Q32 Bio (QTTB) Total Liabilities (2017 - 2026)
Q32 Bio's Total Liabilities was $9.96 million in Q2 2026, down 87.3% from $78.35 million a year earlier and down 42.6% from the prior quarter.
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Analysis
Q32 Bio (QTTB) Total Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Q32 Bio came in at $19.76 million, down 77.2% from FY2024.
- Total Liabilities has now declined for three consecutive years, with a five-year compound annual growth rate of -21.8% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $86.66 million in FY2024 (-62.3%), $229.98 million in FY2023 (-36.0%), $359.18 million in FY2022 (+753.8%) and $42.07 million in FY2021 (-37.9%).
- The Q2 2026 figure marks the lowest quarterly Total Liabilities in data going back to Q4 2017.
- Compared with a year earlier, Total Liabilities has declined for 11 straight quarters, with an average decline of 52.7% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2022 (growth of 753.8%); the worst was Q2 2026 (a decline of 87.3%).
- Per Business Quant data, QTTB's Total Liabilities in the three quarters before Q2 2026 was $17.36 million (Q1 2026), $19.76 million (Q4 2025) and $76.23 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 645.01 Bn | 563.54 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 465.23 Bn | 438.39 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 368.40 Bn | 322.83 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 278.02 Bn | 233.89 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 254.57 Bn | 228.13 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 229.02 Bn | 184.42 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 187.74 Bn | 161.85 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.45 Bn | 105.45 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Q32 Bio | 226.21 Mn | -48.08 Mn | - | 9.96 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.96 Mn |
| Mar 31, 2026 | 17.36 Mn |
| Dec 31, 2025 | 19.76 Mn |
| Sep 30, 2025 | 76.23 Mn |
| Jun 30, 2025 | 78.35 Mn |
| Mar 31, 2025 | 83.09 Mn |
| Dec 31, 2024 | 86.66 Mn |
| Sep 30, 2024 | 86.25 Mn |
| Jun 30, 2024 | 90.70 Mn |
| Mar 31, 2024 | 103.57 Mn |
| Dec 31, 2023 | 229.98 Mn |
| Sep 30, 2023 | 296.51 Mn |
| Jun 30, 2023 | 312.06 Mn |
| Mar 31, 2023 | 335.12 Mn |
| Dec 31, 2022 | 359.18 Mn |
| Sep 30, 2022 | 53.59 Mn |
| Jun 30, 2022 | 44.32 Mn |
| Mar 31, 2022 | 44.70 Mn |
| Dec 31, 2021 | 42.07 Mn |
| Sep 30, 2021 | 32.25 Mn |
API Access
Q32 Bio 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=QTTB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "QTTB", "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=QTTB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();