Patent Landscape

Chemical Patent Landscape

Whether a series is already claimed decides whether it is worth pursuing, and the question comes up long before anyone talks to an attorney. SureChEMBL extracts structures from patent full text, images, and attachments — over 31 million compounds from the major offices — and it is the only open, structure-searchable patent chemistry resource.

Services: https://ftp.ebi.ac.uk/pub/databases/chembl/SureChEMBL (bulk, no key) · https://search.patentsview.org/api/v1 (optional, free key). Checked against: the live bulk tree, August 2026 — 31 releases, newest 2026-08-04.

Read [references/surechembl-bulk.md](references/surechembl-bulk.md) before downloading anything, [references/patent-data-sources.md](references/patent-data-sources.md) to know which source is silent about what, and [references/reading-patents.md](references/reading-patents.md) before drawing any conclusion — that one is judgement, not syntax, and the gap it describes is wide.

The two scripts

| Script | Answers | |---|---| | surechembl_bulk.py | Which release, which tables, and how much disk? | | patent_search.py | Who is filing in this space, in the US? |

SureChEMBL has no REST API

Checked live: surechembl.org/api/ and every plausible variant return 404. The website is interactive-only, and everything programmatic goes through the EBI bulk tree.

python skills/patent-landscape/scripts/surechembl_bulk.py releases --limit 3

# 31 releases, newest 2026-08-04. Updated fortnightly.
release     url
2026-08-04  https://ftp.ebi.ac.uk/.../bulk_data/2026-08-04/
2026-07-17  ...

Two directories hold different data. bulk_data/ is SureChEMBL 2.0 — Parquet plus an FPSim2 similarity index, fortnightly. data/ is the legacy quarterly txt/SDF dump whose README is dated

1. They are easily confused and the old one is much less useful.

Pin a release. Taking "latest" makes an analysis irreproducible against a corpus that changes every two weeks.

Plan the download; it is 15 GB

python skills/patent-landscape/scripts/surechembl_bulk.py plan --question structure-to-patent

# structure-to-patent: match a structure to compound ids, then to the documents disclosing it
# 3 table(s), 14.1 GB for release 2026-08-04
curl -O https://ftp.ebi.ac.uk/.../compounds.parquet           # 4.2 GB
curl -O https://ftp.ebi.ac.uk/.../patent_compound_map.parquet # 5.0 GB
curl -O https://ftp.ebi.ac.uk/.../patents.parquet             # 5.9 GB

A similarity search needs only fpsim2_fingerprints.h5 (1.4 GB) and compounds.parquet. Query the Parquet with DuckDB rather than pandas — it reads them in place without loading them.

Where the compound was found is the legal signal

patent_compound_map.parquet records which document field each compound came from, and that column carries almost all the meaning:

| Field | What it usually means | |---|---| | claims | the compound is claimed — the one that matters | | title / abstract | a headline compound of the filing | | description | disclosed: possibly prior art, a comparator, or a reagent | | image | extracted from a drawing by OCSR, and sometimes wrong |

Treating every extracted compound as "claimed by this patent" is the commonest misreading of this dataset. Only the claims define a monopoly.

Markush claims are not enumerated

This is the limitation that matters most. Chemical patents claim a genus — a scaffold with variable positions — and a single Markush claim can cover billions of compounds. SureChEMBL extracts the specific examples, not the genus.

So no structure hit means this exact structure was not disclosed as an example. It does not mean the structure falls outside every claim, and for a novel analogue of a known series the opposite is usually true. Markush search is a specialist capability that Reaxys, SciFinder, and Derwent implement and no free source does.

Novelty and freedom to operate are different questions

Novelty — has this been disclosed before? — determines whether you can patent it. A structure search genuinely helps.

Freedom to operate — can I sell this without infringing? — requires reading the claims of every in-force patent in every jurisdiction you will sell in, construed against your product. A structure search does not answer this and cannot.

They are independent: a compound can be novel and infringing, or old and non-infringing.

The US-only half

python skills/patent-landscape/scripts/patent_search.py assignees --title "PROTAC"

Needs a free PATENTSVIEW_API_KEY. Note that a missing key surfaces as a connection failure rather than a 401, so the obvious diagnosis is a network problem; the script checks explicitly.

Two coverage facts to carry: PatentsView is US grants and pre-grant publications only — no EPO, WIPO, CNIPA, or JPO — and assignee names are not normalised, so "Merck", "Merck Sharp & Dohme", and "Merck & Co., Inc." count as three companies.

The 18-month blind spot

Applications publish 18 months after priority. Everything filed in the last 18 months is invisible in every source, without exception. An empty landscape may mean nobody is working on the target, or that everybody filed last year — and the second is common precisely for the targets worth working on.

Composing with the rest of the bundle

• chembl → here: SureChEMBL ids cross-reference through UniChem, joining patent chemistry to

measured bioactivity.

• chemical-space → alongside: purchasable is a different question from unclaimed.
• generative-design → after: novelty of generated structures is a real use for this.
• clinicaltrials / openfda → alongside: filings, trials, and approvals are three views of the

same competitive picture.

Reporting results honestly

Name the source, its coverage, and the pinned release. Say which document field a compound was found in. State that Markush claims are not enumerated and that the search under-reports coverage for that reason. Note the 18-month lag. Give family counts rather than document counts where you can.

Never write "this compound is free to use". Write "no exact structure match in SureChEMBL release 2026-08-04; this does not address Markush claims, unpublished applications, or claim construction, and is not a freedom-to-operate assessment." Any decision with money attached needs a patent attorney — this skill exists to tell you whether to go and ask one.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: K-Dense-AI
• Source: K-Dense-AI/drug-discovery-agent-skills
• License: MIT
• Homepage: www.k-dense.ai

Install and usage instructions live in the source repository linked above.