AI Drug Discovery Patent Landscape 2026
AI Drug Discovery Patent Landscape in 2026
The AI drug discovery patent corpus spans 52 patent families, with activity concentrated in computational chemistry and bioinformatics and no single applicant holding a dominant position. The field expanded sharply through 2020 and again in 2024–2025, though annual volume has eased from its earlier peak on a multi-year view.
Fujitsu leads a fragmented, early-stage landscape
Fujitsu Ltd holds the top position with 6 patent records, followed by Avalon Pharmaceuticals with 5 and Atomwise and the Regents of the University of Michigan each with 4. The top five filers account for 28% of the hundred largest filers’ combined total — a relatively modest share that signals an open, fragmented competitive structure rather than entrenched dominance.
No applicant commands a controlling position: a gap of only one or two patent records separates the first through fourth ranks. This thin tier-gap means incumbency is shallow and a focused filing campaign by a new entrant could rapidly alter the ranking.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Fujitsu Ltd | 6 | |
| 2 | Avalon Pharmaceuticals Inc | 5 | |
| 3 | Atomwise Inc | 4 | |
| 4 | Regents of the University of Michigan | 4 | |
| 5 | Genentech Inc | 3 | |
| 6 | Purdue Research Foundation | 3 | |
| 7 | Cosyne Therapeutics Ltd | 3 | |
| 8 | Chengdu Anticancer Biosciences Ltd | 3 | |
| 9 | GBS Global Biopharma Inc | 2 | |
| 10 | Stephen K. Horrigan | 2 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | SB Tech Inc | 2 | |
| 12 | Hunan University | 2 | |
| 13 | Hoffmann-La Roche Inc | 2 | |
| 14 | F HOFFMANN LA ROCHE & CO AG | 2 | |
| 15 | Insilico Medicine IP Ltd | 2 | |
| 16 | Daniel R. Soppet | 2 | |
| 17 | Insilico Medicine AI Limited | 2 | |
| 18 | BVRIT Hyderabad College of Engineering for Women | 1 | |
| 19 | University of Southern California | 1 | |
| 20 | Vaibhav Sharma | 1 |
The presence of both pure-play AI biotechs (Atomwise, Insilico Medicine) and large pharma and tech incumbents (Genentech, Roche entities, Fujitsu) alongside academic institutions (University of Michigan, Purdue Research Foundation) indicates the field has not yet consolidated around a single organizational model.
Filings from roughly the last 18–24 months are subject to publication lag and are likely under-represented in the current corpus; conclusions about very recent activity should be treated as provisional. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Activity surged in 2024–2025 after an earlier peak; computational chemistry dominates the technology mix
Two views together reveal where the field is heading: the annual trend shows when competitive intensity shifted, while the IPC composition shows which technical approaches are drawing the most attention.
Annual filing trend
Filings accelerated from 2018 through a 2020 peak of 8 records, softened through 2022–2023, then rebounded sharply to 8 in 2024 and 16 in 2025. The 2025 figure is almost certainly under-counted due to publication lag and should be read as a lower bound rather than a ceiling. The multi-year trajectory remains expansionary.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G16C (Computational chemistry) is the dominant IPC branch, followed by G16B (Bioinformatics) and G06N (Computing based on AI models). Healthcare informatics (G16H) and combinatorial chemistry (C40B) contribute materially. The cluster of AI-core and chemistry-core branches confirms that drug discovery work here is primarily in silico rather than wet-lab, and that machine-learning model development is still secondary to molecular modelling workflows.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
| # | Patent | Citations |
|---|---|---|
| 1 | Method and systems for phytomedicine analytics for… | 39 |
| 2 | Target molecule-ligand binding mode prediction com… | 35 |
| 3 | Systems and methods for screening compounds in sil… | 18 |
| 4 | Systems and methods for in silico drug discovery | 17 |
| 5 | System and methods for ai-enhanced cellular modeli… | 14 |
| 6 | Computer representations of peptides for efficient… | 12 |
| 7 | Graph based machine learning for generating valid … | 4 |
| 8 | Method of extracting drug information based on bio… | 4 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents.
What the patent structure means for R&D investment
The combination of fragmented ownership, computational-chemistry dominance, and a dual-peak filing trend creates distinct implications for teams evaluating where to position.
Field is in decline phase from its peak, but recent rebound complicates the read
The lifecycle stage is characterized as decline, with annual filings easing back from the 2020 peak. However, the 2024–2025 rebound — the largest single-year volume in the corpus — suggests either a second wave of interest or significant publication lag inflating recent counts. Teams should monitor 2026 actual grant data before concluding the field is contracting.
Lifecycle: DeclineLow concentration leaves the ranking open to disruption
The top five filers hold only 28% of the hundred largest filers’ combined total, and the gap between first and fourth rank is just two patent records. An applicant filing 8–10 targeted patents in a focused sub-area could plausibly enter the top three within a single filing cycle. This low barrier to ranking prominence is unusual compared with more mature technology fields.
FragmentedGenentech–Roche co-filings and Avalon multi-inventor clusters are the primary partnerships
The most active co-filing pairs are Genentech with the two Roche entities (Hoffmann-La Roche AG and Hoffmann-La Roche Inc), each pairing sharing 2 records. Avalon Pharmaceuticals appears in three separate co-filing relationships — with Paul Young, Daniel Soppet, and James Meade — each at 2 records, indicating a small-team inventor model rather than broad industry-academia consortia. No evidence of large multi-party consortia appears in the data.
