Vertex Pharmaceuticals (VRTX) Change in Accrued Expenses (2009 - 2026)
Vertex Pharmaceuticals' Change in Accrued Expenses was -$7.4 million in Q3 2026, compared with $332.9 million a year earlier.
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Analysis
Vertex Pharmaceuticals (VRTX) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Vertex Pharmaceuticals' Change in Accrued Expenses was -$378.9 million through Sep 30, 2026; for FY2025, it was -$116.9 million.
- In earlier years, Change in Accrued Expenses was $212.9 million in FY2024 (-50.4%), $429.4 million in FY2023 (-20.8%), $542.5 million in FY2022 (+77.6%) and $305.4 million in FY2021 (+149.9%).
- Quarterly Change in Accrued Expenses has moved between -$664.5 million (Q4 2025) and $485.5 million (Q2 2022) over five years.
- Compared with a year earlier, Change in Accrued Expenses was higher in three of the last five quarters, with growth averaging 19.8%.
- The best year-over-year quarter for Change in Accrued Expenses over five years was Q3 2022 (growth of 195.3%); the worst was Q1 2025 (a decline of 75.2%).
- Per Business Quant data, VRTX's Change in Accrued Expenses in the three quarters before Q3 2026 was $222.5 million (Q2 2026), $70.5 million (Q1 2026) and -$664.5 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,359.75 Bn | 1,333.37 Bn | 20.46 Bn | - |
| 2 | Johnson & Johnson | 688.76 Bn | 608.62 Bn | 17.30 Bn | 2.41 Bn |
| 3 | AbbVie | 521.69 Bn | 489.75 Bn | 13.12 Bn | 983.00 Mn |
| 4 | Merck | 364.31 Bn | 327.31 Bn | 13.19 Bn | - |
| 5 | Novartis Ag | 306.35 Bn | 279.93 Bn | - | - |
| 6 | Astrazeneca | 285.96 Bn | 259.56 Bn | 13.26 Bn | - |
| 7 | Amgen | 251.88 Bn | 203.53 Bn | 7.58 Bn | -87.00 Mn |
| 8 | Gilead Sciences | 208.59 Bn | 183.61 Bn | 6.73 Bn | 756.00 Mn |
| 9 | Pfizer | 164.73 Bn | 112.38 Bn | 12.56 Bn | - |
| 10 | Vertex Pharmaceuticals | 136.55 Bn | 104.28 Bn | 2.91 Bn | -7.40 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | -7.40 Mn |
| Jun 30, 2026 | 222.50 Mn |
| Mar 31, 2026 | 70.50 Mn |
| Dec 31, 2025 | -664.50 Mn |
| Sep 30, 2025 | 332.90 Mn |
| Jun 30, 2025 | 166.60 Mn |
| Mar 31, 2025 | 48.10 Mn |
| Dec 31, 2024 | -320.10 Mn |
| Sep 30, 2024 | 170.60 Mn |
| Jun 30, 2024 | 168.30 Mn |
| Mar 31, 2024 | 194.10 Mn |
| Dec 31, 2023 | -356.70 Mn |
| Sep 30, 2023 | 368.70 Mn |
| Jun 30, 2023 | 276.70 Mn |
| Mar 31, 2023 | 140.70 Mn |
| Dec 31, 2022 | -437.80 Mn |
| Sep 30, 2022 | 433.20 Mn |
| Jun 30, 2022 | 485.50 Mn |
| Mar 31, 2022 | 61.60 Mn |
| Dec 31, 2021 | 51.20 Mn |
API Access
Vertex Pharmaceuticals Change in Accrued Expenses 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=change-in-accured-expenses&ticker=VRTX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "VRTX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=VRTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();