ClearPoint Neuro (CLPT) Total Liabilities (2011 - 2026)
ClearPoint Neuro (CLPT) posted Total Liabilities of $85.46 million for Q3 2026, up 92.1% from $44.48 million a year earlier and up 12.5% from the prior quarter.
ClearPoint Neuro (CLPT) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, ClearPoint Neuro's Total Liabilities came in at $69.73 million, up 405.3% from FY2024.
- Annual Total Liabilities shows a five-year compound annual growth rate of 20.8% (FY2020 to FY2025).
- In prior years, ClearPoint Neuro's Total Liabilities was $13.8 million in FY2024 (-35.8%), $21.49 million in FY2023 (+15.5%), $18.6 million in FY2022 (+10.8%) and $16.79 million in FY2021 (-38.1%).
- The Q3 2026 figure stands as the highest quarterly Total Liabilities in data going back to Q4 2011.
- On a year-over-year basis, Total Liabilities has increased in each of the last six quarters, with growth averaging 192.3% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q1 2026, with growth of 639.6%; the weakest was Q1 2025, with a decline of 47.1%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $75.97 million (Q2 2026), $74.58 million (Q1 2026) and $69.73 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 267.71 Bn | 244.23 Bn | 5.13 Bn | 59.47 Bn |
| 2 | Abbott Laboratories | 191.69 Bn | 165.56 Bn | 7.39 Bn | 56.62 Bn |
| 3 | Danaher | 166.18 Bn | 145.83 Bn | 3.84 Bn | 39.65 Bn |
| 4 | Intuitive Surgical | 161.07 Bn | 141.36 Bn | 2.08 Bn | 3.23 Bn |
| 5 | Medtronic | 131.65 Bn | 96.90 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 125.25 Bn | 111.44 Bn | 4.25 Bn | 23.79 Bn |
| 7 | Boston Scientific | 63.85 Bn | 59.29 Bn | 3.43 Bn | 19.59 Bn |
| 8 | Edwards Lifesciences | 60.52 Bn | 43.72 Bn | 1.35 Bn | 3.18 Bn |
| 9 | Becton Dickinson | 59.08 Bn | 56.23 Bn | 2.32 Bn | 26.32 Bn |
| 10 | ClearPoint Neuro | 284.74 Mn | 127.61 Mn | 7.06 Mn | 85.46 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 85.46 Mn |
| Jun 30, 2026 | 75.97 Mn |
| Mar 31, 2026 | 74.58 Mn |
| Dec 31, 2025 | 69.73 Mn |
| Sep 30, 2025 | 44.48 Mn |
| Jun 30, 2025 | 43.13 Mn |
| Mar 31, 2025 | 10.08 Mn |
| Dec 31, 2024 | 13.80 Mn |
| Sep 30, 2024 | 11.19 Mn |
| Jun 30, 2024 | 20.44 Mn |
| Mar 31, 2024 | 19.05 Mn |
| Dec 31, 2023 | 21.49 Mn |
| Sep 30, 2023 | 19.74 Mn |
| Jun 30, 2023 | 20.23 Mn |
| Mar 31, 2023 | 17.67 Mn |
| Dec 31, 2022 | 18.60 Mn |
| Sep 30, 2022 | 17.86 Mn |
| Jun 30, 2022 | 17.42 Mn |
| Mar 31, 2022 | 16.04 Mn |
| Dec 31, 2021 | 16.79 Mn |
ClearPoint Neuro 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=CLPT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "CLPT", "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=CLPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();