Q32 Bio (QTTB) Total Non-Current Liabilities (2017 - 2026)
Q32 Bio (QTTB) posted Total Non-Current Liabilities of $9.96 million for Q2 2026, down 57.3% from $23.35 million a year earlier and down 42.6% from the prior quarter.
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Analysis
Q32 Bio (QTTB) Total Non-Current Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2025, Q32 Bio's Total Non-Current Liabilities came in at $19.76 million, down 37.6% from FY2024.
- Annual Total Non-Current Liabilities shows a three-year compound annual growth rate of -19.4% (FY2022 to FY2025).
- In prior years, Q32 Bio's Total Non-Current Liabilities was $31.66 million in FY2024 (-26.1%), $42.84 million in FY2023 (+13.6%) and $37.72 million in FY2022.
- The Q2 2026 figure stands as the lowest quarterly Total Non-Current Liabilities in data going back to Q4 2017.
- On a year-over-year basis, Total Non-Current Liabilities has declined in each of the last seven quarters, with an average decline of 38.3% over the last seven quarters.
- The strongest year-over-year quarter for Total Non-Current Liabilities in the past five years was Q4 2023, with growth of 13.6%; the weakest was Q2 2026, with a decline of 57.3%.
- According to Business Quant data, Total Non-Current Liabilities for the three prior quarters was $17.36 million (Q1 2026), $19.76 million (Q4 2025) and $21.23 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn | 105.99 Bn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn | 106.45 Bn |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn | 80.25 Bn |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn | 48.34 Bn |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn | -967.00 Mn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn | 81.11 Bn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn | 36.04 Bn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn | 100.86 Bn |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn | 5.92 Bn |
| 10 | Q32 Bio | 196.30 Mn | -77.99 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 | 21.23 Mn |
| Jun 30, 2025 | 23.35 Mn |
| Mar 31, 2025 | 28.09 Mn |
| Dec 31, 2024 | 31.66 Mn |
| Sep 30, 2024 | 31.25 Mn |
| Jun 30, 2024 | 35.70 Mn |
| Mar 31, 2024 | 48.45 Mn |
| Dec 31, 2023 | 42.84 Mn |
| Dec 31, 2022 | 37.72 Mn |
| Dec 31, 2019 | 42.52 Mn |
| Sep 30, 2019 | 49.05 Mn |
| Jun 30, 2019 | 46.09 Mn |
| Mar 31, 2019 | 48.17 Mn |
| Dec 31, 2018 | 53.27 Mn |
| Sep 30, 2018 | 46.90 Mn |
| Jun 30, 2018 | 39.85 Mn |
| Mar 31, 2018 | 176.74 Mn |
API Access
Q32 Bio Total Non-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-non-current-liabilities&ticker=QTTB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-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-non-current-liabilities&ticker=QTTB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();