BridgeBio Pharma (BBIO) Operating Expenses (2018 - 2026)
BridgeBio Pharma (BBIO) recorded Operating Expenses of $350.76 million in Q2 2026, up 43.3% from $244.84 million a year earlier and up 16.7% from the prior quarter.
BridgeBio Pharma (BBIO) Operating Expenses (2018 - 2026) Analysis & Trends
On a TTM basis, BridgeBio Pharma's Operating Expenses came in at $1.21 billion as of Jun 30, 2026, up 35.7% year-over-year; for FY2025, it came in at $1.03 billion, up 25.8% from FY2024.
- Annual Operating Expenses has increased for three straight years, with a five-year compound annual growth rate of 16.3% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $814.88 million in FY2024 (+32.1%), $616.67 million in FY2023 (+4.5%), $589.85 million in FY2022 (-8.7%) and $646.35 million in FY2021 (+33.9%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q2 2018.
- On a year-over-year basis, Operating Expenses has increased for 12 consecutive quarters, with growth averaging 29.4% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 64.7% in Q1 2024, against a decline of 27.0% in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $300.47 million (Q1 2026), $293.74 million (Q4 2025) and $265.9 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,130.22 Bn | 1,098.81 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 613.62 Bn | 532.15 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 501.46 Bn | 474.57 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 366.84 Bn | 321.22 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 297.85 Bn | 261.84 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.66 Bn | 235.34 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 235.39 Bn | 190.79 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 190.66 Bn | 164.86 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 169.57 Bn | 116.22 Bn | 10.94 Bn | 6.68 Bn |
| 10 | BridgeBio Pharma | 13.39 Bn | 10.50 Bn | 228.63 Mn | 350.76 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 350.76 Mn |
| Mar 31, 2026 | 300.47 Mn |
| Dec 31, 2025 | 293.74 Mn |
| Sep 30, 2025 | 265.90 Mn |
| Jun 30, 2025 | 244.84 Mn |
| Mar 31, 2025 | 221.01 Mn |
| Dec 31, 2024 | 231.91 Mn |
| Sep 30, 2024 | 194.48 Mn |
| Jun 30, 2024 | 177.71 Mn |
| Mar 31, 2024 | 210.78 Mn |
| Dec 31, 2023 | 179.16 Mn |
| Sep 30, 2023 | 161.78 Mn |
| Jun 30, 2023 | 147.74 Mn |
| Mar 31, 2023 | 127.99 Mn |
| Dec 31, 2022 | 131.10 Mn |
| Sep 30, 2022 | 129.45 Mn |
| Jun 30, 2022 | 153.92 Mn |
| Mar 31, 2022 | 175.37 Mn |
| Dec 31, 2021 | 178.50 Mn |
| Sep 30, 2021 | 151.84 Mn |
BridgeBio Pharma 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=BBIO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BBIO", "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=BBIO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();