Gilead Patent Portfolio
35 US patents · Average 25 claims per patent
Technology Focus Areas
Patent Details
| Patent # | Title | Granted | Expires | Claims | Status |
|---|---|---|---|---|---|
| 10002944 | System for configurable neural network processing with lidar | Dec 5, 2006 | Aug 15, 2023 | 23 | Expired |
| 10002945 | Apparatus for advanced data encoding in AI-driven systems | Jul 21, 2020 | Apr 21, 2038 | 25 | 12.0y left |
| 10002946 | System for enhanced signal transmission in AI-driven networks | Sep 21, 2014 | Mar 6, 2030 | 38 | 3.9y left |
| 10002947 | System for multi-layer signal transmission in MEMS networks | Mar 12, 2014 | Jan 19, 2031 | 9 | 4.8y left |
| 10002948 | Apparatus for modular computational operations in MEMS environments | Aug 2, 2022 | Oct 4, 2040 | 13 | 14.5y left |
| 10002949 | Method for modular wireless communication using photonic | Jul 13, 2026 | Dec 21, 2043 | 15 | 17.7y left |
| 10002950 | Method for integrated channel estimation in photonic communications | Nov 21, 2020 | Aug 28, 2038 | 38 | 12.4y left |
| 10002951 | Apparatus for improved data encoding in 5G systems | Jul 18, 2013 | Oct 2, 2029 | 47 | 3.5y left |
| 10002952 | Method for configurable wireless communication using cloud | Jul 12, 2018 | Sep 26, 2035 | 28 | 9.5y left |
| 10002953 | Method for distributed channel estimation in RF communications | Jul 11, 2022 | Jan 10, 2038 | 11 | 11.8y left |
| 10002954 | Method for modular channel estimation in quantum communications | Jul 26, 2023 | Apr 13, 2041 | 14 | 15.0y left |
| 10002955 | Method for autonomous machine learning inference using AI-driven | Mar 15, 2011 | Apr 26, 2028 | 6 | 2.1y left |
| 10002956 | Apparatus for scalable data encoding in nano-scale systems | Feb 18, 2020 | Jul 14, 2037 | 14 | 11.3y left |
| 10002957 | System for modular neural network processing with AI-driven | Aug 9, 2004 | Sep 4, 2020 | 29 | Expired |
| 10002958 | Method for distributed channel estimation in neural communications | Feb 23, 2023 | Nov 23, 2039 | 48 | 13.6y left |
| 10002959 | Method for integrated wireless communication using digital | Aug 3, 2024 | Oct 19, 2040 | 43 | 14.5y left |
| 10002960 | Method for improved machine learning inference using AI-driven | May 13, 2019 | Sep 27, 2035 | 9 | 9.5y left |
| 10002961 | Apparatus for adaptive data encoding in edge systems | May 10, 2012 | Mar 3, 2028 | 20 | 1.9y left |
| 10002962 | Method for efficient machine learning inference using MEMS | Nov 5, 2019 | Jun 22, 2035 | 20 | 9.2y left |
| 10002963 | Computer-implemented method for scalable nano-scale optimization | Jan 13, 2003 | Sep 6, 2020 | 32 | Expired |
| 10002964 | Computer-implemented method for optimized lidar optimization | Dec 18, 2028 | Oct 8, 2044 | 49 | 18.5y left |
| 10002965 | Method for optimized machine learning inference using cloud | Mar 12, 2020 | Jun 26, 2038 | 37 | 12.2y left |
| 10002966 | Method for dynamic channel estimation in digital communications | Oct 8, 2024 | Oct 2, 2042 | 48 | 16.5y left |
| 10002967 | System for distributed neural network processing with AI-driven | Oct 4, 2015 | Nov 9, 2033 | 38 | 7.6y left |
| 10002968 | Method for low-latency channel estimation in lidar communications | Dec 12, 2027 | Jun 15, 2044 | 9 | 18.2y left |
| 10002969 | System for modular signal transmission in graphene networks | May 4, 2024 | Oct 25, 2041 | 39 | 15.6y left |
| 10002970 | System and method for efficient data processing using MEMS | Feb 23, 2025 | Jul 27, 2043 | 33 | 17.3y left |
| 10002971 | System for enhanced signal transmission in blockchain networks | Sep 22, 2024 | Apr 15, 2040 | 11 | 14.0y left |
| 10002972 | System for configurable neural network processing with RF | May 28, 2003 | Sep 27, 2021 | 22 | Expired |
| 10002973 | Computer-implemented method for adaptive nano-scale optimization | Mar 8, 2011 | Oct 26, 2027 | 28 | 1.6y left |
| 10002974 | Method for modular machine learning inference using cloud | Sep 15, 2017 | Jun 23, 2033 | 16 | 7.2y left |
| 10002975 | Apparatus for dynamic data encoding in graphene systems | Mar 22, 2027 | Aug 28, 2043 | 10 | 17.4y left |
| 10002976 | Apparatus for scalable computational operations in neural environments | Aug 27, 2020 | Sep 11, 2037 | 13 | 11.4y left |
| 10002977 | System and method for optimized data processing using blockchain | Mar 1, 2023 | Sep 24, 2039 | 37 | 13.5y left |
| 10002978 | System for improved signal transmission in photonic networks | Mar 11, 2008 | Oct 16, 2024 | 15 | Expired |
Frequently Asked Questions
Gilead holds 35 US patents with an average of 25 claims per patent. The portfolio has a Patent Strength Score of 38/100 (Grade D).
Gilead has 2 patents expiring within 2 years and 6 patents expiring within 5 years. These expirations may create opportunities for competitors and generic entrants.
Gilead's key technology focus areas include Computing & Data Processing, Telecommunications. The portfolio spans 2 distinct technology classifications (CPC codes).
The Patent Strength Score (0-100, A-F) benchmarks a company's patent portfolio quality based on portfolio size (30%), claims breadth (25%), time remaining to expiration (25%), and portfolio diversity across technology areas (20%).
Patent Strength Score is based on portfolio size, claims breadth, time to expiration, and technology diversity using CPC classifications.
The this entity record above pulls directly from the FDA Orange Book and USPTO patent records. What follows is the per-entity context — how this entity sits in the broader U.S. pharmaceutical patent expirations distribution and which underlying factors drive the headline numbers.
The methodology behind every numeric value on this page is publicly documented on the the FDA Orange Book and USPTO patent records portal and described in detail on this site’s methodology page. Refresh cadence varies by underlying series; the page surfaces the as-of date for each number so readers can trace any figure back to the source release.
Practical use of this page is in combination with the comparison and ranking pages elsewhere on the site, which surface the same data for this entity’s peers within U.S. brand-name drugs. A single-entity reading without peer context can be misleading when an entity is an outlier on one axis but typical on another.
Source: USPTO patent search, 2026.