Erasca (ERAS) Total Non-Current Liabilities (2021 - 2026)
Erasca's Total Non-Current Liabilities was $72.84 million in Q2 2026, unchanged from $72.87 million a year earlier and up 8.1% from the prior quarter.
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Analysis
Erasca (ERAS) Total Non-Current Liabilities (2021 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at Erasca came in at $70.58 million, down 10.3% from FY2024.
- Total Non-Current Liabilities shows a four-year compound annual growth rate of 12.1% (FY2021 to FY2025).
- In earlier years, Total Non-Current Liabilities was $78.67 million in FY2024 (+0.8%), $78.05 million in FY2023 (-23.8%), $102.48 million in FY2022 (+129.1%) and $44.73 million in FY2021.
- Quarterly Total Non-Current Liabilities has moved between $44.73 million (Q4 2021) and $102.48 million (Q4 2022) over five years.
- Compared with a year earlier, Total Non-Current Liabilities was higher in 1 of the last eight quarters, with an average decline of 4.9%.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q4 2022 (growth of 129.1%); the worst was Q4 2023 (a decline of 23.8%).
- Per Business Quant data, ERAS's Total Non-Current Liabilities in the three quarters before Q2 2026 was $67.37 million (Q1 2026), $70.58 million (Q4 2025) and $72.12 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 | Erasca | 4.44 Bn | 4.44 Bn | - | 72.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 72.84 Mn |
| Mar 31, 2026 | 67.37 Mn |
| Dec 31, 2025 | 70.58 Mn |
| Sep 30, 2025 | 72.12 Mn |
| Jun 30, 2025 | 72.87 Mn |
| Mar 31, 2025 | 71.49 Mn |
| Dec 31, 2024 | 78.67 Mn |
| Sep 30, 2024 | 78.51 Mn |
| Jun 30, 2024 | 74.58 Mn |
| Mar 31, 2024 | 81.05 Mn |
| Dec 31, 2023 | 78.05 Mn |
| Sep 30, 2023 | 79.67 Mn |
| Jun 30, 2023 | 77.26 Mn |
| Mar 31, 2023 | 80.46 Mn |
| Dec 31, 2022 | 102.48 Mn |
| Dec 31, 2021 | 44.73 Mn |
API Access
Erasca 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=ERAS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "ERAS", "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=ERAS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();