PURPOSE: Identify mechanism of action (MoA) from animal phenotype models

OVERVIEW: BioSymetrics leverages a proprietary machine learning platform (Augusta™) to generate structure-based activity predictions. This in combination with a vertebrate, in vivo phenotypic profiling framework has allowed us to make phenotype-mechanism association predictions across a range of potential clinical applications.

INPUT: Chemical structures, experimental datasets (public and private)

OUTPUT: Implicated pathways/processes

USE CASE: Phenotype MoA Prediction
INPUT: Phenotype Assays
Activity prediction model is fit and validated
The model ranks a large compound library from most- to least-likely to produce the phenotype
Pre-built clusters from experimental assays provide clues as to the target and pathway
Enrichment of target; Analysis of most-likely active compounds indicates MoA
OUTPUT: Protein targets and affected pathways
Hover on the numbered hot spots above to reveal each stage of progression


  • More certainty of compound effects in vivo
  • Fewer off-target effect “surprises”/ reduced toxicity
  • leverage multiple experimental and public datasets
  • Increased confidence in lead compounds
  • Shorter path to market

PREVIOUS APPLICATIONS: Identification of causal pathway in cardiovascular, metabolomic, and neurological models