Aura Biosciences (AURA) Operating Expenses (2020 - 2026)
Aura Biosciences (AURA) reported Operating Expenses of $48.07 million for Q2 2026, up 68.0% from $28.61 million a year earlier and up 37.9% from the prior quarter.
Aura Biosciences (AURA) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Aura Biosciences' Operating Expenses came in at $138.08 million, up 27.0% year-over-year; for FY2025, it was $112.79 million, up 17.3% from FY2024.
- Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 38.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $96.12 million in FY2024 (+13.1%), $84.99 million in FY2023 (+41.0%), $60.3 million in FY2022 (+71.0%) and $35.25 million in FY2021 (+58.7%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q3 2020.
- Year over year, Operating Expenses gained in seven of the last eight quarters, with growth averaging 23.4%.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 145.0%); the low point was Q4 2025 (a decline of 2.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $34.87 million (Q1 2026), $27.24 million (Q4 2025) and $27.91 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,135.43 Bn | 1,104.02 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 616.54 Bn | 535.06 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 501.55 Bn | 474.66 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 367.19 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 297.91 Bn | 261.90 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.40 Bn | 235.09 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 236.18 Bn | 191.58 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 190.55 Bn | 164.75 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 169.40 Bn | 116.05 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Aura Biosciences | 616.61 Mn | 356.92 Mn | - | 48.07 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 48.07 Mn |
| Mar 31, 2026 | 34.87 Mn |
| Dec 31, 2025 | 27.24 Mn |
| Sep 30, 2025 | 27.91 Mn |
| Jun 30, 2025 | 28.61 Mn |
| Mar 31, 2025 | 29.04 Mn |
| Dec 31, 2024 | 27.81 Mn |
| Sep 30, 2024 | 23.23 Mn |
| Jun 30, 2024 | 22.76 Mn |
| Mar 31, 2024 | 22.31 Mn |
| Dec 31, 2023 | 24.78 Mn |
| Sep 30, 2023 | 20.49 Mn |
| Jun 30, 2023 | 20.28 Mn |
| Mar 31, 2023 | 19.44 Mn |
| Dec 31, 2022 | 17.61 Mn |
| Sep 30, 2022 | 16.06 Mn |
| Jun 30, 2022 | 13.82 Mn |
| Mar 31, 2022 | 12.81 Mn |
| Dec 31, 2021 | 11.63 Mn |
| Sep 30, 2021 | 8.90 Mn |
Aura Biosciences 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=AURA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AURA", "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=AURA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();