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ClariTrial

Emerging Drug Intelligence

Four pillars of intelligence for the questions that matter most in drug development: who is competing, which candidates will succeed, where the opportunities lie, and what stealth companies are building before they announce.

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Intelligence pillars4Competitive, success, opportunities, stealth
Live capabilities16Available today
Planned capabilities10On the roadmap
Data sources7Connected and queryable

Competitive Landscape

Who else is working on similar drugs?

Map the competitive field for any drug target or modality. See which companies have programs at each clinical stage, where target overlap is densest, and how deal activity shapes who controls which assets.

6
Live
0
Planned
Sources (4 live)ClinicalTrials.govAACT / CTTIWHO ICTRPCurated landscape dataSEC EDGAR

Capabilities

TPD competitive matrix

Live

Interactive company-by-target grid showing clinical phase for each program across the TPD field.

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Company profiles

Live

Curated pipeline, financials, and partnership data for tracked companies.

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Modality-level trial aggregates

Live

Live AACT queries for degraders, molecular glues, and kinase inhibitors: phase breakdowns, top sponsors, and sample trials.

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Competitive landscape in AI chat

Live

The AI chat can query the curated TPD matrix directly: filter by target, company, modality, phase, and disease area. Ask natural-language questions about competitive overlap.

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Flexible AACT queries

Live

Parameterized SQL by target, sponsor, drug, condition, phase, and modality in AI chat: not just four fixed presets.

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Partnership and deal tracking

Live

Structured deal flow data (acquirer, value, structure) for competitive context.

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Success Prediction

Which drug candidates are likely to succeed?

Evaluate drug candidates by trial design quality, enrollment momentum, regulatory designations, published interim data, and safety signals. Cross-reference with literature to assess probability of success.

5
Live
2
Planned
Sources (4 live)ClinicalTrials.govPubMed / NCBIOpenFDA FAERSChEMBLConference abstracts

Capabilities

Deep trial detail

Live

Full protocol: eligibility, endpoints, arms, sites, enrollment, and whether results are posted.

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Published evidence search

Live

PubMed-powered search for trial results, systematic reviews, and interim analyses.

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FDA safety signals

Live

OpenFDA adverse event summaries by drug or drug class.

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Head-to-head trial comparison

Live

Side-by-side comparison of 2 to 4 trials: design, endpoints, enrollment, and status.

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Target biology in AI chat

Live

The AI chat can retrieve deep curated target profiles (mechanism, pathway, diseases, degradation rationale) for STAT6, IRAK4, and IRF5 to contextualize trial data.

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Posted results extraction

Planned

Structured parsing of CT.gov posted outcome measures and statistical results.

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Regulatory designation tracking

Planned

FDA breakthrough therapy, fast track, priority review, and orphan drug designations as success predictors.

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Drug Improvement Opportunities

Where can new drugs do better?

Identify where existing drug candidates have known limitations: narrow therapeutic windows, poor CNS penetration, resistance mechanisms, or unaddressed patient populations. Map white-space targets and underserved indications.

5
Live
2
Planned

Capabilities

Target biology profiles

Live

Deep target narratives: mechanism, pathway, disease relevance, and known limitations of current approaches.

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ChEMBL compound potency

Live

Bioactivity data (IC50, Ki) for compounds against specific targets, revealing selectivity and potency gaps.

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White-space target identification

Live

Targets with disease validation but no clinical-stage programs in the competitive matrix.

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Target biology in AI chat

Live

The AI chat can retrieve curated target profiles with degradation rationale, disease context, and competitive gaps to identify where new drugs could improve upon existing candidates.

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Competitive landscape in AI chat

Live

Query the TPD matrix from AI chat to find white-space targets and underserved indications where no company has clinical programs.

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Safety differentiation analysis

Planned

Class-level FAERS analysis to identify adverse event profiles that new drugs could improve upon.

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Patent landscape mapping

Planned

Freedom-to-operate analysis and identification of expiring composition-of-matter patents.

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Stealth Company Intelligence

What are new companies working on before they announce?

Stealth-mode biotechs leave breadcrumbs across public registries, patent filings, grant databases, scientific publications, and conference abstracts. Triangulating these signals reveals emerging competitors before press releases.

0
Live
6
Planned

Capabilities

New sponsor detection

Planned

Monitor AACT for trial registrations from sponsors not in the tracked competitive set. Flag new entrants in watched therapeutic areas.

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International registry monitoring

Planned

WHO ICTRP scan for novel programs registered in ChiCTR, EU CTR, or other international registries before US filing.

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NIH grant intelligence

Planned

Track SBIR/STTR and R01 grants in target areas to identify academic-to-clinical translation signals.

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Preprint and abstract monitoring

Planned

Scan bioRxiv, medRxiv, and conference abstract databases for novel compound disclosures by unknown entities.

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Patent filing surveillance

Planned

Monitor new patent applications (CPC classification) for composition-of-matter claims on novel degraders or targets.

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Composite stealth-signal scoring

Planned

Triangulate registry, patent, publication, and grant signals into a confidence score for emerging competitor identification.

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Planned sources:Patent databasesNIH RePORTERSEC EDGARbioRxiv / medRxivConference abstracts

Emerging drug intelligence combines curated company data with live registry queries. Phase classifications reflect the highest reported clinical stage; always verify against primary sources. This is not investment advice.

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