Olema Pharmaceuticals (OLMA) Operating Expenses (2020 - 2026)
Olema Pharmaceuticals' Operating Expenses came in at $67.18 million for Q2 2026, up 40.4% from $47.86 million a year earlier and up 15.9% from the prior quarter.
Olema Pharmaceuticals (OLMA) Operating Expenses (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Olema Pharmaceuticals reported Operating Expenses of $221.13 million, up 40.7% year-over-year; for FY2025, it came in at $178.7 million, up 25.6% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 52.7% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $142.26 million in FY2024 (+35.5%), $104.96 million in FY2023 (-1.9%), $106.99 million in FY2022 (+49.7%) and $71.49 million in FY2021 (+232.1%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q1 2020.
- Year-over-year, Operating Expenses has increased for 12 consecutive quarters, with growth averaging 36.4% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 125.7%), and the weakest in Q2 2023 (a decline of 35.1%).
- Business Quant data shows OLMA's Operating Expenses at $57.99 million (Q1 2026), $50.08 million (Q4 2025) and $45.88 million (Q3 2025) in the three quarters before Q2 2026.
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 | Olema Pharmaceuticals | 752.96 Mn | 752.96 Mn | - | 67.18 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 67.18 Mn |
| Mar 31, 2026 | 57.99 Mn |
| Dec 31, 2025 | 50.08 Mn |
| Sep 30, 2025 | 45.88 Mn |
| Jun 30, 2025 | 47.86 Mn |
| Mar 31, 2025 | 34.87 Mn |
| Dec 31, 2024 | 36.77 Mn |
| Sep 30, 2024 | 37.62 Mn |
| Jun 30, 2024 | 33.53 Mn |
| Mar 31, 2024 | 34.34 Mn |
| Dec 31, 2023 | 30.42 Mn |
| Sep 30, 2023 | 23.34 Mn |
| Jun 30, 2023 | 21.60 Mn |
| Mar 31, 2023 | 29.60 Mn |
| Dec 31, 2022 | 27.22 Mn |
| Sep 30, 2022 | 23.22 Mn |
| Jun 30, 2022 | 33.29 Mn |
| Mar 31, 2022 | 23.25 Mn |
| Dec 31, 2021 | 21.76 Mn |
| Sep 30, 2021 | 17.76 Mn |
Olema Pharmaceuticals 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=OLMA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "OLMA", "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=OLMA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();