Femasys (FEMY) Accumulated Expenses (2020 - 2026)
Femasys (FEMY) posted Accumulated Expenses of $1.03 million for Q2 2026, down 1.8% from $1.05 million a year earlier but up 0.9% from the prior quarter.
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Analysis
Femasys (FEMY) Accumulated Expenses (2020 - 2026) Analysis & Trends
At the end of FY2025, Femasys' Accumulated Expenses came in at $1.27 million, up 10.0% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 2.5% (FY2020 to FY2025).
- In prior years, Femasys' Accumulated Expenses was $1.15 million in FY2024 (-20.3%), $1.44 million in FY2023 (+216.2%), $456,714 in FY2022 (-24.4%) and $603,787 in FY2021 (-46.0%).
- Quarterly Accumulated Expenses has run from a low of $456,714 in Q4 2022 to a high of $1.44 million in Q4 2023 over five years.
- On a year-over-year basis, Accumulated Expenses increased in four of the last eight quarters, with growth averaging 19.6%.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q4 2023, with growth of 216.2%; the weakest was Q4 2021, with a decline of 46.0%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $1.02 million (Q1 2026), $1.27 million (Q4 2025) and $1.03 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn |
| 10 | Femasys | 6.53 Mn | -14.13 Mn | 189,391.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.03 Mn |
| Mar 31, 2026 | 1.02 Mn |
| Dec 31, 2025 | 1.27 Mn |
| Sep 30, 2025 | 1.03 Mn |
| Jun 30, 2025 | 1.05 Mn |
| Mar 31, 2025 | 1.17 Mn |
| Dec 31, 2024 | 1.15 Mn |
| Sep 30, 2024 | 1.13 Mn |
| Jun 30, 2024 | 886,352.00 |
| Mar 31, 2024 | 673,457.00 |
| Dec 31, 2023 | 1.44 Mn |
| Sep 30, 2023 | 569,442.00 |
| Jun 30, 2023 | 536,830.00 |
| Mar 31, 2023 | 535,417.00 |
| Dec 31, 2022 | 456,714.00 |
| Sep 30, 2022 | 649,615.00 |
| Jun 30, 2022 | 551,828.00 |
| Mar 31, 2022 | 565,228.00 |
| Dec 31, 2021 | 603,787.00 |
| Sep 30, 2021 | 597,856.00 |
API Access
Femasys Accumulated 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=accumulated-expenses&ticker=FEMY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "FEMY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=FEMY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();