Alpha Tau Medical (DRTS) Total Non-Current Liabilities (2020 - 2026)
Alpha Tau Medical's Total Non-Current Liabilities was $80.56 million in Q2 2026, up 398.1% from $16.18 million a year earlier and up 178.1% from the prior quarter.
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Analysis
Alpha Tau Medical (DRTS) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at Alpha Tau Medical came in at $18.05 million, up 21.4% from FY2024.
- Total Non-Current Liabilities shows a five-year compound annual growth rate of -20.3% (FY2020 to FY2025).
- In earlier years, Total Non-Current Liabilities was $14.86 million in FY2024 (-6.0%), $15.81 million in FY2023 (+55.7%), $10.15 million in FY2022 (-82.6%) and $58.37 million in FY2021 (+4.1%).
- The Q2 2026 figure marks the highest quarterly Total Non-Current Liabilities in data going back to Q4 2020.
- Compared with a year earlier, Total Non-Current Liabilities has increased for five straight quarters, with growth averaging 70.5% over the last eight quarters.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q2 2026 (growth of 398.1%); the worst was Q4 2022 (a decline of 82.6%).
- Per Business Quant data, DRTS's Total Non-Current Liabilities in the three quarters before Q2 2026 was $28.97 million (Q1 2026), $18.05 million (Q4 2025) and $17.97 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 54.88 Bn |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | - |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 33.44 Bn |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 2.53 Bn |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 38.93 Bn |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 20.68 Bn |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 17.15 Bn |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 2.26 Bn |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 17.66 Bn |
| 10 | Alpha Tau Medical | 1.18 Bn | 1.07 Bn | - | 80.56 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.56 Mn |
| Mar 31, 2026 | 28.97 Mn |
| Dec 31, 2025 | 18.05 Mn |
| Sep 30, 2025 | 17.97 Mn |
| Jun 30, 2025 | 16.18 Mn |
| Mar 31, 2025 | 14.84 Mn |
| Dec 31, 2024 | 14.86 Mn |
| Sep 30, 2024 | 14.98 Mn |
| Jun 30, 2024 | 15.58 Mn |
| Mar 31, 2024 | 16.38 Mn |
| Dec 31, 2023 | 15.81 Mn |
| Sep 30, 2023 | 10.65 Mn |
| Jun 30, 2023 | 13.23 Mn |
| Mar 31, 2023 | 11.55 Mn |
| Dec 31, 2022 | 10.15 Mn |
| Sep 30, 2022 | 3.35 Mn |
| Jun 30, 2022 | 2.76 Mn |
| Mar 31, 2022 | 6.30 Mn |
| Dec 31, 2021 | 58.37 Mn |
| Dec 31, 2020 | 56.05 Mn |
API Access
Alpha Tau Medical 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=DRTS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "DRTS", "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=DRTS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();