Neuroone Medical Technologies (NMTC) Change in Accrued Expenses (2011 - 2026)
Neuroone Medical Technologies' Change in Accrued Expenses was $361,412 in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 389.5% from $73,839 a year earlier.
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Analysis
Neuroone Medical Technologies (NMTC) Change in Accrued Expenses (2011 - 2026) Analysis & Trends
On a trailing twelve-month basis, Neuroone Medical Technologies' Change in Accrued Expenses was $75,632 through Jun 30, 2026; for FY2025 (ended Sep 30, 2025), it was -$54,442.
- In earlier fiscal years, Change in Accrued Expenses was $16,214 in FY2024, -$1.23 million in FY2023, $1.43 million in FY2022 and -$7,477 in FY2021.
- The fiscal Q3 2026 figure marks the highest quarterly Change in Accrued Expenses since fiscal Q4 2022.
- Compared with a year earlier, Change in Accrued Expenses was higher in two of the last six quarters, with growth averaging 44.3%.
- The best year-over-year quarter for Change in Accrued Expenses over five years was fiscal Q3 2026 (growth of 389.5%); the worst was fiscal Q4 2023 (a decline of 82.9%).
- Per Business Quant data, NMTC's Change in Accrued Expenses in the three fiscal quarters before Q3 2026 was $31,133 (Q2 2026), -$619,376 (Q1 2026) and $302,463 (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 267.71 Bn | 244.23 Bn | 5.13 Bn | - |
| 2 | Abbott Laboratories | 191.69 Bn | 165.56 Bn | 7.39 Bn | - |
| 3 | Danaher | 166.18 Bn | 145.83 Bn | 3.84 Bn | 30.00 Mn |
| 4 | Intuitive Surgical | 161.07 Bn | 141.36 Bn | 2.08 Bn | 80.10 Mn |
| 5 | Medtronic | 131.65 Bn | 96.90 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 125.25 Bn | 111.44 Bn | 4.25 Bn | 77.00 Mn |
| 7 | Boston Scientific | 63.85 Bn | 59.29 Bn | 3.43 Bn | 89.00 Mn |
| 8 | Edwards Lifesciences | 60.52 Bn | 43.72 Bn | 1.35 Bn | 67.20 Mn |
| 9 | Becton Dickinson | 59.08 Bn | 56.23 Bn | 2.32 Bn | - |
| 10 | Neuroone Medical Technologies | 7.41 Mn | -7.61 Mn | 1.18 Mn | 361,412.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 361,412.00 |
| Mar 31, 2026 | 31,133.00 |
| Dec 31, 2025 | -619,376.00 |
| Sep 30, 2025 | 302,463.00 |
| Jun 30, 2025 | 73,839.00 |
| Mar 31, 2025 | 32,548.00 |
| Dec 31, 2024 | -463,292.00 |
| Sep 30, 2024 | 236,795.00 |
| Jun 30, 2024 | 199,613.00 |
| Mar 31, 2024 | 98,390.00 |
| Dec 31, 2023 | -518,584.00 |
| Sep 30, 2023 | 284,791.00 |
| Jun 30, 2023 | 159,179.00 |
| Mar 31, 2023 | -1.36 Mn |
| Dec 31, 2022 | -306,125.00 |
| Sep 30, 2022 | 1.66 Mn |
| Jun 30, 2022 | 107,201.00 |
| Mar 31, 2022 | -18,060.00 |
| Dec 31, 2021 | -317,456.00 |
| Sep 30, 2021 | 125,239.00 |
API Access
Neuroone Medical Technologies Change in Accrued 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=change-in-accured-expenses&ticker=NMTC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=NMTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();