Five foundational technologies set PanAum apart from legacy computational chemistry platforms, each targeting a specific failure point in traditional drug discovery.
A heterogeneous Graph Attention Network (GAT) that synthesizes multi-omics inputs to predict high-affinity molecular scaffolds. Unlike traditional screening, it enables genuine de novo molecular invention with pharmacogenomic variant constraints built directly into the generation process.
Safety and pharmacokinetic constraints are built directly into the molecule generation process, reducing failure rates in pre-clinical and late-stage development. Unsafe candidates are filtered at design time, not after synthesis.
PanAum uses Mendelian Randomization to confirm that each target is a genuine driver of disease rather than a downstream symptom, which helps cut costly late-stage attrition.
Structural biology powered by AlphaFold3 identifies binding pockets and cavity geometries that feed into generative molecular design, including variant conformations from common missense polymorphisms.
Population-level variant intelligence from PharmGKB, CPIC, gnomAD, and the FDA Table of Pharmacogenomic Biomarkers runs through every pipeline stage. Metabolizer phenotype profiling across CYP2D6, CYP2C19, CYP3A4/5, UGT1A1, and SLCO1B1 ensures every lead is safe across real patient populations, not just the reference genome.
| Dimension | Traditional CADD | PanAum Platform |
|---|---|---|
| Target Discovery | Manual / Associative methods | Causal (Mendelian Randomization) + variant-risk scored |
| Molecule Design | Virtual library screening | Generative AI de novo design |
| ADMET Safety | Post-hoc discovery (late-stage) | In-loop prediction & constraint |
| Population Coverage | Assumed universal | Stratified across 5 ancestral groups via PGx layer |
| Metabolizer Safety | Discovered in Phase I/II | CYP/UGT polymorphism constraints in-loop at design stage |
| Data Integration | Single-omics, siloed databases | Multi-omics + pharmacogenomics, 10+ unified sources |
| Time to IND | 6–10 years | 18–36 months |
| Target Validation | Correlative evidence only | Causal, genetically validated |
| Clinical Output | Compound only | Lead + PGx biomarker + Companion Dx draft |
