Tarsus Pharmaceuticals (TARS) Total Non-Current Liabilities (2019 - 2026)
Tarsus Pharmaceuticals (TARS) reported Total Non-Current Liabilities of $248.52 million for Q2 2026, up 15.0% from the prior quarter.
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Analysis
Tarsus Pharmaceuticals (TARS) Total Non-Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Tarsus Pharmaceuticals posted Total Non-Current Liabilities of $208.13 million, up 36.5% from FY2024.
- Total Non-Current Liabilities has increased for five consecutive years, with a five-year compound annual growth rate of 107.7% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $152.46 million in FY2024 (+128.4%), $66.76 million in FY2023 (+91.5%), $34.86 million in FY2022 (+203.7%) and $11.48 million in FY2021 (+113.1%).
- The Q2 2026 figure ranks as the highest quarterly Total Non-Current Liabilities in data going back to Q4 2019.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q3 2022 (growth of 224.4%); the low point was Q3 2021 (a decline of 90.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $216.11 million (Q1 2026), $208.13 million (Q4 2025) and $189.33 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 645.01 Bn | 563.54 Bn | 17.26 Bn | 105.99 Bn |
| 2 | AbbVie | 465.23 Bn | 438.39 Bn | 12.70 Bn | 106.45 Bn |
| 3 | Merck | 368.40 Bn | 322.83 Bn | 12.21 Bn | 80.25 Bn |
| 4 | Novartis Ag | 278.02 Bn | 233.89 Bn | 11.24 Bn | 48.34 Bn |
| 5 | Astrazeneca | 254.57 Bn | 228.13 Bn | 12.86 Bn | -967.00 Mn |
| 6 | Amgen | 229.02 Bn | 184.42 Bn | 7.24 Bn | 81.11 Bn |
| 7 | Gilead Sciences | 187.74 Bn | 161.85 Bn | 6.22 Bn | 36.04 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 100.86 Bn |
| 9 | Vertex Pharmaceuticals | 133.45 Bn | 105.45 Bn | 2.84 Bn | 5.92 Bn |
| 10 | Tarsus Pharmaceuticals | 3.32 Bn | 2.26 Bn | 161.80 Mn | 248.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 248.52 Mn |
| Mar 31, 2026 | 216.11 Mn |
| Dec 31, 2025 | 208.13 Mn |
| Sep 30, 2025 | 189.33 Mn |
| Dec 31, 2024 | 152.46 Mn |
| Sep 30, 2024 | 137.58 Mn |
| Jun 30, 2024 | 123.15 Mn |
| Mar 31, 2024 | 72.46 Mn |
| Dec 31, 2023 | 66.76 Mn |
| Sep 30, 2023 | 52.96 Mn |
| Jun 30, 2023 | 39.37 Mn |
| Mar 31, 2023 | 37.77 Mn |
| Dec 31, 2022 | 34.86 Mn |
| Sep 30, 2022 | 33.63 Mn |
| Jun 30, 2022 | 30.98 Mn |
| Mar 31, 2022 | 31.79 Mn |
| Dec 31, 2021 | 11.48 Mn |
| Sep 30, 2021 | 10.37 Mn |
| Jun 30, 2021 | 10.46 Mn |
| Mar 31, 2021 | 10.12 Mn |
API Access
Tarsus Pharmaceuticals Total Non-Current 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-non-current-liabilities&ticker=TARS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-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-non-current-liabilities&ticker=TARS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();