Aura Biosciences (AURA) Total Liabilities (2020 - 2026)
Aura Biosciences' Total Liabilities came in at $32.86 million for Q2 2026, up 10.4% from $29.77 million a year earlier and up 8.0% from the prior quarter.
Aura Biosciences (AURA) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Aura Biosciences' Total Liabilities was $32.52 million, up 6.5% from FY2024.
- Total Liabilities has increased in each of the last four years, though with a five-year compound annual growth rate of -24.3% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $30.53 million in FY2024 (+4.5%), $29.23 million in FY2023 (+3.1%), $28.35 million in FY2022 (+267.5%) and $7.72 million in FY2021 (-94.1%).
- The five-year range for quarterly Total Liabilities is $5.34 million (Q1 2022) to $221.72 million (Q3 2021).
- Year-over-year, Total Liabilities has increased for 11 consecutive quarters, with growth averaging 8.2% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2023 (growth of 382.8%), and the weakest in Q4 2021 (a decline of 94.1%).
- Business Quant data shows AURA's Total Liabilities at $30.43 million (Q1 2026), $32.52 million (Q4 2025) and $33.36 million (Q3 2025) in the three quarters before Q2 2026.
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 | Aura Biosciences | 636.40 Mn | 376.71 Mn | - | 32.86 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 32.86 Mn |
| Mar 31, 2026 | 30.43 Mn |
| Dec 31, 2025 | 32.52 Mn |
| Sep 30, 2025 | 33.36 Mn |
| Jun 30, 2025 | 29.77 Mn |
| Mar 31, 2025 | 27.44 Mn |
| Dec 31, 2024 | 30.53 Mn |
| Sep 30, 2024 | 30.67 Mn |
| Jun 30, 2024 | 26.83 Mn |
| Mar 31, 2024 | 26.24 Mn |
| Dec 31, 2023 | 29.23 Mn |
| Sep 30, 2023 | 28.05 Mn |
| Jun 30, 2023 | 26.30 Mn |
| Mar 31, 2023 | 25.76 Mn |
| Dec 31, 2022 | 28.35 Mn |
| Sep 30, 2022 | 28.09 Mn |
| Jun 30, 2022 | 5.93 Mn |
| Mar 31, 2022 | 5.34 Mn |
| Dec 31, 2021 | 7.72 Mn |
| Sep 30, 2021 | 221.72 Mn |
Aura Biosciences 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=AURA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "AURA", "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=AURA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();