Prothena Corp Public (PRTA) Total Liabilities (2012 - 2026)
Prothena Corp Public (PRTA) reported Total Liabilities of $15.69 million for Q2 2026, down 79.0% from $74.74 million a year earlier and down 57.9% from the prior quarter.
Prothena Corp Public (PRTA) Total Liabilities (2012 - 2026) Analysis & Trends
At the end of FY2025, Prothena Corp Public posted Total Liabilities of $46.33 million, down 23.0% from FY2024.
- Total Liabilities has declined for five consecutive years, with a five-year compound annual growth rate of -20.8% (FY2020 to FY2025).
- By year, Total Liabilities came in at $60.18 million in FY2024 (-55.4%), $135.02 million in FY2023 (-0.7%), $135.99 million in FY2022 (-5.1%) and $143.32 million in FY2021 (-3.8%).
- The Q2 2026 figure ranks as the lowest quarterly Total Liabilities since Q1 2015.
- Year over year, Total Liabilities has now declined in each of the last four quarters, with an average decline of 35.8% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q2 2025 (growth of 17.4%); the low point was Q2 2026 (a decline of 79.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $37.28 million (Q1 2026), $46.33 million (Q4 2025) and $57.64 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 | Prothena Corp Public | 420.81 Mn | -835.26 Mn | - | 15.69 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.69 Mn |
| Mar 31, 2026 | 37.28 Mn |
| Dec 31, 2025 | 46.33 Mn |
| Sep 30, 2025 | 57.64 Mn |
| Jun 30, 2025 | 74.74 Mn |
| Mar 31, 2025 | 57.66 Mn |
| Dec 31, 2024 | 60.18 Mn |
| Sep 30, 2024 | 60.89 Mn |
| Jun 30, 2024 | 63.65 Mn |
| Mar 31, 2024 | 120.80 Mn |
| Dec 31, 2023 | 135.02 Mn |
| Sep 30, 2023 | 129.69 Mn |
| Jun 30, 2023 | 138.97 Mn |
| Mar 31, 2023 | 134.18 Mn |
| Dec 31, 2022 | 135.99 Mn |
| Sep 30, 2022 | 149.79 Mn |
| Jun 30, 2022 | 142.29 Mn |
| Mar 31, 2022 | 142.53 Mn |
| Dec 31, 2021 | 143.32 Mn |
| Sep 30, 2021 | 142.23 Mn |
Prothena Corp Public 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=PRTA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PRTA", "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=PRTA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();