Jorge Omar Yanez-Cuna

Advancing company platforms, leading the competitive intelligence and strengthening intellectual property portfolios. Leading the development of synthetic DNA constructs for non-viral gene therapies and their application in the production of recombinant adeno-associated virus (rAAV), lentiviral vectors (LVV), and mRNA therapies. Spearheaded the transformation of Anjarium from a therapy-focused company into a CDMO Driving client engagement with cutting-edge technology. Building a high-performing R&D team.

Led the preclinical work for the development of novel AAV gene therapies targeting diverse tissues (e.g. muscle, heart, liver, retina, CNS, cochlea). Led innovation in codon optimisation, promoter design, and vector development, supporting therapeutic pipelines. Collaborated with the intellectual property team in drafting patents, and conducting freedom-to-operate analysis. Contributed to two indications now in clinical trials: LGMD2I (WO2022076556) and congestive heart failure (WO2022031914).

Directed machine learning, bioinformatics, and in vivo and in vitro experiments to develop novel gene expression cassettes, enhancing the specificity and potency of AAV vectors, enabling safer and more effective gene therapy. Collaborated with the IP team in drafting patents, and conducting freedom-to-operate analysis. Engaged top-tier clients in the cell and gene therapy space, planning and managing projects under tight deadlines, while maintaining clear communication to ensure alignment and success.

Developed cutting-edge genomic approaches using CRISPR/Cas9 and NGS technologies to investigate gene regulation and chromatin structure.

Developed machine learning tools to decode how gene expression is regulated by enhancer DNA sequences. Leveraged high-throughput data (e.g. ChIP-seq, RNA-seq, and STARR-seq), to identify sequence elements critical for regulatory activity. Published several high-impact scientific papers, including one in Nature, advancing the understanding of gene regulation mechanisms and demonstrating the power of integrating machine learning and bioinformatics for breakthrough discoveries in life sciences.