Pharming (PHAR) Total Current Liabilities (2019 - 2026)
Pharming (PHAR) reported Total Current Liabilities of $93.25 million for Q2 2026, up 6.0% from $87.94 million a year earlier but down 17.0% from the prior quarter.
Pharming (PHAR) Total Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Pharming posted Total Current Liabilities of $115.79 million, up 56.9% from FY2024.
- Total Current Liabilities has a five-year compound annual growth rate of 8.5% (FY2020 to FY2025).
- By year, Total Current Liabilities came in at $73.8 million in FY2024 (-5.3%), $77.97 million in FY2023 (+30.6%), $59.7 million in FY2022 (+27.6%) and $46.77 million in FY2021 (-39.1%).
- Five-year quarterly Total Current Liabilities spans a low of $46,694 in Q3 2022 and a high of $207.29 million in Q1 2024.
- Year over year, Total Current Liabilities has now increased in each of the last five quarters, with growth averaging 9.7% over the last eight quarters.
- The high point for year-over-year Total Current Liabilities in five years was Q1 2024 (growth of 251.3%); the low point was Q4 2021 (a decline of 99.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $112.35 million (Q1 2026), $115.79 million (Q4 2025) and $87.91 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 54.90 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 41.64 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 27.73 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 31.75 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -31.55 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 25.50 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 11.02 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 32.65 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 3.94 Bn |
| 10 | Pharming | 738.17 Mn | -91.99 Mn | 141.47 Mn | 93.25 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 93.25 Mn |
| Mar 31, 2026 | 112.35 Mn |
| Dec 31, 2025 | 115.79 Mn |
| Sep 30, 2025 | 87.91 Mn |
| Jun 30, 2025 | 87.94 Mn |
| Mar 31, 2025 | 77.54 Mn |
| Dec 31, 2024 | 73.80 Mn |
| Sep 30, 2024 | 79.84 Mn |
| Jun 30, 2024 | 79.94 Mn |
| Mar 31, 2024 | 207.29 Mn |
| Dec 31, 2023 | 77.97 Mn |
| Sep 30, 2023 | 68.06 Mn |
| Jun 30, 2023 | 64.95 Mn |
| Mar 31, 2023 | 59.00 Mn |
| Dec 31, 2022 | 59.70 Mn |
| Sep 30, 2022 | 46,694.00 |
| Jun 30, 2022 | 49.19 Mn |
| Mar 31, 2022 | 45.15 Mn |
| Dec 31, 2021 | 47,205.96 |
| Sep 30, 2021 | 46.72 Mn |
Pharming Total Current Liabilities 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=total-current-liabilities&ticker=PHAR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "PHAR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-current-liabilities&ticker=PHAR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();