Neuroone Medical Technologies (NMTC) Total Liabilities (2010 - 2026)
Neuroone Medical Technologies' Total Liabilities came in at $2.42 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 8.5% from $2.64 million a year earlier and down 2.9% from the prior quarter.
Neuroone Medical Technologies (NMTC) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Neuroone Medical Technologies' Total Liabilities was $3.71 million, down 18.4% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 6.6% (FY2020 to FY2025).
- Going back by fiscal year, Total Liabilities was $4.55 million in FY2024 (+146.1%), $1.85 million in FY2023 (-42.6%), $3.22 million in FY2022 (+132.4%) and $1.38 million in FY2021 (-48.6%).
- The five-year range for quarterly Total Liabilities is $952,478 (fiscal Q3 2022) to $4.55 million (fiscal Q4 2024).
- Year-over-year, Total Liabilities has declined for four consecutive quarters, with growth averaging 45.5% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in fiscal Q1 2025 (growth of 153.5%), and the weakest in fiscal Q1 2022 (a decline of 81.0%).
- Business Quant data shows NMTC's Total Liabilities at $2.49 million (Q2 2026), $2.18 million (Q1 2026) and $3.71 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 267.71 Bn | 244.23 Bn | 5.13 Bn | 59.47 Bn |
| 2 | Abbott Laboratories | 191.69 Bn | 165.56 Bn | 7.39 Bn | 56.62 Bn |
| 3 | Danaher | 166.18 Bn | 145.83 Bn | 3.84 Bn | 39.65 Bn |
| 4 | Intuitive Surgical | 161.07 Bn | 141.36 Bn | 2.08 Bn | 3.23 Bn |
| 5 | Medtronic | 131.65 Bn | 96.90 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 125.25 Bn | 111.44 Bn | 4.25 Bn | 23.79 Bn |
| 7 | Boston Scientific | 63.85 Bn | 59.29 Bn | 3.43 Bn | 19.59 Bn |
| 8 | Edwards Lifesciences | 60.52 Bn | 43.72 Bn | 1.35 Bn | 3.18 Bn |
| 9 | Becton Dickinson | 59.08 Bn | 56.23 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Neuroone Medical Technologies | 7.41 Mn | -7.61 Mn | 1.18 Mn | 2.42 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.42 Mn |
| Mar 31, 2026 | 2.49 Mn |
| Dec 31, 2025 | 2.18 Mn |
| Sep 30, 2025 | 3.71 Mn |
| Jun 30, 2025 | 2.64 Mn |
| Mar 31, 2025 | 3.33 Mn |
| Dec 31, 2024 | 3.56 Mn |
| Sep 30, 2024 | 4.55 Mn |
| Jun 30, 2024 | 1.90 Mn |
| Mar 31, 2024 | 1.54 Mn |
| Dec 31, 2023 | 1.40 Mn |
| Sep 30, 2023 | 1.85 Mn |
| Jun 30, 2023 | 1.84 Mn |
| Mar 31, 2023 | 1.67 Mn |
| Dec 31, 2022 | 1.49 Mn |
| Sep 30, 2022 | 3.22 Mn |
| Jun 30, 2022 | 952,478.00 |
| Mar 31, 2022 | 966,274.00 |
| Dec 31, 2021 | 1.24 Mn |
| Sep 30, 2021 | 1.38 Mn |
Neuroone Medical Technologies Total Liabilities 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=total-liabilities&ticker=NMTC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=NMTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();