A new era in biopharma has arrived
Advances in AI/ML and cloud computing now make it possible to accelerate and scale the discovery of novel therapeutics.
Innovative application of AI/ML leads to identification of novel therapeutic targets.
SpliceCore® transforms massive amounts of RNA sequencing data into the raw material needed to power its therapeutics discovery engine.
SpliceCore® Applications
Discovery of drug targets that can be validated with antisense oligonucleotides.
Identification of RNA splicing derived neoepitopes for immunotherapies.
Detection of clinical biomarkers for patient stratification.
SpliceIO™
Envisagenics’ machine learning module for the identification of tumor-specific RNA splicing-derived neoepitopes
SPINRAZA®
Led by Dr. Adrian Krainer, Envisagenics’ founding scientific team helped in the development of SPINRAZA®. In December 2016, SPINRAZA became the first FDA approved RNA therapeutic to treat Spinal Muscular Atrophy (SMA) by correcting the disease-causing splicing error.
Since then, with further advances in RNA therapeutic delivery systems, an increasing number of RNA therapeutics have received or are close to obtaining FDA approval.
Pipeline
Program
SpliceCore® platform
Details
Identification of drug target in initial patient cohort
Benchmarks
Prevalence, consistency, bulk of expression
Details
Determine that target is expressed in disease but not in control to demote out off-target effects and toxicity
Benchmarks
Null or negetible expression in normal tissues
Details
Determine that target is also prevalent in independent patients cohorts
Benchmarks
Prevalence, consistency, bulk of expression
Details
Determine that target fullfills bilogical requirements for modality type
Benchmarks
Biological impact, pathways role, protein product integrity, RNA stability, subcellular localization, regulatory mechanisms
Details
Determine accesibilty and mudulability of target by drug
Benchmarks
Target mudulability, target accesibility
Experimental Validation
Pre-Clinical
Pipeline
| Milestone | Details | Benchmarks |
|---|---|---|
| Target ID | Identification of drug target in initial patient cohort | Prevalence, consistency, bulk of expression |
| Disease specificity | Determine that target is expressed in disease but not in control to demote out off-target effects and toxicity | Null or negetible expression in normal tissues |
| Cohort reproducibility | Determine that target is also prevalent in independent patients cohorts | Prevalence, consistency, bulk of expression |
| Biological elevance | Determine that target fullfills bilogical requirements for modality type | Biological impact, pathways role, protein product integrity, RNA stability, subcellular localization, regulatory mechanisms |
| Druggability | Determine accesibilty and mudulability of target by drug | Target mudulability, target accesibility |