Ensysce Biosciences (ENSC) Operating Expenses (2018 - 2025)
Ensysce Biosciences (ENSC) reported Operating Expenses of $4.23 million for Q3 2025, up 52.6% from $2.77 million a year earlier and up 35.6% from the prior quarter.
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Analysis
Ensysce Biosciences (ENSC) Operating Expenses (2018 - 2025) Analysis & Trends
Over the twelve months ended Sep 30, 2025, Ensysce Biosciences' Operating Expenses came in at $15.52 million, up 44.7% year-over-year; for FY2024, it was $11.94 million, down 7.8% from FY2023.
- Operating Expenses has a five-year compound annual growth rate of 29.1% (FY2019 to FY2024).
- By year, Operating Expenses came in at $12.95 million in FY2023 (-51.6%), $26.75 million in FY2022 (+14.3%), $23.4 million in FY2021 (+322.1%) and $5.54 million in FY2020 (+66.6%).
- Five-year quarterly Operating Expenses spans a low of $774,849 in Q1 2021 and a high of $18.09 million in Q3 2021.
- Year over year, Operating Expenses has now increased in each of the last four quarters, with growth averaging 7.7% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2022 (growth of 747.3%); the low point was Q3 2022 (a decline of 64.4%).
- Per Business Quant data, the three quarters before Q3 2025 came in at $3.12 million (Q2 2025), $3.29 million (Q1 2025) and $4.88 million (Q4 2024).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,264.65 Bn | 1,238.27 Bn | 20.46 Bn | 7.68 Bn |
| 2 | Johnson & Johnson | 677.74 Bn | 597.60 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 517.10 Bn | 485.11 Bn | 13.12 Bn | 11.14 Bn |
| 4 | Merck | 362.23 Bn | 325.17 Bn | 13.19 Bn | 7.61 Bn |
| 5 | Novartis Ag | 315.90 Bn | 276.16 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 289.40 Bn | 266.24 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 249.90 Bn | 201.56 Bn | 7.58 Bn | 6.66 Bn |
| 8 | Gilead Sciences | 209.15 Bn | 184.26 Bn | 6.73 Bn | 4.84 Bn |
| 9 | Pfizer | 165.88 Bn | 113.23 Bn | 12.56 Bn | 7.09 Bn |
| 10 | Ensysce Biosciences | 901,219.67 | -10.35 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 4.23 Mn |
| Jun 30, 2025 | 3.12 Mn |
| Mar 31, 2025 | 3.29 Mn |
| Dec 31, 2024 | 4.88 Mn |
| Sep 30, 2024 | 2.77 Mn |
| Jun 30, 2024 | 2.14 Mn |
| Mar 31, 2024 | 2.15 Mn |
| Dec 31, 2023 | 3.67 Mn |
| Sep 30, 2023 | 3.14 Mn |
| Jun 30, 2023 | 2.78 Mn |
| Mar 31, 2023 | 3.35 Mn |
| Dec 31, 2022 | 7.63 Mn |
| Sep 30, 2022 | 6.44 Mn |
| Jun 30, 2022 | 7.26 Mn |
| Mar 31, 2022 | 5.41 Mn |
| Dec 31, 2021 | 3.64 Mn |
| Sep 30, 2021 | 18.09 Mn |
| Jun 30, 2021 | 857,133.00 |
| Mar 31, 2021 | 774,849.00 |
| Dec 31, 2020 | 1.51 Mn |
API Access
Ensysce 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=ENSC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ENSC", "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=ENSC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();