Praxis Precision Medicines (PRAX) Total Liabilities (2019 - 2026)
Praxis Precision Medicines' Total Liabilities came in at $49.06 million for Q2 2026, up 0.9% from $48.61 million a year earlier but down 2.4% from the prior quarter.
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Analysis
Praxis Precision Medicines (PRAX) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Praxis Precision Medicines' Total Liabilities was $59.77 million, up 58.7% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 30.6% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $37.66 million in FY2024 (+106.0%), $18.28 million in FY2023 (-53.2%), $39.02 million in FY2022 (-6.9%) and $41.94 million in FY2021 (+166.8%).
- The five-year range for quarterly Total Liabilities is $18.28 million (Q4 2023) to $59.77 million (Q4 2025).
- Year-over-year, Total Liabilities has increased for eight consecutive quarters, with growth averaging 66.3% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2022 (growth of 252.9%), and the weakest in Q3 2021 (a decline of 88.3%).
- Business Quant data shows PRAX's Total Liabilities at $50.24 million (Q1 2026), $59.77 million (Q4 2025) and $52.88 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
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 | Praxis Precision Medicines | 7.47 Bn | 5.06 Bn | - | 49.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 49.06 Mn |
| Mar 31, 2026 | 50.24 Mn |
| Dec 31, 2025 | 59.77 Mn |
| Sep 30, 2025 | 52.88 Mn |
| Jun 30, 2025 | 48.61 Mn |
| Mar 31, 2025 | 39.52 Mn |
| Dec 31, 2024 | 37.66 Mn |
| Sep 30, 2024 | 33.59 Mn |
| Jun 30, 2024 | 21.96 Mn |
| Mar 31, 2024 | 20.73 Mn |
| Dec 31, 2023 | 18.28 Mn |
| Sep 30, 2023 | 19.97 Mn |
| Jun 30, 2023 | 27.87 Mn |
| Mar 31, 2023 | 33.92 Mn |
| Dec 31, 2022 | 39.02 Mn |
| Sep 30, 2022 | 31.74 Mn |
| Jun 30, 2022 | 41.55 Mn |
| Mar 31, 2022 | 48.48 Mn |
| Dec 31, 2021 | 41.94 Mn |
| Sep 30, 2021 | 28.49 Mn |
API Access
Praxis Precision Medicines 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=PRAX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PRAX", "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=PRAX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();