Tg Therapeutics (TGTX) Total Liabilities (2010 - 2026)
Tg Therapeutics' Total Liabilities was $1.04 billion in Q2 2026, up 143.0% from $426.18 million a year earlier and up 9.5% from the prior quarter.
Tg Therapeutics (TGTX) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Tg Therapeutics came in at $415.23 million, up 16.9% from FY2024.
- Total Liabilities has now increased for three consecutive years, with a five-year compound annual growth rate of 31.3% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $355.33 million in FY2024 (+110.1%), $169.09 million in FY2023 (+25.3%), $134.99 million in FY2022 (-5.3%) and $142.48 million in FY2021 (+34.0%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities in data going back to Q4 2010.
- Compared with a year earlier, Total Liabilities has increased for 14 straight quarters, with growth averaging 90.7% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2026 (growth of 143.0%); the worst was Q4 2022 (a decline of 5.3%).
- Per Business Quant data, TGTX's Total Liabilities in the three quarters before Q2 2026 was $945.71 million (Q1 2026), $415.23 million (Q4 2025) and $417.81 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 645.01 Bn | 563.54 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 465.23 Bn | 438.39 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 368.40 Bn | 322.83 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 278.02 Bn | 233.89 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 254.57 Bn | 228.13 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 229.02 Bn | 184.42 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 187.74 Bn | 161.85 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.45 Bn | 105.45 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Tg Therapeutics | 8.60 Bn | 7.99 Bn | 199.14 Mn | 1.04 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.04 Bn |
| Mar 31, 2026 | 945.71 Mn |
| Dec 31, 2025 | 415.23 Mn |
| Sep 30, 2025 | 417.81 Mn |
| Jun 30, 2025 | 426.18 Mn |
| Mar 31, 2025 | 419.40 Mn |
| Dec 31, 2024 | 355.33 Mn |
| Sep 30, 2024 | 393.86 Mn |
| Jun 30, 2024 | 223.64 Mn |
| Mar 31, 2024 | 213.21 Mn |
| Dec 31, 2023 | 169.09 Mn |
| Sep 30, 2023 | 166.30 Mn |
| Jun 30, 2023 | 180.40 Mn |
| Mar 31, 2023 | 169.93 Mn |
| Dec 31, 2022 | 134.99 Mn |
| Sep 30, 2022 | 117.41 Mn |
| Jun 30, 2022 | 122.63 Mn |
| Mar 31, 2022 | 132.64 Mn |
| Dec 31, 2021 | 142.48 Mn |
| Sep 30, 2021 | 98.17 Mn |
Tg Therapeutics 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=TGTX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "TGTX", "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=TGTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();