Codexis (CDXS) Total Non-Current Liabilities (2009 - 2026)
Codexis (CDXS) reported Total Non-Current Liabilities of $91.62 million for Q3 2026, up 8.9% from $84.11 million a year earlier and up 6.8% from the prior quarter.
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Analysis
Codexis (CDXS) Total Non-Current Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Codexis posted Total Non-Current Liabilities of $95.94 million, up 18.7% from FY2024.
- Total Non-Current Liabilities has a five-year compound annual growth rate of 13.8% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $80.82 million in FY2024 (+65.9%), $48.71 million in FY2023 (-53.3%), $104.23 million in FY2022 (+29.2%) and $80.68 million in FY2021 (+60.5%).
- Five-year quarterly Total Non-Current Liabilities spans a low of $48.71 million in Q4 2023 and a high of $104.23 million in Q4 2022.
- Year over year, Total Non-Current Liabilities has now increased in each of the last nine quarters, with growth averaging 19.1% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q4 2024 (growth of 65.9%); the low point was Q4 2023 (a decline of 53.3%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $85.75 million (Q2 2026), $84.8 million (Q1 2026) and $95.94 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 54.88 Bn |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | - |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 33.44 Bn |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 2.53 Bn |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 38.93 Bn |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 20.68 Bn |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 17.15 Bn |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 2.26 Bn |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 17.66 Bn |
| 10 | Codexis | 127.04 Mn | -143.91 Mn | 15.25 Mn | 91.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 91.62 Mn |
| Jun 30, 2026 | 85.75 Mn |
| Mar 31, 2026 | 84.80 Mn |
| Dec 31, 2025 | 95.94 Mn |
| Sep 30, 2025 | 84.11 Mn |
| Jun 30, 2025 | 81.32 Mn |
| Mar 31, 2025 | 77.98 Mn |
| Dec 31, 2024 | 80.82 Mn |
| Sep 30, 2024 | 73.50 Mn |
| Jun 30, 2024 | 69.30 Mn |
| Mar 31, 2024 | 69.04 Mn |
| Dec 31, 2023 | 48.71 Mn |
| Sep 30, 2023 | 61.73 Mn |
| Jun 30, 2023 | 81.23 Mn |
| Mar 31, 2023 | 90.66 Mn |
| Dec 31, 2022 | 104.23 Mn |
| Sep 30, 2022 | 79.80 Mn |
| Jun 30, 2022 | 74.17 Mn |
| Mar 31, 2022 | 75.31 Mn |
| Dec 31, 2021 | 80.68 Mn |
API Access
Codexis 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=CDXS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "CDXS", "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=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();