Get traceable SAR that fits your schema and holds up under analysis
Excelra turns complex patents, papers, and agreed source material into structured chemical and biological records your team can use. Structures, targets, activities, assay context, and provenance are mapped to your data model, including difficult chemistry and layouts that automated pipelines often misread.
Reduce preprocessing and scientific rework while giving modeling, medicinal chemistry, assay, and informatics teams a consistent view of the source evidence and every standardized value.
Keep chemistry, context, and provenance intact
- Mapped to your data model SDF, CSV, TSV, Excel, JSON, or a custom field map aligned to your entity model, controlled vocabularies, ontologies, and downstream interfaces. Client-specific fields and terminology can be incorporated into the curation rules.
- Structure fidelity through ingest Structure diagrams, names, and source identifiers are reconciled where the evidence supports a match. Source-reported and normalized representations remain distinct. Project rules can address salts or solvates, charge states, tautomer handling, and parent structures without assigning unsupported stereochemistry.
- Comparable activities without losing the source record Endpoint types, relation operators, values, units, and assay context are captured and standardized under agreed rules. Original reported values remain available alongside normalized fields, and distinct endpoints such as IC50, EC50, Ki, Kd, and percent inhibition are not collapsed simply because their units can be converted.
- Scientific review for complex modalities Scope can include HELM-compatible polymer representations; degrader components, linkers, and attachment points; covalent warheads and reported attachment context; mAbs and other biologics; and multi-assay layouts that require relationships across text, figures, and tables.
- Three-tier scientific QC Curation is followed by independent review and senior QC. Checks focus on high-impact failure modes such as incorrect target mapping, unit conversion errors, unsupported stereochemistry, and loss of warhead, linker, or assay context.
Preserve the relationships your analysis depends on
Curation engagements connect structure, target, activity, assay, and source evidence, then map those relationships into your organization’s fields and vocabularies.
Move complex source work off your scientists’ critical path
Excelra’s patent-curation work, including public KRAS programs, demonstrates the operating pattern: identify relevant disclosures, reconcile structures across diagrams and tables, link activities to assay context, and deliver the result in a consistent data model under agreed rights.
- Patent-aware coverage for chemotypes and activity data absent from journal-only sets
- Repeatable curation rules and review workflows across production batches
- Optional mining-to-curation workflow when source coverage is uncertain
A sample CSV, TSV, SDF, or JSON output lets informatics and data-science teams inspect field coverage, normalization decisions, provenance, and ingestion fit directly.
Make your existing automation more dependable
Keep parsers and language models where they perform well. Excelra can provide validated reference data, exception handling, and production review for the structures, R-groups, stereochemistry, Markush context, and multi-assay tables that create the most consequential errors.
Questions we hear from discovery and informatics leaders
Scientific curation requires more than transcription. Target identity, structures, stereochemistry, units, assay context, and modality-specific relationships must remain coherent. Multi-tier review reduces the downstream investigation and rework caused by plausible-looking but incorrect rows.
Those platforms are designed primarily for search and analysis within their licensed environments. Data curation addresses a different need: a defined dataset mapped to your schema and delivered for approved internal use under agreed terms. Specific reuse and training rights should be confirmed in the applicable license.
If GOSTAR already covers your slice and its data model is acceptable or needs only light reshaping, a partial backfile can be faster than curating the same evidence from source. Use curation when you need novel fields, organization-specific ontologies, mixed source types, or enrichment around a covered core.
Yes. Share the scientific need and a sample source or schema snippet. We will scope a standardization benchmark or restart engagement from the technical fit, then commercial terms follow once that fit is clear.
Data curation
Inspect schema fit before a production batch
Share a representative source and the fields your workflow requires. We will use them to scope a standardization benchmark.
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