Precision Biosciences (DTIL) Operating Expenses (2018 - 2026)
Precision Biosciences (DTIL) posted Operating Expenses of $19.16 million for fiscal Q2 2026 (quarter ended Jun 30, 2026), down 12.5% from $21.9 million a year earlier and down 3.8% from the prior quarter.
Precision Biosciences (DTIL) Operating Expenses (2018 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Precision Biosciences was $81.45 million, down 10.9% year-over-year; for FY2025 (ended Dec 31, 2025), it came in at $86.41 million, down 8.9% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of -8.4% (FY2020 to FY2025).
- In prior fiscal years, Precision Biosciences' Operating Expenses was $94.86 million in FY2024 (+2.6%), $92.46 million in FY2023 (+5.8%), $87.41 million in FY2022 (-43.6%) and $154.91 million in FY2021 (+15.5%).
- The fiscal Q2 2026 figure stands as the lowest quarterly Operating Expenses since fiscal Q3 2018.
- On a year-over-year basis, Operating Expenses has declined in each of the last five quarters, with an average decline of 6.8% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q4 2024, with growth of 16.2%; the weakest was fiscal Q4 2022, with a decline of 38.7%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $19.91 million (Q1 2026), $21.7 million (Q4 2025) and $20.68 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,167.71 Bn | 1,136.29 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 647.75 Bn | 567.61 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 503.60 Bn | 476.71 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 368.10 Bn | 322.48 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 303.19 Bn | 267.18 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 268.04 Bn | 241.73 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 242.69 Bn | 198.09 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 194.89 Bn | 169.09 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 173.31 Bn | 119.95 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Precision Biosciences | 173.76 Mn | -175.43 Mn | - | 19.16 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19.16 Mn |
| Mar 31, 2026 | 19.91 Mn |
| Dec 31, 2025 | 21.70 Mn |
| Sep 30, 2025 | 20.68 Mn |
| Jun 30, 2025 | 21.90 Mn |
| Mar 31, 2025 | 22.14 Mn |
| Dec 31, 2024 | 25.48 Mn |
| Sep 30, 2024 | 21.85 Mn |
| Jun 30, 2024 | 25.75 Mn |
| Mar 31, 2024 | 21.77 Mn |
| Dec 31, 2023 | 21.93 Mn |
| Sep 30, 2023 | 25.48 Mn |
| Jun 30, 2023 | 22.92 Mn |
| Mar 31, 2023 | 22.13 Mn |
| Dec 31, 2022 | 22.71 Mn |
| Sep 30, 2022 | 22.04 Mn |
| Jun 30, 2022 | 33.37 Mn |
| Mar 31, 2022 | 30.65 Mn |
| Dec 31, 2021 | 37.06 Mn |
| Sep 30, 2021 | 35.58 Mn |
Precision Biosciences Operating 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=operating-expenses&ticker=DTIL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=DTIL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();