Prokidney (PROK) Operating Expenses (2021 - 2026)
Prokidney's Operating Expenses was $48.52 million in Q2 2026, up 21.5% from $39.93 million a year earlier and up 7.4% from the prior quarter.
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Analysis
Prokidney (PROK) Operating Expenses (2021 - 2026) Analysis & Trends
On a trailing twelve-month basis, Prokidney's Operating Expenses was $178.03 million through Jun 30, 2026, down 2.3% year-over-year; for FY2025, it came in at $165.9 million, down 9.7% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 43.8% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $183.75 million in FY2024 (+21.3%), $151.52 million in FY2023 (-1.0%), $153.01 million in FY2022 (+177.6%) and $55.11 million in FY2021 (+103.9%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q4 2024.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 14.1%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2022 (growth of 120.5%); the worst was Q1 2023 (a decline of 38.5%).
- Per Business Quant data, PROK's Operating Expenses in the three quarters before Q2 2026 was $45.16 million (Q1 2026), $45.6 million (Q4 2025) and $38.76 million (Q3 2025).
Peer Set
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 | Prokidney | 274.24 Mn | -213.07 Mn | - | 48.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 48.52 Mn |
| Mar 31, 2026 | 45.16 Mn |
| Dec 31, 2025 | 45.60 Mn |
| Sep 30, 2025 | 38.76 Mn |
| Jun 30, 2025 | 39.93 Mn |
| Mar 31, 2025 | 41.62 Mn |
| Dec 31, 2024 | 51.65 Mn |
| Sep 30, 2024 | 48.97 Mn |
| Jun 30, 2024 | 43.06 Mn |
| Mar 31, 2024 | 40.08 Mn |
| Dec 31, 2023 | 24.21 Mn |
| Sep 30, 2023 | 46.62 Mn |
| Jun 30, 2023 | 39.82 Mn |
| Mar 31, 2023 | 40.88 Mn |
| Dec 31, 2022 | 30.24 Mn |
| Sep 30, 2022 | 35.57 Mn |
| Jun 30, 2022 | 20.74 Mn |
| Mar 31, 2022 | 66.46 Mn |
| Dec 31, 2021 | 13.71 Mn |
| Sep 30, 2021 | 17.08 Mn |
API Access
Prokidney 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=PROK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PROK", "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=PROK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();