Emergent BioSolutions (EBS) Total Debt (2010 - 2026)
Emergent BioSolutions (EBS) reported Total Debt of $581.8 million for Q2 2026, down 12.9% from $667.8 million a year earlier but up 1.4% from the prior quarter.
Emergent BioSolutions (EBS) Total Debt (2010 - 2026) Analysis & Trends
At the end of FY2025, Emergent BioSolutions posted Total Debt of $572.1 million, down 13.8% from FY2024.
- Total Debt has declined for three consecutive years, with a five-year compound annual growth rate of -8.1% (FY2020 to FY2025).
- By year, Total Debt came in at $663.7 million in FY2024 (-22.8%), $860.2 million in FY2023 (-38.8%), $1.41 billion in FY2022 (+67.2%) and $841 million in FY2021 (-3.9%).
- Five-year quarterly Total Debt spans a low of $572.1 million in Q4 2025 and a high of $1.41 billion in Q4 2022.
- Year over year, Total Debt has now declined in each of the last three quarters, with an average decline of 16.9% over the last eight quarters.
- The high point for year-over-year Total Debt in five years was Q1 2023 (growth of 67.9%); the low point was Q4 2023 (a decline of 38.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $573.6 million (Q1 2026), $572.1 million (Q4 2025) and $663.1 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,143.52 Bn | 1,112.10 Bn | 19.71 Bn | 54.91 Bn |
| 2 | Johnson & Johnson | 622.88 Bn | 541.41 Bn | 17.26 Bn | 49.04 Bn |
| 3 | AbbVie | 510.73 Bn | 483.84 Bn | 12.70 Bn | 70.82 Bn |
| 4 | Merck | 366.08 Bn | 320.46 Bn | 12.21 Bn | 53.91 Bn |
| 5 | Novartis Ag | 297.30 Bn | 261.29 Bn | 11.24 Bn | 9.59 Bn |
| 6 | Astrazeneca | 261.27 Bn | 234.95 Bn | 12.86 Bn | 32.35 Bn |
| 7 | Amgen | 235.10 Bn | 190.50 Bn | 7.24 Bn | 57.30 Bn |
| 8 | Gilead Sciences | 193.90 Bn | 168.09 Bn | 6.22 Bn | 26.25 Bn |
| 9 | Pfizer | 171.85 Bn | 118.50 Bn | 10.94 Bn | 63.19 Bn |
| 10 | Emergent BioSolutions | 324.05 Mn | -426.85 Mn | 137.20 Mn | 581.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 581.80 Mn |
| Mar 31, 2026 | 573.60 Mn |
| Dec 31, 2025 | 572.10 Mn |
| Sep 30, 2025 | 663.10 Mn |
| Jun 30, 2025 | 667.80 Mn |
| Mar 31, 2025 | 665.70 Mn |
| Dec 31, 2024 | 663.70 Mn |
| Sep 30, 2024 | 662.60 Mn |
| Jun 30, 2024 | 862.20 Mn |
| Mar 31, 2024 | 905.90 Mn |
| Dec 31, 2023 | 860.20 Mn |
| Sep 30, 2023 | 861.80 Mn |
| Jun 30, 2023 | 903.20 Mn |
| Mar 31, 2023 | 1.40 Bn |
| Dec 31, 2022 | 1.41 Bn |
| Sep 30, 2022 | 1.05 Bn |
| Jun 30, 2022 | 825.20 Mn |
| Mar 31, 2022 | 833.10 Mn |
| Dec 31, 2021 | 841.00 Mn |
| Sep 30, 2021 | 848.90 Mn |
Emergent BioSolutions Total Debt 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-debt&ticker=EBS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-debt", "ticker": "EBS", "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-debt&ticker=EBS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();