I provide consulting expertise to develop next generation gene and cell therapies: computational biology, gene therapy / gene editing, guide design, on- and off-target analysis, new company setup, and regulatory interactions.Client projects have included: • Advising on overall off-target strategy from early research to clinic • Regulatory submission of Investigational New Drug (IND) applications • Implementing and improving gene editing off-target methods including Digenome-seq • Epigenetic (ATAC-seq) and RNA-seq data analysis • Setting up new computational infrastructure (AWS / cloud), computational biology groups and hiring new employees • Due diligence of new technologies and ventures for therapeutic and platform developmenthttp://www.nextgenedit.com

• Led gene editing characterization and regulatory submission for 10+ CRISPR-based clinical trials that are currently open• Expanding the research platform by characterizing new Cas enzymes, Cas specificities, and other new editing modalities• CRISPR screening for various cell traits and modifications that can improve outcomes in clinical trials

• Started first company sponsored CRISPR clinical trials for CTX001 via submissions to European or American regulatory agencies for beta thalassemia and sickle cell disease(!)• Created on- and off-target NGS assessment strategy for all CRISPR Therapeutics programs; presented and published about strategy to influence community conversation• Work with multiple collaboration / alliance partners and contract research organizations on therapeutic programs• Manage outsourced software development, research IT infrastructure maintenance• Lead amazing team of over 10 computational and bench researchers

• Predicted guide RNAs appropriate for therapeutic targets• Sequenced edited DNA to asses guide efficiency on and off target• Validated various methods for increasing guide screening capacity• Computationally improved guide RNA effectiveness prediction and guide editing detection limit

Summary: Key early research put two drugs on the market - Idhifa (IDH2m inhibitor) and Tibsovo (IDH1m inhibitor) - and led to three ongoing clinical trials - Mitapivat (PKR activator), Vorasidenib (Pan-IDHm inhibitor), and AG-270 (MAT2A inhibitor). • Showed first evidence that methylation reversal of leukemia pathways was the mechanism of action of Agios’ IDH2 small molecule inhibitor (Idhifa) by analyzing methylation microarray and sequencing data (Kernytsky et al, Blood 2015 125:296-303)• Identified MAT2A in synthetic lethal shRNA screens as a target for AG-270 currently in clinical development (Marjon et al Cell Rep. 2016 15:575-587)• Created the next generation of cancer metabolism drugs by creating and testing patient stratification and responder hypotheses and identifying new targets for personalized treatments.• Inferred rare disease prevalence using NHLBI 6500 exome sequencing data • Developed PCR and deep sequencing methods for phage display small peptide screening • Created tool to separate human / mouse mixed DNA sequences from mouse xenografts by determining how uniquely a sequencing read maps / aligns to human and mouse genomes • Built RNA-seq pipeline for analyzing in-house data using Tophat, Bowtie, and Cufflinks

Summary: Directed basic research decisions using genome-scale tumor data (gene expression, methylation, amplification/deletion, and mutation) from public sources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and the database of Genotypes and Phenotypes (dbGAP)• Built a framework for mining The Cancer Genome Atlas (TCGA) for recurrent gain-of-function point mutations that make ideal small molecule drug targets• Created SNP imputation algorithm with a 60% accuracy to identify cell lines for a new program using public data and enabled stalled project to proceed

• Contributed and evaluated core methods and algorithms for large-scale data integration and refinement project that produced leading DNA sequence variation detection engine (SNP and indel genotyping) for next-generation sequencing (Illumina, SOLID, 454 sequencers)• Interacted closely with bench scientists to create, test, and approve new design for selectively sequencing whole exomes (all exons in a genome); design is currently in production on large fraction of the Broad’s 100 Illumina sequencers and brings 15% reduction in sequencing cost• Created and developed reusable bioinformatics tools within a structured Java analysis framework to fulfill various projects’ analysis needs

• Integrated various genome-scale sources of sequence, structure, and function data and used genetic algorithms to automatically select appropriate input features for the training of machine learning algorithms including neural networks and support vector machines (SVMs) to predict protein function / enzymatic activity• Performed large-scale assessment of integral membrane protein structure prediction methods; created public web server to provide rigorous community benchmarking of methods• Automated the creation and weekly updating of custom, in-house databases of protein structure and sequence from mirrored versions of public biological databases• Optimized prediction of protein crystallizability for high-throughput crystallization consortium

• Worked on design, implementation, and testing of gene expression microarray production facility• Designed software to select the best group of oligonucleotides to detect a given gene with high sensitivity

• Performed gene expression experiments and analyzed results for disease relevance in collaboration with various research groups using Affymetrix GeneChip and proprietary microarray technology• Implemented system for annotation and analysis of high-throughput expression data that interacted with SQL databases and Java-based analysis tools