Tarsus Pharmaceuticals (TARS) Total Non-Current Liabilities (2019 - 2026)
Tarsus Pharmaceuticals (TARS) reported Total Non-Current Liabilities of $252.39 million for Q3 2026, up 33.3% from $189.33 million a year earlier and up 1.6% 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 Q3 2026 figure ranks as the highest quarterly Total Non-Current Liabilities in data going back to Q4 2019.
- Over the past five years, the year-over-year growth in Total Non-Current Liabilities ranged from 18.8% (Q1 2023) to 224.4% (Q3 2022).
- Per Business Quant data, the three quarters before Q3 2026 came in at $248.52 million (Q2 2026), $216.11 million (Q1 2026) and $208.13 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,264.65 Bn | 1,238.27 Bn | 20.46 Bn | 60.81 Bn |
| 2 | Johnson & Johnson | 677.74 Bn | 597.60 Bn | 17.30 Bn | 102.65 Bn |
| 3 | AbbVie | 517.10 Bn | 485.11 Bn | 13.12 Bn | 117.60 Bn |
| 4 | Merck | 362.23 Bn | 325.17 Bn | 13.19 Bn | 79.95 Bn |
| 5 | Novartis Ag | 315.90 Bn | 276.16 Bn | 11.24 Bn | 48.34 Bn |
| 6 | Astrazeneca | 289.40 Bn | 266.24 Bn | 12.86 Bn | 33.91 Bn |
| 7 | Amgen | 249.90 Bn | 201.56 Bn | 7.58 Bn | 76.12 Bn |
| 8 | Gilead Sciences | 209.15 Bn | 184.26 Bn | 6.73 Bn | 36.05 Bn |
| 9 | Pfizer | 165.88 Bn | 113.23 Bn | 12.56 Bn | 96.04 Bn |
| 10 | Tarsus Pharmaceuticals | 3.35 Bn | 2.41 Bn | 180.68 Mn | 252.39 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 252.39 Mn |
| 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 |
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();