Lexaria Bioscience (LEXX) Operating Expenses (2017 - 2026)
Lexaria Bioscience (LEXX) recorded Operating Expenses of $1.99 million in fiscal Q3 2026 (quarter ended May 31, 2026), down 49.2% from $3.92 million a year earlier but up 35.5% from the prior quarter.
Lexaria Bioscience (LEXX) Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Lexaria Bioscience's Operating Expenses came in at $7.9 million as of May 31, 2026, down 34.2% year-over-year; for FY2025 (ended Aug 31, 2025), it came in at $12.58 million, up 102.6% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 23.6% (FY2020 to FY2025).
- Across earlier fiscal years, Operating Expenses came in at $6.21 million in FY2024 (-7.7%), $6.73 million in FY2023 (-1.1%), $6.8 million in FY2022 (+9.1%) and $6.23 million in FY2021 (+42.8%).
- Quarterly Operating Expenses has ranged from $813,005 in fiscal Q2 2024 to $3.92 million in fiscal Q3 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has declined for three consecutive quarters, with growth averaging 59.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 259.8% in fiscal Q2 2025, against a decline of 49.7% in fiscal Q2 2026 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $1.47 million (Q2 2026), $1.57 million (Q1 2026) and $2.86 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Lexaria Bioscience | 3.39 Mn | -12.26 Mn | - | 1.99 Mn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 1.99 Mn |
| Feb 28, 2026 | 1.47 Mn |
| Nov 30, 2025 | 1.57 Mn |
| Aug 31, 2025 | 2.86 Mn |
| May 31, 2025 | 3.92 Mn |
| Feb 28, 2025 | 2.93 Mn |
| Nov 30, 2024 | 2.87 Mn |
| Aug 31, 2024 | 2.29 Mn |
| May 31, 2024 | 1.83 Mn |
| Feb 29, 2024 | 813,005.00 |
| Nov 30, 2023 | 1.29 Mn |
| Aug 31, 2023 | 1.14 Mn |
| May 31, 2023 | 2.47 Mn |
| Feb 28, 2023 | 1.34 Mn |
| Nov 30, 2022 | 1.78 Mn |
| Aug 31, 2022 | 818,448.00 |
| May 31, 2022 | 2.50 Mn |
| Feb 28, 2022 | 1.47 Mn |
| Nov 30, 2021 | 2.01 Mn |
| Aug 31, 2021 | 1.31 Mn |
Lexaria Bioscience 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=LEXX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LEXX", "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=LEXX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();