ARS Pharmaceuticals (SPRY) Total Liabilities (2020 - 2026)
ARS Pharmaceuticals' Total Liabilities was $236.98 million in Q2 2026, up 95.6% from $121.15 million a year earlier and up 4.7% from the prior quarter.
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Analysis
ARS Pharmaceuticals (SPRY) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at ARS Pharmaceuticals came in at $213.39 million, up 126.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of -12.2% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $94.36 million in FY2024, $2.43 million in FY2023 (-71.6%), $8.55 million in FY2022 (-90.8%) and $92.72 million in FY2021 (-77.3%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities since Q3 2022.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with growth averaging 99.8% over the last four quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q1 2026 (growth of 130.1%); the worst was Q1 2023 (a decline of 97.1%).
- Per Business Quant data, SPRY's Total Liabilities in the three quarters before Q2 2026 was $226.26 million (Q1 2026), $213.39 million (Q4 2025) and $225.15 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 7.18 Bn |
| 10 | ARS Pharmaceuticals | 410.68 Mn | 266.88 Mn | 20.81 Mn | 236.98 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 236.98 Mn |
| Mar 31, 2026 | 226.26 Mn |
| Dec 31, 2025 | 213.39 Mn |
| Sep 30, 2025 | 225.15 Mn |
| Jun 30, 2025 | 121.15 Mn |
| Mar 31, 2025 | 98.34 Mn |
| Dec 31, 2024 | 94.36 Mn |
| Sep 30, 2024 | 16.62 Mn |
| Jun 30, 2024 | 6.73 Mn |
| Mar 31, 2024 | 3.72 Mn |
| Dec 31, 2023 | 2.43 Mn |
| Sep 30, 2023 | 11.27 Mn |
| Jun 30, 2023 | 10.20 Mn |
| Mar 31, 2023 | 10.04 Mn |
| Dec 31, 2022 | 8.55 Mn |
| Sep 30, 2022 | 321.22 Mn |
| Jun 30, 2022 | 338.03 Mn |
| Mar 31, 2022 | 350.72 Mn |
| Dec 31, 2021 | 92.72 Mn |
| Sep 30, 2021 | 20.43 Mn |
API Access
ARS Pharmaceuticals Total Liabilities 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=total-liabilities&ticker=SPRY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "SPRY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=SPRY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();