Atea Pharmaceuticals (AVIR) Total Liabilities (2019 - 2026)
Atea Pharmaceuticals (AVIR) reported Total Liabilities of $28.12 million for Q2 2026, up 3.4% from $27.19 million a year earlier but down 15.7% from the prior quarter.
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Analysis
Atea Pharmaceuticals (AVIR) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Atea Pharmaceuticals posted Total Liabilities of $39.78 million, up 54.2% from FY2024.
- Total Liabilities has a five-year compound annual growth rate of -33.9% (FY2020 to FY2025).
- By year, Total Liabilities came in at $25.8 million in FY2024 (-35.1%), $39.78 million in FY2023 (+52.2%), $26.14 million in FY2022 (-58.4%) and $62.82 million in FY2021 (-80.1%).
- Five-year quarterly Total Liabilities spans a low of $19.95 million in Q1 2023 and a high of $262.05 million in Q3 2021.
- Year over year, Total Liabilities has now increased in each of the last three quarters, with an average decline of 1.9% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q1 2024 (growth of 143.9%); the low point was Q3 2022 (a decline of 91.1%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $33.37 million (Q1 2026), $39.78 million (Q4 2025) and $27.18 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Atea Pharmaceuticals | 417.06 Mn | 417.06 Mn | - | 28.12 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 28.12 Mn |
| Mar 31, 2026 | 33.37 Mn |
| Dec 31, 2025 | 39.78 Mn |
| Sep 30, 2025 | 27.18 Mn |
| Jun 30, 2025 | 27.19 Mn |
| Mar 31, 2025 | 28.88 Mn |
| Dec 31, 2024 | 25.80 Mn |
| Sep 30, 2024 | 32.44 Mn |
| Jun 30, 2024 | 33.91 Mn |
| Mar 31, 2024 | 48.66 Mn |
| Dec 31, 2023 | 39.78 Mn |
| Sep 30, 2023 | 26.35 Mn |
| Jun 30, 2023 | 23.68 Mn |
| Mar 31, 2023 | 19.95 Mn |
| Dec 31, 2022 | 26.14 Mn |
| Sep 30, 2022 | 23.39 Mn |
| Jun 30, 2022 | 33.88 Mn |
| Mar 31, 2022 | 37.31 Mn |
| Dec 31, 2021 | 62.82 Mn |
| Sep 30, 2021 | 262.05 Mn |
API Access
Atea Pharmaceuticals Total 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-liabilities&ticker=AVIR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "AVIR", "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-liabilities&ticker=AVIR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();