Tarsus Pharmaceuticals (TARS) Total Liabilities (2019 - 2026)
Tarsus Pharmaceuticals (TARS) reported Total Liabilities of $264.41 million for Q2 2026, up 62.8% from $162.38 million a year earlier and up 13.9% from the prior quarter.
Tarsus Pharmaceuticals (TARS) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Tarsus Pharmaceuticals posted Total Liabilities of $218.73 million, up 43.5% from FY2024.
- Total Liabilities has increased for five consecutive years, with a five-year compound annual growth rate of 105.3% (FY2020 to FY2025).
- By year, Total Liabilities came in at $152.46 million in FY2024 (+122.6%), $68.5 million in FY2023 (+95.9%), $34.96 million in FY2022 (+187.1%) and $12.18 million in FY2021 (+103.2%).
- The Q2 2026 figure ranks as the highest quarterly Total Liabilities in data going back to Q4 2019.
- Year over year, Total Liabilities has now increased in each of the last 19 quarters, with growth averaging 77.2% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q2 2024 (growth of 202.4%); the low point was Q3 2021 (a decline of 89.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $232.18 million (Q1 2026), $218.73 million (Q4 2025) and $199.48 million (Q3 2025).
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 | Tarsus Pharmaceuticals | 3.32 Bn | 2.27 Bn | 161.80 Mn | 264.41 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 264.41 Mn |
| Mar 31, 2026 | 232.18 Mn |
| Dec 31, 2025 | 218.73 Mn |
| Sep 30, 2025 | 199.48 Mn |
| Jun 30, 2025 | 162.38 Mn |
| Mar 31, 2025 | 158.29 Mn |
| Dec 31, 2024 | 152.46 Mn |
| Sep 30, 2024 | 138.82 Mn |
| Jun 30, 2024 | 124.60 Mn |
| Mar 31, 2024 | 74.07 Mn |
| Dec 31, 2023 | 68.50 Mn |
| Sep 30, 2023 | 54.67 Mn |
| Jun 30, 2023 | 41.20 Mn |
| Mar 31, 2023 | 37.81 Mn |
| Dec 31, 2022 | 34.96 Mn |
| Sep 30, 2022 | 33.84 Mn |
| Jun 30, 2022 | 31.32 Mn |
| Mar 31, 2022 | 32.29 Mn |
| Dec 31, 2021 | 12.18 Mn |
| Sep 30, 2021 | 11.27 Mn |
Tarsus 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=TARS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "TARS", "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=TARS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();