Protein Binding and Biotransformation Dynamics

Albumin Binding Site Predictions

Dual Binding Analysis

The Spirographic AI system now includes dual binding prediction capabilities, addressing the critical clinical gap of multi-site binding drugs. 42 drugs (6.6% of the validation dataset) are known dual binders that occupy multiple albumin sites simultaneously. The enhanced system successfully identifies these dual binders with >95% confidence, providing clinicians with displacement risk assessment and quantitative drug-drug interaction screening capabilities unavailable in any competing platform. This enhancement 

Validation Report

Cytochrome P450 99.4% Accuracy across 8 Isoforms

The Logan AI CYP450 Isoform Screening System delivers world-class accuracy with 99.4% precision across eight major cytochrome P450 enzymes, successfully identifying drug substrates for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 from molecular structure alone. With 100% specificity and zero false positives across 784 predictions, the system provides pharmaceutical companies with unparalleled confidence in drug-drug interaction screening, personalized dosing strategies, and regulatory submissions. Our comprehensive validation on 98 drugs demonstrates perfect negative control recognition for non-CYP metabolized compounds, ensuring accurate identification of alternative clearance pathways. This industry-leading performance enables precise clinical decision support, reduces late-stage development failures, and accelerates drug approval timelines through reliable ADME profiling.

CYP450 Metabolite Prediction Engine

50.2% Exact Matches

Validated against 213 experimentally confirmed metabolites, Spirographic AI’s CYP450 metabolite prediction engine achieves 50.2% exact SMILES match and 62.9% structural similarity (Tanimoto ≥ 0.7) — placing it in the range of leading commercial metabolite prediction platforms. Exact match identifies the precise metabolic product; structural similarity captures chemically meaningful predictions where the transformation site is correct but stereochemistry or minor substitution differs. Together these metrics reflect a system that correctly characterizes the majority of what the liver actually makes from a candidate compound — the critical early signal for metabolic liability, reactive intermediate formation, and toxicity risk before any human exposure occurs.