Femasys (FEMY) Other Non-Current Liabilities (2020 - 2026)
Femasys (FEMY) recorded Other Non-Current Liabilities of $5.96 million in Q2 2026, up 227.2% from $1.82 million a year earlier and up 13.6% from the prior quarter.
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Analysis
Femasys (FEMY) Other Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Femasys reported Other Non-Current Liabilities of $5.25 million, up 182.0% from FY2024.
- Annual Other Non-Current Liabilities has a five-year compound annual growth rate of 49.5% (FY2020 to FY2025).
- Across earlier years, Other Non-Current Liabilities came in at $1.86 million in FY2024 (-33.3%), $2.79 million in FY2023 (+390.7%), $567,972 in FY2022 (-19.1%) and $702,492 in FY2021 (unchanged).
- Quarterly Other Non-Current Liabilities has ranged from $567,972 in Q2 2022 to $6.73 million in Q3 2025 over the past five years.
- On a year-over-year basis, Other Non-Current Liabilities has increased for four consecutive quarters, with growth averaging 90.2% over the last eight quarters.
- Peak year-over-year performance for Other Non-Current Liabilities in the last five years was growth of 390.7% in Q4 2023, against a decline of 33.3% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $5.25 million (Q1 2026), $5.25 million (Q4 2025) and $6.73 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn |
| 10 | Femasys | 6.32 Mn | -14.34 Mn | 189,391.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.96 Mn |
| Mar 31, 2026 | 5.25 Mn |
| Dec 31, 2025 | 5.25 Mn |
| Sep 30, 2025 | 6.73 Mn |
| Jun 30, 2025 | 1.82 Mn |
| Mar 31, 2025 | 1.86 Mn |
| Dec 31, 2024 | 1.86 Mn |
| Sep 30, 2024 | 2.61 Mn |
| Jun 30, 2024 | 2.61 Mn |
| Mar 31, 2024 | 2.63 Mn |
| Dec 31, 2023 | 2.79 Mn |
| Sep 30, 2023 | 1.58 Mn |
| Jun 30, 2023 | 1.92 Mn |
| Mar 31, 2023 | 567,972.00 |
| Dec 31, 2022 | 567,972.00 |
| Sep 30, 2022 | 567,972.00 |
| Jun 30, 2022 | 567,972.00 |
| Mar 31, 2022 | 702,492.00 |
| Dec 31, 2021 | 702,492.00 |
| Sep 30, 2021 | 702,492.00 |
API Access
Femasys Other Non-Current 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=other-non-current-liabilities&ticker=FEMY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-non-current-liabilities", "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=other-non-current-liabilities&ticker=FEMY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();