Envisagenics Validates AI/ML Approach for RNA Target Identification and SSO Therapeutic Development
NEW YORK, April 25, 2024 /PRNewswire/ -- Envisagenics, an AI-driven biotechnology company, today announced the publication in the journal Molecular Systems Biology of study results evaluating the company's SpliceCore AI/ML platform in Triple Negative Breast Cancer (TNBC). This study demonstrates the efficacy of artificial intelligence and machine learning (AI/ML) for target discovery in triple negative breast cancer (TNBC) and for identifying functional and verifiable splice-switching oligonucleotides (SSOs) crucial for the development of RNA therapeutics. The results also validate its potential to tackle a challenging disease such as TNBC, a particularly aggressive cancer affecting approximately 200,000 patients annually, with a dismal five-year survival rate of only 20%. Detailed results from the study, titled "Development and Validation of AI/ML Derived Splice-Switching Oligonucleotides," are available here.
- While holding immense promise as a therapeutic approach for impeding cancer growth, the identification of functional SSOs using traditional methods is high cost and requires extensive time and labor.
- "This study bridges the gap between computational predictions and experimental validation, positioning AI/ML as a critical force in validating RNA targets and advancing SSO therapeutic development," said Martin Akerman, Ph.D., Envisagenics' CTO and Co-Founder.
- Validated a previously unidentified target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13), discovered through the SpliceCore platform.
- "Our findings affirm the robustness and reliability of the platform and shed light on previously unrecognized avenues for therapeutic intervention."