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Envisagenics Validates AI/ML Approach for RNA Target Identification and SSO Therapeutic Development

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Results from evaluation of the company’s SpliceCore® AI/ML platform in Triple Negative Breast Cancer published in Molecular Systems Biology

Envisagenics, an AI-driven biotechnology company, 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,”.

SSOs are synthetic antisense oligonucleotide compounds that directly act on pre-mRNA to regulate the expression of alternatively spliced isoforms unique to cancer cells, which are key drivers of cancer progression and metastasis. 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.

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In the study, Envisagenics achieved the following milestones:

  • Utilized its proprietary platform, SpliceCore, to identify novel therapeutic targets along with their corresponding modulatory SSOs, and the specific Splicing Factors affected in pre-mRNA by these SSOs.
  • Conducted a retrospective validation of the SpliceCore algorithm using known functional SSOs.
  • Validated a previously unidentified target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13), discovered through the SpliceCore platform.
  • Illustrated the efficacy of targeting NEDD4Le13 with an AI/ML-designed SSO, showcasing its ability to attenuate the proliferative and migratory tendencies of TNBC cells, through downregulation of the transforming growth factor beta (TGFβ) pathway, a pivotal player in tumor invasion and metastasis.
  • Discovered a novel mechanism of TGFβ pathway regulation through alternative splicing in cancer.

“For patients with TNBC and other diseases that are difficult to treat, this study illustrates the usefulness of SpliceCore to discover novel therapeutic targets from patient’s RNA sequencing data,” said Dr. Akerman. “Our findings affirm the robustness and reliability of the platform and shed light on previously unrecognized avenues for therapeutic intervention.”

Source: PRNewsWire

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