Femasys (FEMY) Amortizatization of Intangibles (2020 - 2026)
Femasys (FEMY) posted Amortizatization of Intangibles of $19,005 for Q2 2026, up 120.5% from $8,618 a year earlier and up 13.9% from the prior quarter.
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Analysis
Femasys (FEMY) Amortizatization of Intangibles (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Amortizatization of Intangibles at Femasys was $66,083, up 119.5% year-over-year; for FY2025, it came in at $46,175, up 129.3% from FY2024.
- Annual Amortizatization of Intangibles shows a five-year compound annual growth rate of -17.2% (FY2020 to FY2025).
- In prior years, Femasys' Amortizatization of Intangibles was $20,140 in FY2024 (+511.4%), $3,294 in FY2023 (-84.9%), $21,799 in FY2022 (-45.5%) and $39,976 in FY2021 (-66.4%).
- The Q2 2026 figure stands as the highest quarterly Amortizatization of Intangibles since Q4 2020.
- On a year-over-year basis, Amortizatization of Intangibles has increased in each of the last six quarters, with growth averaging 290.7% over the last seven quarters.
- The strongest year-over-year quarter for Amortizatization of Intangibles in the past five years was Q3 2024, with growth of 992.1%; the weakest was Q3 2023, with a decline of 88.0%.
- According to Business Quant data, Amortizatization of Intangibles for the three prior quarters was $16,692 (Q1 2026), $16,711 (Q4 2025) and $13,675 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Amort. of Intangibles (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | 485.00 Mn |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | 658.00 Mn |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | 463.00 Mn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 24.00 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | - |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 175.00 Mn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | - |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | - |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | - |
| 10 | Femasys | 6.20 Mn | -14.47 Mn | 189,391.00 | 19,005.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19,005.00 |
| Mar 31, 2026 | 16,692.00 |
| Dec 31, 2025 | 16,711.00 |
| Sep 30, 2025 | 13,675.00 |
| Jun 30, 2025 | 8,618.00 |
| Mar 31, 2025 | 7,171.00 |
| Dec 31, 2024 | 7,967.00 |
| Sep 30, 2024 | 6,345.00 |
| Jun 30, 2024 | 4,583.00 |
| Mar 31, 2024 | 1,245.00 |
| Dec 31, 2023 | 388.00 |
| Sep 30, 2023 | 581.00 |
| Jun 30, 2023 | 912.00 |
| Mar 31, 2023 | 1,413.00 |
| Dec 31, 2022 | 2,465.00 |
| Sep 30, 2022 | 4,842.00 |
| Jun 30, 2022 | 7,062.00 |
| Mar 31, 2022 | 7,430.00 |
| Dec 31, 2021 | 7,953.00 |
| Sep 30, 2021 | 9,139.00 |
API Access
Femasys Amortizatization of Intangibles 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=amortizatization-of-intangibles&ticker=FEMY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "amortizatization-of-intangibles", "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=amortizatization-of-intangibles&ticker=FEMY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();