candidate-ranker

What problem does it solve?

It reduces decision fatigue in Oral Mucositis (OM) drug discovery by producing a clear, reproducible ranked shortlist from multi-source biomedical evidence.

Core Features & Use Cases

• Multi-criteria prioritization (MCDA): Scores each candidate 0–10 across OM-relevant dimensions (target relevance, mechanism strength, drug-likeness, ADMET, clinical precedent, traditional use evidence, pathway coverage, feasibility) with defined weights.
• OM-specific mapping and gap analysis: Assigns candidates to OM Sonis model phases (1–5), then identifies which phases and dimensions are underserved.
• Conservative handling of incomplete data: Uses confidence levels and flags missing evidence without inflating scores.

Quick Start

Rank a set of OM drug and phytochemical candidates from processed CSV evidence and produce candidate scorecards plus a ranking summary table and phase coverage gap analysis.