ADMET Prediction Models Patents: Who Leads, Where Gaps Are 2026
ADMET Prediction Models: Patents Mapping Who Files and Where the Gaps Sit
Concentrated at the top. The top 5 assignees account for 57.9% of all 19 records in scope, and the top 10 reach 84.2% — a short list of repeat filers surrounded by a long tail of single-filing entrants. Filings moved from zero in 2017 to a peak of 6 in 2025; 2026 already shows 5 published records but the year is only partial and publication lag of roughly 18 months means the final count will sit higher once late filings clear examination and publication.
- 1BOREALIS GMBH3
- 2DEEPCURE INC2
- 3SB TECH INC2
- 4NAT TAIWAN UNIV2
- 5NATIONAL ENVIRONMENTAL RESEARCH ACADEMY2
See the full admet prediction models analysis in Eureka
- The complete ranking, not just the top five
- Every IPC branch with its share of the corpus
- The most-cited records, and where claim space is still thin
Common questions on ADMET prediction model patents
How many patents exist for ADMET prediction models?
The scoped dataset contains 19 published records between 2015 and the 2026 cut-off, filed by 28 ranked assignees. This is a narrow field by patent-count standards, which means individual filings can shift concentration figures noticeably from year to year. Treat the count as the current state of a still-emerging niche rather than a mature, saturated technology area.
Who are the leading patent filers in ADMET prediction models?
Filing is concentrated at the top: the five most active assignees account for 57.9% of all 19 records in scope, and the top ten reach 84.2%. Beyond that group sits a long tail of assignees with a single filing each, including universities, a national research agency and individual inventors. Recent-year data shows some momentum shifting toward newer entrants while earlier leaders show no latest-year filings.
What technology areas do ADMET prediction model patents cover?
Nearly four in five of the 19 records (78.9%) carry the G16C computational chemistry classification, and just under half (47.4%) also carry G06N for AI-based computing methods. Smaller but present adjacencies include bioinformatics (G16B, 31.6%), general digital data processing (G06F, 21.1%), and narrower slices in polymer compositions, healthcare informatics, enzyme/DNA testing and material analysis. The pattern shows most claims frame prediction as a chemistry-specific method rather than a generic machine-learning application.
Disclaimer. This analysis is based on Patsnap Eureka data drawn from a limited snapshot of global patent records and is provided for general information and reference only. Patent data carries inherent limitations — recent filings are under-counted because of publication lag, counts may be on a record or family basis, classification and applicant-name data may contain errors or duplicates, and the underlying search query defines the scope shown — so the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing here is an exhaustive prior-art, novelty, freedom-to-operate or validity search, nor does it constitute legal, financial or professional advice, and it should not be relied upon as such. Verify independently and review with qualified patent and legal professionals before acting on it.
Method: Filing trend and technology composition. Derived from a Patsnap search on ADMET Prediction Models covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish. Every share divides by all records in scope. Data: Patsnap Eureka. See the full landscape report.