Anna Lyubetskaya Email & Phone Number

Cambridge, Massachusetts, United States

In collaboration with drug discovery collaborators, spearheaded the identification and validation of novel oncology targets in 2 solid tumor indications within a global, cross-functional setting. As a result, developed a complete analytical and experimental framework that leveraged machine learning, artificial intelligence, and image analysis, multi-modal spatial transcriptomics and pathology patient data, and pooled functional genomics screens, facilitating the generation of novel target and biomarker hypotheses.

Partnered with 6 oncology drug discovery programs across stages of development, contributing predictive and pharmacodynamics biomarkers, translational hypotheses, and patient disease stratifications. Pioneered quantitative analyses of state-of-the-art genomics technologies – including spatial transcriptomics, scRNA-Seq, Perturb-Seq, and cfDNA/RNA – to drive biomarker strategies.

Led clinical and research computational work to facilitate a personalized neoantigen cancer vaccine Phase 1/2a clinical trial.

Contributed to the initiation of a personalized neoantigen cancer vaccine Phase 1/2a clinical trial by providing analytics for a proprietary cell assay and by investigating the competitive space.

Co-developed a scalable data science architecture for knowledge extraction from unstructured scientific text and construction of disease-focused relationship graphs. As the product owner, led an engineering team in prototyping the product. Additionally, established data science workshops for marketing and sales departments

Supervised the bioinformatics analysis and integration of bulk and single-cell genomics and epigenomics datasets for a variety of metabolic projects for the Functional Genomics and Bioinformatics Core.

Advanced studies of obesity and insulin resistance by developing computational pipelines and performing various genomics and epigenomics computational analyses in collaboration with 5 clinical and experimental teams.

Developed and validated a novel computational framework for analysis of bacterial ChIP-Seq data as a part of a cross-functional consortium. Refined and expanded existing regulatory bacterial networks through the integration of binding and expression data focusing on non-canonical transcriptional regulation.

Ph.D, Bioinformatics

Bachelor Of Science (Bs), Bioinformatics And Bioengineering