Predict gene therapy
before you build it.
Osmium models expression kinetics, immune clearance, NAb interference, and therapeutic windows for AAV gene therapy constructs — from first principles, not black boxes.
Simulation Capabilities
Six modeling subsystems. One integrated prediction.
Expression Kinetics
Sigmoidal onset, exponential decay, CMV promoter silencing — modeled day-by-day for 365+ days per construct.
- ›Three-phase model: zero → sigmoidal ramp → exponential decay
- ›Cell division dilution based on tissue-specific turnover rates
- ›CMV promoter silencing half-life at 90 days in vivo
- ›Promoter strength multipliers for 11 different promoters
Immune Response Modeling
Innate + adaptive immunity with tissue-specific immune privilege. Predicts T-cell clearance and its impact on expression.
- ›Gaussian innate response peaks at day 3
- ›Adaptive response onset at day 14, plateaus over weeks
- ›Immune privilege factors: retina 0.9, brain 0.7, liver 0.0
- ›Immunomodulator cassettes reduce response by 60%
NAb Seroprevalence
Pre-existing neutralizing antibodies block initial transduction. Population-stratified data (general vs pediatric) for all 6 serotypes.
- ›AAV2 highest seroprevalence at 72% (general population)
- ›Pediatric populations 40-50% lower across all serotypes
- ›NAb reduction formula: max(0, 1 - prevalence × 1.5)
- ›De novo NAb development modeled from day 14 onward
Therapeutic Window Prediction
Automatically identifies when expression crosses the therapeutic threshold and when it falls below — the true clinical value.
- ›Configurable therapeutic threshold per construct
- ›Onset day, end day, and effective duration calculated
- ›Redose recommendation 14 days before window closes
- ›High NAb titer warning for same-serotype redosing
Serotype Head-to-Head
Compare all 6 AAV serotypes against the same gene/tissue/route combination. Sorted by effective therapeutic duration.
- ›Tissue-specific transduction efficiency multipliers
- ›Route delivery efficiency (IV, intrathecal, subretinal, etc.)
- ›Results ranked by effective duration, not just peak expression
- ›Identifies optimal serotype for each tissue target
Dose-Response Analysis
Model expression peaks across 6 orders of magnitude of dosing. Understand the dose-response relationship for each serotype.
- ›Doses from 1e11 to 1e14 viral genomes
- ›Peak expression scales with transduction efficiency
- ›Tissue mass and blood flow fraction factored in
- ›Ceiling effect at 100 AU prevents runaway expression
Roadmap
Where we are and where we're going.
- +SQLite database with 18 tables, 189 seed rows
- +14 genes with exact coding sizes from primary references
- +26 regulatory elements with bp-accurate sizing
- +6 serotype tropism profiles + 8 administration routes
- +Tissue-to-promoter and tissue-to-serotype decision tables
- +117 passing tests with full data integrity verification
- +PK/PD expression kinetics (onset → peak → decay)
- +Immune response modeling (innate + adaptive)
- +NAb seroprevalence-based transduction reduction
- +12 tissue parameter presets with cell turnover data
- +Serotype head-to-head comparison engine
- +Therapeutic window detection and redose recommendation
- +AAV packaging compatibility check (4,700bp limit)
- +Auto mini-gene fallback for oversized genes
- +Tissue-optimized promoter selection (priority-ranked)
- +Serotype and route recommendation engine
- +Component-level size accounting (ITRs + promoter + gene + enhancer + polyA)
- +6 pre-computed construct templates (SMA, LCA, HemB, SCD, CF, DMD)
- ○NCBI E-utilities for gene sequence validation
- ○Ensembl REST API for transcript data
- ○UniProt REST API for protein function
- ○GTEx Portal for tissue expression data
- ○gnomAD for population variant frequencies
- ○bioRxiv/PubMed for literature monitoring
See it in action.
Explore the interactive visualizer with live simulation data from all 6 construct templates.
Launch Visualizer →