Erasca (ERAS) Total Current Liabilities (2020 - 2026)
Erasca (ERAS) posted Total Current Liabilities of $33.57 million for Q2 2026, up 19.3% from $28.15 million a year earlier and up 25.9% from the prior quarter.
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Analysis
Erasca (ERAS) Total Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Erasca's Total Current Liabilities came in at $28.51 million, down 9.2% from FY2024.
- Annual Total Current Liabilities shows a five-year compound annual growth rate of 15.8% (FY2020 to FY2025).
- In prior years, Erasca's Total Current Liabilities was $31.4 million in FY2024 (+20.0%), $26.16 million in FY2023 (-46.3%), $48.69 million in FY2022 (+85.7%) and $26.22 million in FY2021 (+91.7%).
- The Q2 2026 figure stands as the highest quarterly Total Current Liabilities since Q4 2022.
- On a year-over-year basis, Total Current Liabilities increased in five of the last eight quarters, with growth averaging 5.0%.
- The strongest year-over-year quarter for Total Current Liabilities in the past five years was Q4 2021, with growth of 91.7%; the weakest was Q4 2023, with a decline of 46.3%.
- According to Business Quant data, Total Current Liabilities for the three prior quarters was $26.66 million (Q1 2026), $28.51 million (Q4 2025) and $28.71 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 54.90 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 41.64 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 27.73 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 31.75 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -31.55 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 25.50 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 11.02 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 32.65 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 3.94 Bn |
| 10 | Erasca | 4.42 Bn | 4.42 Bn | - | 33.57 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 33.57 Mn |
| Mar 31, 2026 | 26.66 Mn |
| Dec 31, 2025 | 28.51 Mn |
| Sep 30, 2025 | 28.71 Mn |
| Jun 30, 2025 | 28.15 Mn |
| Mar 31, 2025 | 25.47 Mn |
| Dec 31, 2024 | 31.40 Mn |
| Sep 30, 2024 | 30.03 Mn |
| Jun 30, 2024 | 24.89 Mn |
| Mar 31, 2024 | 30.24 Mn |
| Dec 31, 2023 | 26.16 Mn |
| Sep 30, 2023 | 26.73 Mn |
| Jun 30, 2023 | 23.29 Mn |
| Mar 31, 2023 | 25.52 Mn |
| Dec 31, 2022 | 48.69 Mn |
| Sep 30, 2022 | 27.68 Mn |
| Jun 30, 2022 | 22.32 Mn |
| Mar 31, 2022 | 21.39 Mn |
| Dec 31, 2021 | 26.22 Mn |
| Sep 30, 2021 | 19.59 Mn |
API Access
Erasca Total 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-current-liabilities&ticker=ERAS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-current-liabilities&ticker=ERAS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();