Cogent Biosciences (COGT) Total Liabilities (2017 - 2026)
Cogent Biosciences (COGT) recorded Total Liabilities of $302.16 million in Q2 2026, up 152.3% from $119.78 million a year earlier and up 2.3% from the prior quarter.
Cogent Biosciences (COGT) Total Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2025, Cogent Biosciences reported Total Liabilities of $301.24 million, up 320.7% from FY2024.
- Annual Total Liabilities has increased for five straight years, with a five-year compound annual growth rate of 79.3% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $71.61 million in FY2024 (+28.7%), $55.64 million in FY2023 (+23.4%), $45.08 million in FY2022 (+151.7%) and $17.91 million in FY2021 (+10.2%).
- The Q2 2026 figure is the highest quarterly Total Liabilities in data going back to Q4 2017.
- On a year-over-year basis, Total Liabilities has increased for 12 consecutive quarters, with growth averaging 137.4% over the last eight quarters.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 355.7% in Q1 2026, against a decline of 88.8% in Q3 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $295.31 million (Q1 2026), $301.24 million (Q4 2025) and $123.47 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Cogent Biosciences | 5.47 Bn | 5.47 Bn | - | 302.16 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 302.16 Mn |
| Mar 31, 2026 | 295.31 Mn |
| Dec 31, 2025 | 301.24 Mn |
| Sep 30, 2025 | 123.47 Mn |
| Jun 30, 2025 | 119.78 Mn |
| Mar 31, 2025 | 64.80 Mn |
| Dec 31, 2024 | 71.61 Mn |
| Sep 30, 2024 | 69.36 Mn |
| Jun 30, 2024 | 56.71 Mn |
| Mar 31, 2024 | 53.78 Mn |
| Dec 31, 2023 | 55.64 Mn |
| Sep 30, 2023 | 52.55 Mn |
| Jun 30, 2023 | 43.94 Mn |
| Mar 31, 2023 | 39.64 Mn |
| Dec 31, 2022 | 45.08 Mn |
| Sep 30, 2022 | 41.62 Mn |
| Jun 30, 2022 | 46.67 Mn |
| Mar 31, 2022 | 19.01 Mn |
| Dec 31, 2021 | 17.91 Mn |
| Sep 30, 2021 | 18.15 Mn |
Cogent Biosciences 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=COGT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "COGT", "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=COGT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();