Bioxytran (BIXT) Operating Expenses (2010 - 2026)
Bioxytran (BIXT) posted Operating Expenses of $654,600 for Q2 2026, up 192.1% from $224,077 a year earlier but down 66.1% from the prior quarter.
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Analysis
Bioxytran (BIXT) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Bioxytran was $3.69 million, up 134.5% year-over-year; for FY2025, it came in at $1.84 million, down 17.1% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 7.7% (FY2020 to FY2025).
- In prior years, Bioxytran's Operating Expenses was $2.22 million in FY2024 (-41.5%), $3.8 million in FY2023 (+56.0%), $2.44 million in FY2022 (-42.2%) and $4.21 million in FY2021 (+232.2%).
- Quarterly Operating Expenses has run from a low of -$14,225 in Q3 2022 to a high of $1.93 million in Q1 2026 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last four quarters, with growth averaging 40.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 378.2%; the weakest was Q3 2024, with a decline of 64.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $1.93 million (Q1 2026), $607,285 (Q4 2025) and $496,005 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Bioxytran | 2.29 Mn | 1.13 Mn | - | 654,600.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 654,600.00 |
| Mar 31, 2026 | 1.93 Mn |
| Dec 31, 2025 | 607,285.00 |
| Sep 30, 2025 | 496,005.00 |
| Jun 30, 2025 | 224,077.00 |
| Mar 31, 2025 | 515,142.00 |
| Dec 31, 2024 | 488,313.00 |
| Sep 30, 2024 | 346,204.00 |
| Jun 30, 2024 | 609,322.00 |
| Mar 31, 2024 | 779,229.00 |
| Dec 31, 2023 | 1.01 Mn |
| Sep 30, 2023 | 985,465.00 |
| Jun 30, 2023 | 1.06 Mn |
| Mar 31, 2023 | 750,242.00 |
| Dec 31, 2022 | 1.09 Mn |
| Sep 30, 2022 | -14,225.00 |
| Jun 30, 2022 | 537,224.00 |
| Mar 31, 2022 | 819,106.00 |
| Dec 31, 2021 | 935,964.00 |
| Sep 30, 2021 | 547,243.00 |
API Access
Bioxytran 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=BIXT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BIXT", "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=BIXT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();