Drug Development OS: The Evidence Record Behind Asset Decisions
Drug-development teams rarely lose time because one source is missing.
They lose time because the source is somewhere else. Clinical trials in one place. Publications in another. Regulatory records, patents, company filings, investor decks, data-room records, reviewer notes, and clinical-strategy rationale scattered across separate workflows.
AuraOne Drug Development OS is built around that problem: one asset record, one evidence fabric, and one packetized decision trail.
What is proven today
The current product implementation supports the core workflow shape:
- Asset scouting and external program review
- Scientific diligence with evidence-cited claims, assumptions, risks, and gaps
- Clinical strategy with trial evidence, endpoint precedents, and indication hypotheses
- Human review gates before assisted-live or unreviewed evidence can drive applied worker output
- Diligence, indication, and decision packets with citations, provider modes, hashes, manifests, and audit metadata
- Provider health and provenance labels so users can distinguish fixtures, assisted-live research, live public APIs, enterprise connectors, and licensed-vendor abstractions
That matters because a portfolio decision is only useful if the team can inspect the evidence behind it later.
The public-source layer
The platform now has live public-provider adapters for the source classes a drug-development team needs most often:
- ClinicalTrials.gov for clinical trial records
- PubMed, Europe PMC, Crossref, and OpenAlex for literature
- FDA Drugs@FDA and DailyMed for regulatory and label records
- PatentsView for patent metadata
- ChEMBL and PubChem for chemistry evidence
- Open Targets for target-validation evidence
- SEC EDGAR for public company filings
The web research provider is separate. It can help discover public evidence across the web, but it is always assisted-live and review-gated. It does not become authoritative evidence until a reviewer accepts it.
The abstraction layer
Some source classes should not be marketed as production integrations until a customer has credentials, source allowlists, or a licensed vendor contract. AuraOne tracks those honestly as source abstractions.
That includes EU and global registries, EMA, EPO OPS, WIPO/Lens, BindingDB, RCSB PDB, GWAS Catalog, GEO/Expression Atlas, DepMap/cBioPortal, conference abstracts, investor-deck ingestion, Snowflake/S3, Benchling/Dotmatics, Veeva/Medidata, and licensed competitive-intelligence vendors.
Those entries are useful now because they give settings, health, packets, and workers a consistent provenance contract. They are not represented as credentialed customer integrations until the customer environment actually has access.
The decision workflow
The workflow is intentionally simple.
First, the team starts with an asset, target, company, indication, or diligence question. AuraOne searches configured public providers and assisted web sources, then brings candidate evidence into the asset record.
Second, reviewers accept, reject, edit, and attach evidence. Review state stays visible. Source URLs, provider record IDs, retrieval timestamps, source domains, and content hashes travel with the evidence.
Third, workers produce diligence, clinical, risk, or decision outputs. The outputs are schema-validated and evidence-grounded. Unsupported claims and unreviewed evidence are blocked or flagged before the output can be applied.
Fourth, the team exports a packet. The packet carries accepted evidence, claims, assumptions, risks, gaps, worker manifests, source manifests, provider modes, and a packet hash.
That packet is the artifact the next reviewer, portfolio lead, or governance process can inspect.
Fifth, those signed decisions become training signal. The accepted evidence and reviewer judgments improve the model that drafts the next diligence pass — and the resulting weights stay yours.
What we do not claim yet
This is not a claim of full market parity with any production drug-development intelligence vendor.
AuraOne should not yet claim production customer deployment proof, licensed competitive-intelligence data access, or live integrations with every enterprise system.
The accurate claim is narrower and stronger:
AuraOne has shipped an implementation-level Drug Development OS with live public biomedical and company-intelligence providers, assisted web research, enterprise connector abstractions, review-gated specialist workers, benchmark scaffolding, and packetized provenance.
That is the product surface now available to build from.
What teams keep
The durable asset is the record — and the model trained on it:
- Accepted evidence and rejected evidence
- Provider provenance and content hashes
- Reviewer decisions and review state
- Clinical context and endpoint precedents
- Claims, assumptions, risks, and gaps
- Decision packets and audit manifests
- Strategy memory and rejected hypotheses
- The weights your reviewers' judgments improve
This is an AI app for your field, and you keep the weights. The work does not disappear into a slide deck, a shared folder, or a black-box answer. It stays attached to the asset.
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