Processa Pharmaceuticals (PCSA) Total Non-Current Liabilities (2012 - 2023)
Processa Pharmaceuticals' Total Non-Current Liabilities was $608,484 in Q4 2023, down 36.6% from $960,110 a year earlier and down 16.2% from the prior quarter.
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Analysis
Processa Pharmaceuticals (PCSA) Total Non-Current Liabilities (2012 - 2023) Analysis & Trends
From Q4 2012 onward, Processa Pharmaceuticals has reported Total Non-Current Liabilities for 26 quarters.
- Total Non-Current Liabilities shows a three-year compound annual growth rate of -31.3% (FY2020 to FY2023).
- In earlier years, Total Non-Current Liabilities was $960,110 in FY2022 (+66.0%), $578,405 in FY2021 (-69.2%) and $1.87 million in FY2020.
- The Q4 2023 figure marks the lowest quarterly Total Non-Current Liabilities since Q4 2021.
- Compared with a year earlier, Total Non-Current Liabilities has declined for three straight quarters, with growth averaging 9.6% over the last eight quarters.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q1 2023 (growth of 216.5%); the worst was Q4 2021 (a decline of 69.2%).
- Per Business Quant data, PCSA's Total Non-Current Liabilities in the three quarters before Q4 2023 was $725,847 (Q3 2023), $741,741 (Q2 2023) and $2.1 million (Q1 2023).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.97 Bn | 1,105.55 Bn | 19.71 Bn | 60.66 Bn |
| 2 | Johnson & Johnson | 619.72 Bn | 538.25 Bn | 17.26 Bn | 105.50 Bn |
| 3 | AbbVie | 503.40 Bn | 476.52 Bn | 12.70 Bn | 106.45 Bn |
| 4 | Merck | 370.15 Bn | 324.53 Bn | 12.21 Bn | 80.25 Bn |
| 5 | Novartis Ag | 298.64 Bn | 262.63 Bn | 11.24 Bn | 48.34 Bn |
| 6 | Astrazeneca | 261.07 Bn | 234.76 Bn | 12.86 Bn | 33.91 Bn |
| 7 | Amgen | 237.00 Bn | 192.40 Bn | 7.24 Bn | 78.66 Bn |
| 8 | Gilead Sciences | 191.24 Bn | 165.43 Bn | 6.22 Bn | 35.10 Bn |
| 9 | Pfizer | 170.31 Bn | 116.96 Bn | 10.94 Bn | 97.04 Bn |
| 10 | Processa Pharmaceuticals | 4.81 Mn | -8.93 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | 608,484.00 |
| Sep 30, 2023 | 725,847.00 |
| Jun 30, 2023 | 741,741.00 |
| Mar 31, 2023 | 2.10 Mn |
| Dec 31, 2022 | 960,110.00 |
| Sep 30, 2022 | 775,440.00 |
| Jun 30, 2022 | 986,723.00 |
| Mar 31, 2022 | 663,926.00 |
| Dec 31, 2021 | 578,405.00 |
| Sep 30, 2021 | 1.42 Mn |
| Jun 30, 2021 | 1.50 Mn |
| Mar 31, 2021 | 1.60 Mn |
| Dec 31, 2020 | 1.87 Mn |
| Jun 30, 2018 | 3.13 Mn |
| Dec 31, 2017 | 2.60 Mn |
| Sep 30, 2015 | 27,507.00 |
| Jun 30, 2015 | 104,948.00 |
| Mar 31, 2015 | 119,446.00 |
| Dec 31, 2014 | 494,066.00 |
| Sep 30, 2014 | 1.97 Mn |
API Access
Processa Pharmaceuticals 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=PCSA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "PCSA", "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=PCSA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();