Relmada Therapeutics (RLMD) Net Long-Term Debt Issued (Repaid) (2014 - 2020)
Relmada Therapeutics' Net Long-Term Debt Issued (Repaid) came in at -$50,000 for FY2022.
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Analysis
Relmada Therapeutics (RLMD) Net Long-Term Debt Issued (Repaid) (2014 - 2020) Analysis & Trends
Going back to FY2014, Relmada Therapeutics' Net Long-Term Debt Issued (Repaid) data covers 8 years.
- The FY2022 figure represents the highest annual Net Long-Term Debt Issued (Repaid) since FY2018.
- Per Business Quant, earlier years put Net Long-Term Debt Issued (Repaid) at -$110,247 in FY2020, -$368,695 in FY2019 and $6.53 million in FY2018.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Net LT Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,264.65 Bn | 1,238.27 Bn | 20.46 Bn | - |
| 2 | Johnson & Johnson | 677.74 Bn | 597.60 Bn | 17.30 Bn | -1.00 Mn |
| 3 | AbbVie | 517.10 Bn | 485.11 Bn | 13.12 Bn | 9.98 Bn |
| 4 | Merck | 362.23 Bn | 325.17 Bn | 13.19 Bn | - |
| 5 | Novartis Ag | 315.90 Bn | 276.16 Bn | 11.24 Bn | 1.96 Bn |
| 6 | Astrazeneca | 289.40 Bn | 266.24 Bn | 12.86 Bn | - |
| 7 | Amgen | 249.90 Bn | 201.56 Bn | 7.58 Bn | -3.05 Bn |
| 8 | Gilead Sciences | 209.15 Bn | 184.26 Bn | 6.73 Bn | -19.00 Mn |
| 9 | Pfizer | 165.88 Bn | 113.23 Bn | 12.56 Bn | - |
| 10 | Relmada Therapeutics | 473.10 Mn | -85.48 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2020 | -110,247.00 |
| Dec 31, 2019 | 2,444.00 |
| Sep 30, 2019 | -108,279.00 |
| Mar 31, 2019 | -85,969.00 |
| Dec 31, 2018 | -85,466.00 |
| Sep 30, 2018 | -84,966.00 |
| Mar 31, 2018 | -56,655.00 |
| Dec 31, 2017 | 2.39 Mn |
| Sep 30, 2017 | 3.96 Mn |
| Jun 30, 2017 | -27,583.00 |
| Mar 31, 2017 | -82,450.00 |
| Dec 31, 2016 | -54,403.00 |
| Sep 30, 2016 | -109,234.00 |
| Mar 31, 2016 | -88,533.00 |
| Dec 31, 2015 | -87,915.00 |
| Sep 30, 2015 | -87,304.00 |
| Jun 30, 2015 | 1.00 |
| Sep 30, 2014 | -148,441.00 |
API Access
Relmada Therapeutics Net Long-Term Debt Issued (Repaid) 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=non-current-debt&ticker=RLMD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-debt", "ticker": "RLMD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-current-debt&ticker=RLMD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();