Armata Pharmaceuticals (ARMP) Total Current Liabilities (2013 - 2026)
Armata Pharmaceuticals' Total Current Liabilities came in at $250.2 million for Q2 2026, up 108.4% from $120.09 million a year earlier.
Armata Pharmaceuticals (ARMP) Total Current Liabilities (2013 - 2026) Analysis & Trends
At the end of FY2025, Armata Pharmaceuticals' Total Current Liabilities was $8.95 million, down 81.5% from FY2024.
- Total Current Liabilities carries a five-year compound annual growth rate of 5.9% (FY2020 to FY2025).
- Going back by year, Total Current Liabilities was $48.25 million in FY2024 (+193.1%), $16.46 million in FY2023 (-33.8%), $24.87 million in FY2022 (+416.7%) and $4.81 million in FY2021 (-28.2%).
- The Q2 2026 figure represents the highest quarterly Total Current Liabilities in data going back to Q4 2013.
- Year-over-year, Total Current Liabilities increased in five of the last eight quarters, with growth averaging 73.1%.
- The fastest year-over-year change in Total Current Liabilities over five years came in Q1 2023 (growth of 725.8%), and the weakest in Q1 2026 (a decline of 91.7%).
- Business Quant data shows ARMP's Total Current Liabilities at $9.23 million (Q1 2026), $8.95 million (Q4 2025) and $139.95 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 645.01 Bn | 563.54 Bn | 17.26 Bn | 54.90 Bn |
| 2 | AbbVie | 465.23 Bn | 438.39 Bn | 12.70 Bn | 41.64 Bn |
| 3 | Merck | 368.40 Bn | 322.83 Bn | 12.21 Bn | 27.73 Bn |
| 4 | Novartis Ag | 278.02 Bn | 233.89 Bn | 11.24 Bn | 31.75 Bn |
| 5 | Astrazeneca | 254.57 Bn | 228.13 Bn | 12.86 Bn | -31.55 Bn |
| 6 | Amgen | 229.02 Bn | 184.42 Bn | 7.24 Bn | 25.50 Bn |
| 7 | Gilead Sciences | 187.74 Bn | 161.85 Bn | 6.22 Bn | 11.02 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 32.65 Bn |
| 9 | Vertex Pharmaceuticals | 133.45 Bn | 105.45 Bn | 2.84 Bn | 3.94 Bn |
| 10 | Armata Pharmaceuticals | 133.35 Mn | 81.07 Mn | - | 250.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 250.20 Mn |
| Mar 31, 2026 | 9.23 Mn |
| Dec 31, 2025 | 8.95 Mn |
| Sep 30, 2025 | 139.95 Mn |
| Jun 30, 2025 | 120.09 Mn |
| Mar 31, 2025 | 110.54 Mn |
| Dec 31, 2024 | 48.25 Mn |
| Sep 30, 2024 | 118.20 Mn |
| Jun 30, 2024 | 123.18 Mn |
| Mar 31, 2024 | 110.05 Mn |
| Dec 31, 2023 | 16.46 Mn |
| Sep 30, 2023 | 21.88 Mn |
| Jun 30, 2023 | 51.56 Mn |
| Mar 31, 2023 | 51.42 Mn |
| Dec 31, 2022 | 24.87 Mn |
| Sep 30, 2022 | 7.00 Mn |
| Jun 30, 2022 | 7.38 Mn |
| Mar 31, 2022 | 6.23 Mn |
| Dec 31, 2021 | 4.81 Mn |
| Sep 30, 2021 | 5.25 Mn |
Armata Pharmaceuticals 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=ARMP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "ARMP", "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=ARMP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();