For Pharma R&D & Biotech
AI for Pharma R&D & Biotech
Who it is for
- Big pharma
- Mid-size biotech
- Specialty pharma
- IP law firms
- Pharma consultancies
- Investment funds
Patent and pipeline evidence extraction
Problem and approach
Where pharma teams lose time today
- Patent landscape analysis across thousands of patents is expensive and slow
- Competitive pipeline intelligence is scattered across press releases and trial registries
- Regulatory dossier preparation requires precise cross-referencing
- Extracting comparable data from hundreds of publications is slow and inconsistent
- Evidence for a dossier is scattered across formats and teams
What DataStruct does
- Patent claim analysis and freedom-to-operate assessment
- Pipeline intelligence extraction (compound, indication, phase, sponsor)
- Regulatory milestone extraction from filings and releases you upload
- Literature data extraction with source-linked summaries
- One workspace for patents, literature and pipeline documents
Use cases
Pharma use cases
Patent Landscape Analysis
FTO analysis across a therapeutic area means reading thousands of patents.
Claim and priority-date extraction across the patent set, with source links for counsel.
Competitive Pipeline Intelligence
Tracking competitors' pipelines means monitoring trial registries, press releases, and conferences.
Extraction of pipeline data (compound, indication, phase, sponsor) from the documents you upload, each linked to source.
Regulatory Dossier Preparation
eCTD and CTA submissions require precise cross-referencing.
Rule packs for required sections and source-linked extraction across modules, for reviewer checking.
Scientific Literature Evidence Extraction
Medical Affairs needs comparable data from a growing set of publications in a therapeutic area.
Upload the publications, define the fields, and extract them with source links; ask questions across the set with citations.
Documents and questions
What pharma teams bring, and ask
Documents it reads
- Patents
- Scientific Publications
- Clinical Trials
- Regulatory Dossiers
- Drug Labels
- FDA CRLs
- SOPs
- Competitive Intelligence Reports
Questions you can ask
- “What is the patent landscape for KRAS inhibitors?”
- “Compare efficacy data across competing compounds”
- “What FDA feedback has been received on this mechanism?”
- “Identify freedom-to-operate risks for our pipeline”
- “Track regulatory milestones for this indication”
How findings read
The same evidence model in every sector
Answers cite the sources they rely on. Records DataStruct could not confirm are shown separately for a reviewer to check, related material is kept apart from evidence, and a finding with no support says so. Access is controlled by workspace roles, and sensitive actions are audit logged.