Precision Biosciences (DTIL) Other Accumulated Expenses (2019 - 2026)
Precision Biosciences' Other Accumulated Expenses was $588,000 in fiscal Q2 2026 (quarter ended Jun 30, 2026), down 18.4% from $721,000 a year earlier and down 31.5% from the prior quarter.
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Analysis
Precision Biosciences (DTIL) Other Accumulated Expenses (2019 - 2026) Analysis & Trends
At the end of FY2025 (ended Dec 31, 2025), Other Accumulated Expenses at Precision Biosciences came in at $649,000, down 34.4% from FY2024.
- Other Accumulated Expenses shows a five-year compound annual growth rate of -5.3% (FY2020 to FY2025).
- In earlier fiscal years, Other Accumulated Expenses was $989,000 in FY2024 (-58.6%), $2.39 million in FY2023 (+220.9%), $745,000 in FY2022 (-23.7%) and $977,000 in FY2021 (+14.4%).
- The fiscal Q2 2026 figure marks the lowest quarterly Other Accumulated Expenses in data going back to fiscal Q4 2019.
- Compared with a year earlier, Other Accumulated Expenses has declined for eight straight quarters, with an average decline of 40.8% over the last eight quarters.
- The best year-over-year quarter for Other Accumulated Expenses over five years was fiscal Q4 2023 (growth of 220.9%); the worst was fiscal Q1 2025 (a decline of 67.7%).
- Per Business Quant data, DTIL's Other Accumulated Expenses in the three fiscal quarters before Q2 2026 was $858,000 (Q1 2026), $649,000 (Q4 2025) and $611,000 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Eli Lilly | 1,076.25 Bn | 1,044.84 Bn | 19.71 Bn |
| 2 | Johnson & Johnson | 617.18 Bn | 535.70 Bn | 17.26 Bn |
| 3 | AbbVie | 464.58 Bn | 437.73 Bn | 12.70 Bn |
| 4 | Merck | 356.04 Bn | 310.47 Bn | 12.21 Bn |
| 5 | Novartis Ag | 269.07 Bn | 224.94 Bn | 11.24 Bn |
| 6 | Astrazeneca | 243.21 Bn | 216.77 Bn | 12.86 Bn |
| 7 | Amgen | 217.88 Bn | 173.28 Bn | 7.24 Bn |
| 8 | Gilead Sciences | 179.62 Bn | 153.74 Bn | 6.22 Bn |
| 9 | Pfizer | 158.45 Bn | 105.40 Bn | 10.94 Bn |
| 10 | Precision Biosciences | 166.80 Mn | -182.39 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 588,000.00 |
| Mar 31, 2026 | 858,000.00 |
| Dec 31, 2025 | 649,000.00 |
| Sep 30, 2025 | 611,000.00 |
| Jun 30, 2025 | 721,000.00 |
| Mar 31, 2025 | 896,000.00 |
| Dec 31, 2024 | 989,000.00 |
| Sep 30, 2024 | 1.39 Mn |
| Jun 30, 2024 | 1.92 Mn |
| Mar 31, 2024 | 2.77 Mn |
| Dec 31, 2023 | 2.39 Mn |
| Sep 30, 2023 | 1.85 Mn |
| Jun 30, 2023 | 1.21 Mn |
| Mar 31, 2023 | 1.41 Mn |
| Dec 31, 2022 | 745,000.00 |
| Sep 30, 2022 | 1.23 Mn |
| Jun 30, 2022 | 1.45 Mn |
| Mar 31, 2022 | 1.62 Mn |
| Dec 31, 2021 | 977,000.00 |
| Sep 30, 2021 | 1.88 Mn |
API Access
Precision Biosciences Other Accumulated Expenses 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=other-accumulated-expenses&ticker=DTIL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "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=other-accumulated-expenses&ticker=DTIL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();