.07 Bn | 224.94 Bn | 11.24 Bn | -251.00 Mn |
| 6 | Astrazeneca | 243.21 Bn | 216.77 Bn | 12.86 Bn | - |
| 7 | Amgen | 217.88 Bn | 173.28 Bn | 7.24 Bn | 901.00 Mn |
| 8 | Gilead Sciences | 179.62 Bn | 153.74 Bn | 6.22 Bn | 338.00 Mn |
| 9 | Pfizer | 158.45 Bn | 105.40 Bn | 10.94 Bn | - |
| 10 | Greenwich LifeSciences | 249.03 Mn | 249.03 Mn | - | -224,114.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | -224,114.00 |
| Dec 31, 2025 | 236,620.00 |
| Sep 30, 2025 | 123,982.00 |
| Jun 30, 2025 | -1,510.00 |
| Mar 31, 2025 | 8,446.00 |
| Dec 31, 2024 | 276,745.00 |
| Sep 30, 2024 | 49,828.00 |
| Jun 30, 2024 | -25,232.00 |
| Mar 31, 2024 | 4,940.00 |
| Dec 31, 2023 | -28,296.00 |
| Sep 30, 2023 | 65,302.00 |
| Jun 30, 2023 | -13,647.00 |
| Mar 31, 2023 | -27,330.00 |
| Dec 31, 2022 | 25,026.00 |
| Sep 30, 2022 | 8,745.00 |
| Jun 30, 2022 | -12,034.00 |
| Mar 31, 2022 | -144,004.00 |
| Dec 31, 2021 | 5,053.00 |
| Sep 30, 2021 | 63,301.00 |
| Jun 30, 2021 | 18,303.00 |
API Access
Greenwich LifeSciences Change in Accured Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=GLSI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "GLSI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=GLSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();