Precision Biosciences (DTIL) Total Non-Current Liabilities (2018 - 2026)
Precision Biosciences' Total Non-Current Liabilities was $43.93 million in fiscal Q2 2026 (quarter ended Jun 30, 2026), down 32.3% from $64.87 million a year earlier and down 2.3% from the prior quarter.
Precision Biosciences (DTIL) Total Non-Current Liabilities (2018 - 2026) Analysis & Trends
At the end of FY2025 (ended Dec 31, 2025), Total Non-Current Liabilities at Precision Biosciences came in at $46.47 million, down 33.6% from FY2024.
- Total Non-Current Liabilities has now declined for three consecutive fiscal years, with a five-year compound annual growth rate of -15.1% (FY2020 to FY2025).
- In earlier fiscal years, Total Non-Current Liabilities was $70 million in FY2024 (-46.5%), $130.92 million in FY2023 (-21.9%), $167.74 million in FY2022 (+52.0%) and $110.33 million in FY2021 (+4.7%).
- The fiscal Q2 2026 figure marks the lowest quarterly Total Non-Current Liabilities in data going back to fiscal Q4 2018.
- Compared with a year earlier, Total Non-Current Liabilities has declined for 13 straight quarters, with an average decline of 32.4% over the last eight quarters.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was fiscal Q2 2022 (growth of 54.0%); the worst was fiscal Q1 2022 (a decline of 49.9%).
- Per Business Quant data, DTIL's Total Non-Current Liabilities in the three fiscal quarters before Q2 2026 was $44.99 million (Q1 2026), $46.47 million (Q4 2025) and $66.88 million (Q3 2025).
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 | Precision Biosciences | 165.47 Mn | -183.71 Mn | - | 43.93 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 43.93 Mn |
| Mar 31, 2026 | 44.99 Mn |
| Dec 31, 2025 | 46.47 Mn |
| Sep 30, 2025 | 66.88 Mn |
| Jun 30, 2025 | 64.87 Mn |
| Mar 31, 2025 | 65.07 Mn |
| Dec 31, 2024 | 70.00 Mn |
| Sep 30, 2024 | 77.78 Mn |
| Jun 30, 2024 | 76.83 Mn |
| Mar 31, 2024 | 125.52 Mn |
| Dec 31, 2023 | 130.92 Mn |
| Sep 30, 2023 | 125.28 Mn |
| Jun 30, 2023 | 137.66 Mn |
| Mar 31, 2023 | 154.33 Mn |
| Dec 31, 2022 | 167.74 Mn |
| Sep 30, 2022 | 177.35 Mn |
| Jun 30, 2022 | 184.14 Mn |
| Mar 31, 2022 | 101.69 Mn |
| Dec 31, 2021 | 110.33 Mn |
| Sep 30, 2021 | 115.76 Mn |
Precision Biosciences 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=DTIL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "DTIL", "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=DTIL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();