Gilead Sciences (GILD) Change in Inventory (2009 - 2026)
Gilead Sciences' Change in Inventory came in at $145 million for Q2 2026, down 17.1% from $175 million a year earlier but up 178.8% from the prior quarter.
Gilead Sciences (GILD) Change in Inventory (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Gilead Sciences reported Change in Inventory of $835 million, up 17.8% year-over-year; for FY2025, it came in at $1.04 billion, up 143.2% from FY2024.
- Change in Inventory carries a five-year compound annual growth rate of 39.7% (FY2020 to FY2025).
- Going back by year, Change in Inventory was $426 million in FY2024 (-49.4%), $842 million in FY2023 (+171.6%), $310 million in FY2022 and -$11 million in FY2021.
- The five-year range for quarterly Change in Inventory is -$70 million (Q3 2021) to $515 million (Q3 2025).
- Year-over-year, Change in Inventory has declined for three consecutive quarters, with growth averaging 111.2% over the last eight quarters.
- The fastest year-over-year change in Change in Inventory over five years came in Q3 2025 (growth of 505.9%), and the weakest in Q1 2024 (a decline of 80.2%).
- Business Quant data shows GILD's Change in Inventory at $52 million (Q1 2026), $123 million (Q4 2025) and $515 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,230.11 Bn | 1,198.70 Bn | 19.71 Bn | - |
| 2 | Johnson & Johnson | 644.39 Bn | 564.25 Bn | 17.30 Bn | 150.00 Mn |
| 3 | AbbVie | 503.52 Bn | 476.68 Bn | 12.70 Bn | 143.00 Mn |
| 4 | Merck | 363.29 Bn | 317.72 Bn | 12.21 Bn | - |
| 5 | Novartis Ag | 298.23 Bn | 262.62 Bn | 11.24 Bn | - |
| 6 | Astrazeneca | 267.53 Bn | 241.29 Bn | 12.86 Bn | - |
| 7 | Amgen | 241.80 Bn | 197.20 Bn | 7.24 Bn | 31.00 Mn |
| 8 | Gilead Sciences | 195.07 Bn | 169.19 Bn | 6.22 Bn | 145.00 Mn |
| 9 | Pfizer | 173.33 Bn | 120.28 Bn | 10.94 Bn | - |
| 10 | Vertex Pharmaceuticals | 135.58 Bn | 107.59 Bn | 2.84 Bn | 27.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 145.00 Mn |
| Mar 31, 2026 | 52.00 Mn |
| Dec 31, 2025 | 123.00 Mn |
| Sep 30, 2025 | 515.00 Mn |
| Jun 30, 2025 | 175.00 Mn |
| Mar 31, 2025 | 223.00 Mn |
| Dec 31, 2024 | 226.00 Mn |
| Sep 30, 2024 | 85.00 Mn |
| Jun 30, 2024 | 70.00 Mn |
| Mar 31, 2024 | 45.00 Mn |
| Dec 31, 2023 | 307.00 Mn |
| Sep 30, 2023 | 82.00 Mn |
| Jun 30, 2023 | 226.00 Mn |
| Mar 31, 2023 | 227.00 Mn |
| Dec 31, 2022 | 276.00 Mn |
| Sep 30, 2022 | 95.00 Mn |
| Jun 30, 2022 | -8.00 Mn |
| Mar 31, 2022 | -53.00 Mn |
| Dec 31, 2021 | -35.00 Mn |
| Sep 30, 2021 | -70.00 Mn |
Gilead Sciences Change in Inventory 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-inventory&ticker=GILD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-inventory", "ticker": "GILD", "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-inventory&ticker=GILD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();