Emmaus Life Sciences (EMMA) Total Liabilities (2010 - 2026)
Emmaus Life Sciences' Total Liabilities was $82.55 million in Q2 2026, up 4.4% from $79.05 million a year earlier but down 4.6% from the prior quarter.
Emmaus Life Sciences (EMMA) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Emmaus Life Sciences came in at $85.04 million, up 6.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 5.6% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $80.08 million in FY2024 (-3.4%), $82.94 million in FY2023 (+0.8%), $82.32 million in FY2022 (+5.3%) and $78.18 million in FY2021 (+20.9%).
- Quarterly Total Liabilities has moved between $73.79 million (Q1 2022) and $86.56 million (Q1 2026) over five years.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with growth averaging 0.3% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2021 (growth of 20.9%); the worst was Q2 2025 (a decline of 4.7%).
- Per Business Quant data, EMMA's Total Liabilities in the three quarters before Q2 2026 was $86.56 million (Q1 2026), $85.04 million (Q4 2025) and $80.24 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.97 Bn | 1,105.55 Bn | 19.71 Bn | 108.40 Bn |
| 2 | Johnson & Johnson | 619.72 Bn | 538.25 Bn | 17.26 Bn | 116.09 Bn |
| 3 | AbbVie | 503.40 Bn | 476.52 Bn | 12.70 Bn | 141.05 Bn |
| 4 | Merck | 370.15 Bn | 324.53 Bn | 12.21 Bn | 87.82 Bn |
| 5 | Novartis Ag | 298.64 Bn | 262.63 Bn | 11.24 Bn | 80.09 Bn |
| 6 | Astrazeneca | 261.07 Bn | 234.76 Bn | 12.86 Bn | 65.46 Bn |
| 7 | Amgen | 237.00 Bn | 192.40 Bn | 7.24 Bn | 83.95 Bn |
| 8 | Gilead Sciences | 191.24 Bn | 165.43 Bn | 6.22 Bn | 37.53 Bn |
| 9 | Pfizer | 170.31 Bn | 116.96 Bn | 10.94 Bn | 115.64 Bn |
| 10 | Emmaus Life Sciences | 3.51 Mn | -2.79 Mn | 5.97 Mn | 82.55 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 82.55 Mn |
| Mar 31, 2026 | 86.56 Mn |
| Dec 31, 2025 | 85.04 Mn |
| Sep 30, 2025 | 80.24 Mn |
| Jun 30, 2025 | 79.05 Mn |
| Mar 31, 2025 | 81.08 Mn |
| Dec 31, 2024 | 80.08 Mn |
| Sep 30, 2024 | 81.12 Mn |
| Jun 30, 2024 | 82.95 Mn |
| Mar 31, 2024 | 83.19 Mn |
| Dec 31, 2023 | 82.94 Mn |
| Sep 30, 2023 | 83.78 Mn |
| Jun 30, 2023 | 85.32 Mn |
| Mar 31, 2023 | 86.31 Mn |
| Dec 31, 2022 | 82.32 Mn |
| Sep 30, 2022 | 79.79 Mn |
| Jun 30, 2022 | 80.62 Mn |
| Mar 31, 2022 | 73.79 Mn |
| Dec 31, 2021 | 78.18 Mn |
| Sep 30, 2021 | 75.16 Mn |
Emmaus Life Sciences Total 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-liabilities&ticker=EMMA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "EMMA", "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-liabilities&ticker=EMMA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();