Sparse collaborationUS filing dominance with meaningful PCT and European coverage
The United States is the leading jurisdiction with 23 patent records, followed by WIPO PCT filings at 15 and Europe (EPO) and India each at 6. China holds 3 records. The strong PCT presence relative to direct national filings suggests applicants are preserving international optionality rather than committing to narrow geographic strategies. India’s parity with EPO is notable and may reflect growing domestic AI-pharma activity.
US-led, PCT-hedgedGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
| Applicant | Collaborator | Co-filings |
|---|---|---|
| Genentech Inc | F. Hoffmann-La Roche AG | 2 |
| Genentech Inc | Hoffmann-La Roche Inc | 2 |
| YOUNG PAUL | Avalon Pharmaceuticals Inc | 2 |
| Daniel R. Soppet | Avalon Pharmaceuticals Inc | 2 |
| MEADE JAMES | Avalon Pharmaceuticals Inc | 2 |
Co-filing pairs, ranked by the number of jointly-filed patent families.
Fujitsu and Avalon lead, with distinct computational and pharmaceutical orientations
The top two applicants differ markedly in profile: Fujitsu is a broad-based technology company with computational chemistry emphasis, while Avalon Pharmaceuticals is a drug-focused organization. Applicant momentum data are not available for this corpus, so trajectory commentary relies on the filing trend alone.
Fujitsu Ltd
Fujitsu holds 6 patent records, the highest count in the corpus, consistent with its established position in enterprise AI and high-performance computing applied to life sciences. The company’s filing emphasis aligns with computational and AI-model branches (G16C, G06N), reflecting a platform-tool orientation rather than proprietary drug-candidate development. Specific recent trajectory data are not available in the evidence.
patent records: 6Avalon Pharmaceuticals Inc
Avalon Pharmaceuticals holds 5 patent records and appears as the anchor in three separate inventor co-filing pairs, suggesting a concentrated inventor team driving output. Its positioning closer to the drug-candidate end of the pipeline distinguishes it from technology-platform filers. Specific recent filing trajectory data are not available in the evidence.
patent records: 5Under-served branches adjacent to the computational core
Several IPC branches appear at low share relative to the dominant computational chemistry and bioinformatics clusters. These are observations of relative sparsity; only those with plausible technical relevance to AI drug discovery are highlighted as worth watching.
A61K · Medicinal preparations
With only 4 patent records and a 3% share, A61K coverage is sparse relative to the volume of in silico discovery work in this corpus. AI-guided formulation optimization and delivery-system design are downstream applications that could logically bridge the computational discovery layer to this branch. Teams with wet-lab capability could differentiate by connecting AI-predicted candidates directly to formulation IP, a step currently under-protected in this corpus.
Search this in Eureka →C12Q · Measuring & testing involving enzymes and DNA
C12Q holds only 3 patent records and a 2% share, making it the sparsest branch with direct biological relevance. AI-driven assay design, enzyme activity prediction, and genomic target validation are natural intersections between machine learning and this IPC class. The low filing count may reflect that applicants are filing assay-related work under G16B (Bioinformatics) instead, or that the experimental validation step remains outside the current filing strategy of most corpus participants.
Search this in Eureka →How leading applicants differ across technology routes
Strength of each leader across the main technology routes.
| Player | G16C 20 · Computational chemistry | G16B 40 · Bioinformatics | G16B 15 · Bioinformatics | G06N 3 · Computing based on AI models | G16H 50 · Healthcare informatics |
|---|---|---|---|---|---|
| Regents of the University of Michigan | Absent | Strong · 4 | Absent | Absent | Strong · 4 |
| Fujitsu Ltd | Strong · 6 | Absent | Absent | Absent | Absent |
| Chengdu Anticancer Biosciences Ltd | Strong · 3 | Absent | Absent | Strong · 3 | Absent |
| Purdue Research Foundation | Strong · 3 | Absent | Strong · 3 | Absent | Absent |
| Atomwise Inc | Absent | Strong · 3 | Strong · 2 | Absent | Absent |
| Avalon Pharmaceuticals Inc | Strong · 4 | Absent | Absent | Absent | Absent |
| Cosyne Therapeutics Ltd | Strong · 3 | Absent | Absent | Moderate · 1 | Absent |
Frequently asked questions
The current corpus contains 52 patent families in scope. This is a relatively small corpus, which reflects both the emerging nature of the field and the specificity of the search definition.
Fujitsu Ltd is the top-ranked applicant with 6 patent records, followed by Avalon Pharmaceuticals with 5 and Atomwise and the Regents of the University of Michigan each with 4.
The United States leads with 23 patent records, followed by WIPO PCT at 15 and Europe (EPO) and India each at 6. China holds 3 records. Canada, Singapore, Australia, and Germany each have 1–2 records.
G16C (Computational chemistry) is the largest branch, followed by G16B (Bioinformatics) and G06N (Computing based on AI models). Healthcare informatics (G16H) and combinatorial chemistry (C40B) are secondary contributors.
The lifecycle stage is characterized as decline from the 2020 peak, with the recent-window growth rate at -11%. However, 2024 and 2025 show the highest single-year filing volumes in the corpus, and 2025 figures are subject to publication lag. The picture is mixed and warrants monitoring.
The most-cited patent covers phytomedicine analytics with 39 citations, followed by a target molecule–ligand binding mode prediction patent at 35 citations. In silico drug screening and discovery systems rank third and fourth with 18 and 17 citations respectively.
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Disclaimer. This page is generated from PatSnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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