Clinical Decypher.

Clinical Decypher is an AI decision intelligence platform for pharma clinical R&D that solves a single high-leverage problem: implicit and unvalidated assumptions buried in Target Product Profiles (TPPs) and clinical trial protocol drafts. In an industry where R&D costs are rising 10% per year, 30% of protocols undergo amendments, and a single unvalidated assumption — an over-optimistic enrollment rate, a misaligned comparator, an unsupported endpoint — can sink a multi-hundred-million-dollar trial, the platform systematically surfaces every "expected," "anticipated," and "assumed" buried in dense protocol documents.

The capstone scope focuses on Assumption Extraction & Structured Assumption Intelligence Layer: the AI auto-extracts both explicit and implicit assumptions, identifies numeric assumptions, detects probabilistic language ("expected," "anticipated"), classifies assumptions into structured categories, maps each to supporting evidence citations, flags assumptions lacking direct evidence, and computes confidence scores plus risk prioritization.

Output is a Structured Assumption Register — exportable (PDF / CSV), human-editable, with override capability at each stage (extraction, classification, evidence mapping). The AI persona is an expert Clinical Decision Intelligence Analyst supporting Clinical Development Leads and clinical strategy teams: analytical, objective, evidence-based, structured, concise, and transparent about uncertainty — never speculates when evidence is missing.

Targeting the clinical decision intelligence tools market: $2.5B in 2026, growing to $3.9B by 2030 at 12% CAGR. B2B (pharma, CROs), competing against Veeva Vault, Medidata, and Oracle Health — differentiated by focused oncology pipeline awareness, AI-enabled assumption intelligence, and embedded analytics across protocol design, clinical execution, and portfolio decisions rather than the document-management framing that incumbents lead with.