Precision Biosciences (DTIL) Total Liabilities (2018 - 2026)
Precision Biosciences (DTIL) reported Total Liabilities of $80.63 million for fiscal Q2 2026 (quarter ended Jun 30, 2026), up 7.7% from $74.87 million a year earlier and up 18.9% from the prior quarter.
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Analysis
Precision Biosciences (DTIL) Total Liabilities (2018 - 2026) Analysis & Trends
At the end of FY2025 (ended Dec 31, 2025), Precision Biosciences posted Total Liabilities of $62.17 million, down 22.3% from FY2024.
- Total Liabilities has declined for three consecutive fiscal years, with a five-year compound annual growth rate of -10.1% (FY2020 to FY2025).
- By fiscal year, Total Liabilities came in at $80 million in FY2024 (-43.2%), $140.92 million in FY2023 (-20.7%), $177.74 million in FY2022 (+47.7%) and $120.33 million in FY2021 (+13.8%).
- The fiscal Q2 2026 figure ranks as the highest quarterly Total Liabilities since fiscal Q3 2024.
- Year over year, Total Liabilities gained in 1 of the last eight quarters, with an average decline of 22.8%.
- The high point for year-over-year Total Liabilities in five years was fiscal Q2 2022 (growth of 49.8%); the low point was fiscal Q1 2025 (a decline of 49.1%).
- Per Business Quant data, the three fiscal quarters before Q2 2026 came in at $67.79 million (Q1 2026), $62.17 million (Q4 2025) and $76.88 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Precision Biosciences | 165.47 Mn | -183.71 Mn | - | 80.63 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.63 Mn |
| Mar 31, 2026 | 67.79 Mn |
| Dec 31, 2025 | 62.17 Mn |
| Sep 30, 2025 | 76.88 Mn |
| Jun 30, 2025 | 74.87 Mn |
| Mar 31, 2025 | 75.07 Mn |
| Dec 31, 2024 | 80.00 Mn |
| Sep 30, 2024 | 88.39 Mn |
| Jun 30, 2024 | 91.09 Mn |
| Mar 31, 2024 | 147.54 Mn |
| Dec 31, 2023 | 140.92 Mn |
| Sep 30, 2023 | 135.28 Mn |
| Jun 30, 2023 | 147.66 Mn |
| Mar 31, 2023 | 164.33 Mn |
| Dec 31, 2022 | 177.74 Mn |
| Sep 30, 2022 | 187.35 Mn |
| Jun 30, 2022 | 194.14 Mn |
| Mar 31, 2022 | 111.69 Mn |
| Dec 31, 2021 | 120.33 Mn |
| Sep 30, 2021 | 125.76 Mn |
API Access
Precision 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=DTIL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=DTIL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();