Kiniksa Pharmaceuticals International (KNSA) Accumulated Expenses (2017 - 2026)
Kiniksa Pharmaceuticals International (KNSA) posted Accumulated Expenses of $46.73 million for Q2 2026, up 30.0% from $35.96 million a year earlier and up 42.6% from the prior quarter.
Kiniksa Pharmaceuticals International (KNSA) Accumulated Expenses (2017 - 2026) Analysis & Trends
At the end of FY2025, Kiniksa Pharmaceuticals International's Accumulated Expenses came in at $42.02 million, up 29.9% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 7.6% (FY2020 to FY2025).
- In prior years, Kiniksa Pharmaceuticals International's Accumulated Expenses was $32.36 million in FY2024 (+16.7%), $27.73 million in FY2023 (-7.9%), $30.11 million in FY2022 (-20.8%) and $38.03 million in FY2021 (+30.2%).
- The Q2 2026 figure stands as the highest quarterly Accumulated Expenses in data going back to Q4 2017.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last three quarters, with growth averaging 7.1% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q1 2024, with growth of 114.1%; the weakest was Q1 2025, with a decline of 50.5%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $32.77 million (Q1 2026), $42.02 million (Q4 2025) and $30.94 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn |
| 10 | Kiniksa Pharmaceuticals International | 11.64 Bn | 10.38 Bn | 220.03 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.73 Mn |
| Mar 31, 2026 | 32.77 Mn |
| Dec 31, 2025 | 42.02 Mn |
| Sep 30, 2025 | 30.94 Mn |
| Jun 30, 2025 | 35.96 Mn |
| Mar 31, 2025 | 22.13 Mn |
| Dec 31, 2024 | 32.36 Mn |
| Sep 30, 2024 | 40.38 Mn |
| Jun 30, 2024 | 33.37 Mn |
| Mar 31, 2024 | 44.72 Mn |
| Dec 31, 2023 | 27.73 Mn |
| Sep 30, 2023 | 41.15 Mn |
| Jun 30, 2023 | 35.32 Mn |
| Mar 31, 2023 | 20.89 Mn |
| Dec 31, 2022 | 30.11 Mn |
| Sep 30, 2022 | 30.87 Mn |
| Jun 30, 2022 | 34.50 Mn |
| Mar 31, 2022 | 38.89 Mn |
| Dec 31, 2021 | 38.03 Mn |
| Sep 30, 2021 | 28.53 Mn |
Kiniksa Pharmaceuticals International Accumulated 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=accumulated-expenses&ticker=KNSA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "KNSA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=KNSA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();