Cartesian Therapeutics (RNAC) Long-Term Debt Repayments (2015 - 2023)
Cartesian Therapeutics' Long-Term Debt Repayments came in at $27.46 million for FY2023.
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Analysis
Cartesian Therapeutics (RNAC) Long-Term Debt Repayments (2015 - 2023) Analysis & Trends
Going back to FY2015, Cartesian Therapeutics' Long-Term Debt Repayments data covers 5 years.
- Long-Term Debt Repayments carries a four-year compound annual growth rate of 77.0% (FY2019 to FY2023).
- The FY2023 figure represents the highest annual Long-Term Debt Repayments in data going back to FY2015.
- Per Business Quant, earlier years put Long-Term Debt Repayments at $19.31 million in FY2020 (+589.8%) and $2.8 million in FY2019.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,165.22 Bn | 1,133.81 Bn | 19.71 Bn | 873.00 Mn |
| 2 | Johnson & Johnson | 646.28 Bn | 566.14 Bn | 17.30 Bn | 1.00 Mn |
| 3 | AbbVie | 503.17 Bn | 476.28 Bn | 12.70 Bn | 2.00 Bn |
| 4 | Merck | 365.23 Bn | 319.60 Bn | 12.21 Bn | 5.00 Mn |
| 5 | Novartis Ag | 302.66 Bn | 266.65 Bn | 11.24 Bn | 20.00 Mn |
| 6 | Astrazeneca | 267.39 Bn | 241.08 Bn | 12.86 Bn | 2.46 Bn |
| 7 | Amgen | 241.61 Bn | 197.01 Bn | 7.24 Bn | - |
| 8 | Gilead Sciences | 194.67 Bn | 168.86 Bn | 6.22 Bn | 17.00 Mn |
| 9 | Pfizer | 172.91 Bn | 119.55 Bn | 10.94 Bn | - |
| 10 | Cartesian Therapeutics | 188.59 Mn | -346.18 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2023 | 24.87 Mn |
| Sep 30, 2020 | 15.11 Mn |
| Jun 30, 2020 | 2.10 Mn |
| Mar 31, 2020 | 2.10 Mn |
| Dec 31, 2019 | 2.10 Mn |
| Sep 30, 2019 | 700,000.00 |
| Sep 30, 2017 | 11.10 Mn |
| Jun 30, 2017 | 1.11 Mn |
| Mar 31, 2017 | 728,000.00 |
| Dec 31, 2015 | 717,000.00 |
| Sep 30, 2015 | 703,000.00 |
API Access
Cartesian Therapeutics Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=RNAC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "ticker": "RNAC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=long-term-debt-repayments&ticker=RNAC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();