Myomo (MYO) Operating Expenses (2016 - 2025)
Myomo's Operating Expenses came in at $9.96 million for Q3 2025, up 26.0% from $7.9 million a year earlier but down 6.4% from the prior quarter.
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Analysis
Myomo (MYO) Operating Expenses (2016 - 2025) Analysis & Trends
Over the trailing twelve months to Sep 30, 2025, Myomo reported Operating Expenses of $39.59 million, up 51.9% year-over-year; for FY2024, it came in at $29.39 million, up 37.3% from FY2023.
- Operating Expenses has increased in each of the last eight years, with a five-year compound annual growth rate of 17.3% (FY2019 to FY2024).
- Going back by year, Operating Expenses was $21.41 million in FY2023 (+2.3%), $20.93 million in FY2022 (+1.7%), $20.58 million in FY2021 (+32.9%) and $15.49 million in FY2020 (+17.2%).
- The five-year range for quarterly Operating Expenses is $4.47 million (Q4 2020) to $10.64 million (Q2 2025).
- Year-over-year, Operating Expenses has increased for ten consecutive quarters, with growth averaging 39.5% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2025 (growth of 65.2%), and the weakest in Q4 2022 (a decline of 16.7%).
- Business Quant data shows MYO's Operating Expenses at $10.64 million (Q2 2025), $10.13 million (Q1 2025) and $8.86 million (Q4 2024) in the three quarters before Q3 2025.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Myomo | 58.80 Mn | -614,275.30 | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 9.96 Mn |
| Jun 30, 2025 | 10.64 Mn |
| Mar 31, 2025 | 10.13 Mn |
| Dec 31, 2024 | 8.86 Mn |
| Sep 30, 2024 | 7.90 Mn |
| Jun 30, 2024 | 6.44 Mn |
| Mar 31, 2024 | 6.19 Mn |
| Dec 31, 2023 | 5.54 Mn |
| Sep 30, 2023 | 5.51 Mn |
| Jun 30, 2023 | 5.38 Mn |
| Mar 31, 2023 | 4.98 Mn |
| Dec 31, 2022 | 4.86 Mn |
| Sep 30, 2022 | 5.46 Mn |
| Jun 30, 2022 | 5.30 Mn |
| Mar 31, 2022 | 5.32 Mn |
| Dec 31, 2021 | 5.83 Mn |
| Sep 30, 2021 | 5.30 Mn |
| Jun 30, 2021 | 4.80 Mn |
| Mar 31, 2021 | 4.65 Mn |
| Dec 31, 2020 | 4.47 Mn |
API Access
Myomo 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=MYO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MYO", "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=MYO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();