Pacira BioSciences (PCRX) Operating Expenses (2010 - 2026)
Pacira BioSciences (PCRX) posted Operating Expenses of $188.13 million for Q2 2026, up 9.0% from $172.6 million a year earlier and up 10.4% from the prior quarter.
Pacira BioSciences (PCRX) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Pacira BioSciences was $726.29 million, down 10.4% year-over-year; for FY2025, it came in at $707.22 million, down 8.7% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 13.0% (FY2020 to FY2025).
- In prior years, Pacira BioSciences' Operating Expenses was $774.34 million in FY2024 (+31.8%), $587.3 million in FY2023 (-3.2%), $606.8 million in FY2022 (+34.4%) and $451.61 million in FY2021 (+17.8%).
- Quarterly Operating Expenses has run from a low of $96.29 million in Q3 2021 to a high of $308.1 million in Q3 2024 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last three quarters, with growth averaging 16.4% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2024, with growth of 110.7%; the weakest was Q3 2025, with a decline of 43.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $170.47 million (Q1 2026), $194.53 million (Q4 2025) and $173.15 million (Q3 2025).
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 | Pacira BioSciences | 1.43 Bn | 495.69 Mn | 148.24 Mn | 188.13 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 188.13 Mn |
| Mar 31, 2026 | 170.47 Mn |
| Dec 31, 2025 | 194.53 Mn |
| Sep 30, 2025 | 173.15 Mn |
| Jun 30, 2025 | 172.60 Mn |
| Mar 31, 2025 | 166.93 Mn |
| Dec 31, 2024 | 162.55 Mn |
| Sep 30, 2024 | 308.10 Mn |
| Jun 30, 2024 | 149.78 Mn |
| Mar 31, 2024 | 153.91 Mn |
| Dec 31, 2023 | 148.08 Mn |
| Sep 30, 2023 | 146.21 Mn |
| Jun 30, 2023 | 129.59 Mn |
| Mar 31, 2023 | 163.43 Mn |
| Dec 31, 2022 | 181.85 Mn |
| Sep 30, 2022 | 146.18 Mn |
| Jun 30, 2022 | 138.18 Mn |
| Mar 31, 2022 | 140.60 Mn |
| Dec 31, 2021 | 154.98 Mn |
| Sep 30, 2021 | 96.29 Mn |
Pacira 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=PCRX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PCRX", "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=PCRX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();