Repligen (RGEN) Total Non-Current Liabilities (2011 - 2026)
Repligen's Total Non-Current Liabilities was $821.06 million in Q2 2026, up 14.5% from $716.87 million a year earlier and up 1.5% from the prior quarter.
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Analysis
Repligen (RGEN) Total Non-Current Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at Repligen came in at $707.74 million, down 3.1% from FY2024.
- Total Non-Current Liabilities shows a five-year compound annual growth rate of 66.8% (FY2020 to FY2025).
- In earlier years, Total Non-Current Liabilities was $730.16 million in FY2024 (+4.1%), $701.4 million in FY2023 (+223.7%), $216.7 million in FY2022 (-7.0%) and $233.03 million in FY2021 (+325.4%).
- The Q2 2026 figure marks the highest quarterly Total Non-Current Liabilities in data going back to Q4 2011.
- Compared with a year earlier, Total Non-Current Liabilities was higher in seven of the last eight quarters, with growth averaging 43.3%.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q4 2021 (growth of 325.4%); the worst was Q3 2021 (a decline of 49.2%).
- Per Business Quant data, RGEN's Total Non-Current Liabilities in the three quarters before Q2 2026 was $808.55 million (Q1 2026), $707.74 million (Q4 2025) and $709.49 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 55.95 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | - |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 33.25 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 40.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 21.28 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 17.56 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 2.57 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 23.92 Bn |
| 10 | Repligen | 10.85 Bn | 7.74 Bn | 110.04 Mn | 821.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 821.06 Mn |
| Mar 31, 2026 | 808.55 Mn |
| Dec 31, 2025 | 707.74 Mn |
| Sep 30, 2025 | 709.49 Mn |
| Jun 30, 2025 | 716.87 Mn |
| Mar 31, 2025 | 714.66 Mn |
| Dec 31, 2024 | 730.16 Mn |
| Sep 30, 2024 | 705.59 Mn |
| Jun 30, 2024 | 706.76 Mn |
| Mar 31, 2024 | 706.55 Mn |
| Dec 31, 2023 | 701.40 Mn |
| Sep 30, 2023 | 170.05 Mn |
| Jun 30, 2023 | 211.85 Mn |
| Mar 31, 2023 | 204.67 Mn |
| Dec 31, 2022 | 216.70 Mn |
| Sep 30, 2022 | 216.73 Mn |
| Jun 30, 2022 | 216.03 Mn |
| Mar 31, 2022 | 193.09 Mn |
| Dec 31, 2021 | 233.03 Mn |
| Sep 30, 2021 | 176.69 Mn |
API Access
Repligen 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=RGEN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "RGEN", "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=RGEN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();