Neuroone Medical Technologies (NMTC) Operating Expenses (2010 - 2026)
Neuroone Medical Technologies (NMTC) reported Operating Expenses of $3.61 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 28.8% from $2.8 million a year earlier and up 6.5% from the prior quarter.
Neuroone Medical Technologies (NMTC) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Neuroone Medical Technologies' Operating Expenses came in at $13.17 million, up 6.0% year-over-year; for FY2025 (ended Sep 30, 2025), it was $12.37 million, down 4.6% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 12.6% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $12.97 million in FY2024 (-6.5%), $13.87 million in FY2023 (+16.4%), $11.91 million in FY2022 (+16.9%) and $10.19 million in FY2021 (+49.2%).
- The fiscal Q3 2026 figure ranks as the highest quarterly Operating Expenses since fiscal Q1 2024.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 0.1%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q3 2023 (growth of 36.3%); the low point was fiscal Q3 2024 (a decline of 18.1%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $3.39 million (Q2 2026), $3.28 million (Q1 2026) and $2.9 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Neuroone Medical Technologies | 11.31 Mn | -3.71 Mn | 1.18 Mn | 3.61 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.61 Mn |
| Mar 31, 2026 | 3.39 Mn |
| Dec 31, 2025 | 3.28 Mn |
| Sep 30, 2025 | 2.90 Mn |
| Jun 30, 2025 | 2.80 Mn |
| Mar 31, 2025 | 3.45 Mn |
| Dec 31, 2024 | 3.22 Mn |
| Sep 30, 2024 | 2.96 Mn |
| Jun 30, 2024 | 3.08 Mn |
| Mar 31, 2024 | 3.28 Mn |
| Dec 31, 2023 | 3.66 Mn |
| Sep 30, 2023 | 3.36 Mn |
| Jun 30, 2023 | 3.75 Mn |
| Mar 31, 2023 | 3.53 Mn |
| Dec 31, 2022 | 3.23 Mn |
| Sep 30, 2022 | 3.33 Mn |
| Jun 30, 2022 | 2.76 Mn |
| Mar 31, 2022 | 3.02 Mn |
| Dec 31, 2021 | 2.80 Mn |
| Sep 30, 2021 | 2.63 Mn |
Neuroone Medical Technologies 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=NMTC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NMTC", "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=NMTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();