NovaBridge Biosciences (NBP) Net Margin (2019 - 2023)
NovaBridge Biosciences (NBP) posted Net Margin of -1332200.00% for Q4 2023, down 1321642.54 percentage points from the prior quarter.
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Analysis
NovaBridge Biosciences (NBP) Net Margin (2019 - 2023) Analysis & Trends
For FY2023, NovaBridge Biosciences' Net Margin came in at -32664.40%, down 9226.23 percentage points from FY2022.
- Annual Net Margin has declined for three consecutive years, with a five-year change of -31915.37 percentage points (FY2018 to FY2023).
- In prior years, NovaBridge Biosciences' Net Margin was -23438.17% in FY2022 (-20789.43 pp), -2648.74% in FY2021 (-2679.26 pp), 30.53% in FY2020 (+4980.82 pp) and -4950.29% in FY2019 (-4201.27 pp).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Net Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 21.86% |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 21.27% |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | -8.04% |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 22.61% |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 18.81% |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 23.62% |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | -134.51% |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | -1.65% |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 32.99% |
| 10 | NovaBridge Biosciences | 149.78 Mn | 149.78 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | -1,332,200.00% |
| Sep 30, 2023 | -10,557.46% |
| Jun 30, 2023 | -0.20% |
| Dec 31, 2020 | 67.96% |
| Sep 30, 2019 | -1,640.29% |
API Access
NovaBridge Biosciences Net Margin 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=net-margin&ticker=NBP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "net-margin", "ticker": "NBP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=net-margin&ticker=NBP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();