BioRestorative Therapies (BRTX) Operating Expenses (2010 - 2025)
BioRestorative Therapies (BRTX) recorded Operating Expenses of $3.84 million in Q4 2025, up 40.8% from $2.73 million a year earlier and up 3.6% from the prior quarter.
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Analysis
BioRestorative Therapies (BRTX) Operating Expenses (2010 - 2025) Analysis & Trends
For FY2025, BioRestorative Therapies reported Operating Expenses of $15.98 million, up 34.0% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 41.4% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $11.93 million in FY2024 (-22.4%), $15.37 million in FY2023 (-19.5%), $19.09 million in FY2022 (-27.5%) and $26.35 million in FY2021 (+831.5%).
- Quarterly Operating Expenses has ranged from $2.5 million in Q3 2024 to $15.07 million in Q1 2021 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with growth averaging 7.8% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 642.9% in Q2 2021, against a decline of 66.4% in Q1 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $3.71 million (Q3 2025), $3.6 million (Q2 2025) and $4.83 million (Q1 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.97 Bn | 1,105.55 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 619.72 Bn | 538.25 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 503.40 Bn | 476.52 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 370.15 Bn | 324.53 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 298.64 Bn | 262.63 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.07 Bn | 234.76 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 237.00 Bn | 192.40 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 191.24 Bn | 165.43 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 170.31 Bn | 116.96 Bn | 10.94 Bn | 6.68 Bn |
| 10 | BioRestorative Therapies | 687,973.67 | -23.25 Mn | 17,964.00 | 3.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 3.84 Mn |
| Sep 30, 2025 | 3.71 Mn |
| Jun 30, 2025 | 3.60 Mn |
| Mar 31, 2025 | 4.83 Mn |
| Dec 31, 2024 | 2.73 Mn |
| Sep 30, 2024 | 2.50 Mn |
| Jun 30, 2024 | 2.55 Mn |
| Mar 31, 2024 | 4.14 Mn |
| Dec 31, 2023 | 3.24 Mn |
| Sep 30, 2023 | 3.14 Mn |
| Jun 30, 2023 | 3.18 Mn |
| Mar 31, 2023 | 5.81 Mn |
| Dec 31, 2022 | 4.69 Mn |
| Sep 30, 2022 | 4.64 Mn |
| Jun 30, 2022 | 4.70 Mn |
| Mar 31, 2022 | 5.07 Mn |
| Dec 31, 2021 | 4.01 Mn |
| Sep 30, 2021 | 3.70 Mn |
| Jun 30, 2021 | 3.57 Mn |
| Mar 31, 2021 | 15.07 Mn |
API Access
BioRestorative Therapies 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=BRTX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BRTX", "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=BRTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();