Biolife Solutions (BLFS) Operating Expenses (2010 - 2026)
Biolife Solutions (BLFS) recorded Operating Expenses of $16.59 million in Q2 2026, down 47.1% from $31.36 million a year earlier and down 5.0% from the prior quarter.
Biolife Solutions (BLFS) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Biolife Solutions' Operating Expenses came in at $45.56 million as of Jun 30, 2026, down 22.1% year-over-year; for FY2025, it was $78.72 million, up 44.2% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 7.7% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $54.57 million in FY2024 (-6.7%), $58.52 million in FY2023 (-28.8%), $82.16 million in FY2022 (-46.8%) and $154.32 million in FY2021 (+184.0%).
- Quarterly Operating Expenses has ranged from -$131.61 million in Q4 2022 to $117.1 million in Q2 2022 over the past five years.
- On a year-over-year basis, Operating Expenses rose in three of the last six quarters, with an average decline of 4.7%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 259.0% in Q3 2021, against a decline of 66.0% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $17.47 million (Q1 2026), -$16.66 million (Q4 2025) and $28.16 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 260.54 Bn | 239.57 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 170.96 Bn | 141.39 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 164.49 Bn | 148.30 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 152.54 Bn | 131.97 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 119.41 Bn | 84.66 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 112.98 Bn | 99.09 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 64.88 Bn | 59.65 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 53.29 Bn | 50.44 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.48 Bn | 34.49 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Biolife Solutions | 1.89 Bn | 1.56 Bn | 18.29 Mn | 16.59 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 16.59 Mn |
| Mar 31, 2026 | 17.47 Mn |
| Dec 31, 2025 | -16.66 Mn |
| Sep 30, 2025 | 28.16 Mn |
| Jun 30, 2025 | 31.36 Mn |
| Mar 31, 2025 | 15.30 Mn |
| Dec 31, 2024 | -9.99 Mn |
| Sep 30, 2024 | 21.81 Mn |
| Jun 30, 2024 | 21.02 Mn |
| Mar 31, 2024 | 21.73 Mn |
| Dec 31, 2023 | -58.20 Mn |
| Sep 30, 2023 | 39.05 Mn |
| Jun 30, 2023 | 39.87 Mn |
| Mar 31, 2023 | 51.31 Mn |
| Dec 31, 2022 | -131.61 Mn |
| Sep 30, 2022 | 52.49 Mn |
| Jun 30, 2022 | 117.10 Mn |
| Mar 31, 2022 | 44.19 Mn |
| Dec 31, 2021 | 55.77 Mn |
| Sep 30, 2021 | 44.96 Mn |
Biolife Solutions 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=BLFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BLFS", "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=BLFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();