Ocular Therapeutix (OCUL) Total Liabilities (2013 - 2026)
Ocular Therapeutix's Total Liabilities came in at $151.28 million for Q2 2026, up 4.0% from $145.42 million a year earlier and up 0.2% from the prior quarter.
Ocular Therapeutix (OCUL) Total Liabilities (2013 - 2026) Analysis & Trends
At the end of FY2025, Ocular Therapeutix's Total Liabilities was $153.75 million, up 7.8% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of -3.7% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $142.59 million in FY2024 (-11.4%), $160.93 million in FY2023 (+41.3%), $113.91 million in FY2022 (-2.5%) and $116.89 million in FY2021 (-37.1%).
- The five-year range for quarterly Total Liabilities is $107.27 million (Q2 2022) to $160.93 million (Q4 2023).
- Year-over-year, Total Liabilities has increased for six consecutive quarters, with growth averaging 2.4% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q4 2023 (growth of 41.3%), and the weakest in Q4 2021 (a decline of 37.1%).
- Business Quant data shows OCUL's Total Liabilities at $150.96 million (Q1 2026), $153.75 million (Q4 2025) and $152.65 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 653.54 Bn | 572.07 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 467.01 Bn | 440.17 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.16 Bn | 321.59 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 277.56 Bn | 233.43 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 258.23 Bn | 231.79 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 224.14 Bn | 179.54 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 187.30 Bn | 161.42 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.47 Bn | 110.41 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.31 Bn | 105.31 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Ocular Therapeutix | 2.12 Bn | 2.12 Bn | 11.46 Mn | 151.28 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 151.28 Mn |
| Mar 31, 2026 | 150.96 Mn |
| Dec 31, 2025 | 153.75 Mn |
| Sep 30, 2025 | 152.65 Mn |
| Jun 30, 2025 | 145.42 Mn |
| Mar 31, 2025 | 139.99 Mn |
| Dec 31, 2024 | 142.59 Mn |
| Sep 30, 2024 | 138.35 Mn |
| Jun 30, 2024 | 139.40 Mn |
| Mar 31, 2024 | 130.96 Mn |
| Dec 31, 2023 | 160.93 Mn |
| Sep 30, 2023 | 154.53 Mn |
| Jun 30, 2023 | 119.47 Mn |
| Mar 31, 2023 | 118.86 Mn |
| Dec 31, 2022 | 113.91 Mn |
| Sep 30, 2022 | 112.35 Mn |
| Jun 30, 2022 | 107.27 Mn |
| Mar 31, 2022 | 107.83 Mn |
| Dec 31, 2021 | 116.89 Mn |
| Sep 30, 2021 | 130.40 Mn |
Ocular Therapeutix 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=OCUL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "OCUL", "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=OCUL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();