Arun Jayaraman Email & Phone Number

Gaithersburg, Maryland, United States

Researching clinical patient samples for AstraZeneca's Early Respiratory & Immunology (Early R&I) group.I am the lead analyst for deep sequencing of patient cohorts contributing to translational science and clinical development, primarily supporting programs targeting rheumatoid arthritis populations. I have expertise analyzing genomics, proteomics, and transcriptomics patient profiles along with specialized technologies such as CITE-seq and spatial transcriptomics. I have contributed directly to investment decision-making for several RA therapies and generated results that are consequential for clinical trial designs.

I simultaneously support the early stage target discovery and late stage drug repurposing efforts for rheumatology at AbbVie. I have had the opportunity to analyze a variety of complex datasets including a CITE-seq dataset of synovial tissue from our discovery partnerships to very high dimensional longitudinal data from our clinical trials. I also support our patient stratification efforts for our clinical and discovery scientist colleagues using several methods such and cell type deconvolution and WGCNA-based gene network analysis to help identify patients with disease biology of interest for our target and biomarker discovery and cross-validation efforts.

Atlanta, Georgia, United States

Cardiac progenitor cells (CPCs) have been extensively studied for their cardiac regenerative properties. It has been well documented by both researchers in the Davis Lab and elsewhere that CPCs tend to lose their regenerative capabilities as people age. I sought to determine if there are any subpopulations of c-kit+ CPCs that are present in younger patient samples driving the regenerative properties that may be under-expressed in older patient samples. In order to characterize the cell populations, I leveraged the high resolution capabilities of single cell RNA sequencing technology.

Worcester, Massachusetts, United States

I worked as an intern in the myeloid antibody-drug conjugate group to mine existing scRNA-seq datasets for identification of new myeloid-specific surface protein targets and compositional characterization of known surface proteins across different disease and tissue states for the treatment of various inflammatory diseases (Crohn’s disease, ulcerative colitis, hidradenitis suppurativa, COVID-19, and rheumatoid arthritis).

Abbott Park, Il

I implemented a variety of machine learning tools for de novo molecule generation and predicting retrosynthetic pathways. The goal was to incorporate a variety of distinct machine learning tools into a seamless drug discovery pipeline.I also worked on building an in silico toxicity model for predicting off-target binding of small molecule drugs. RDock was used to score the protein docking of over 20,000 molecules to determine the distribution of expected docking scores for an individual protein. The molecule of interest would then be docked in a similar manner to a protein in the database and depending on where it falls on the distribution of scores would suggest the likelihood of the specific protein-drug interaction. The model was eventually expanded to include more than 300 proteins.

Urbana-Champaign, Illinois Area

I worked on replacing an existing web page of product information in order to utilize an updated database. I used the Vue.js javascript framework for web development and Pipeline Pilot to send queries and retrieve data from the database.

Abbott Park, Il

My project focused on determining the optimal co-milling process conditions for dry particle coating to improve powder flowability and tabletability. I worked together with another intern and used a variety of instruments to assess the material properties of the powder blends. I created and presented a poster about my project to other AbbVie employees during the Intern Poster Session. I am also a co-author of a publication regarding the work I did during this internship.

Urbana-Champaign, Illinois Area

In the Spring of 2018, I joined Dr. Han’s research group at UIUC as the first undergraduate research assistant, and I worked there until I graduated in May 2020. I assisted Dr. Joonhyuck Park, a post-doctoral Fellow in Dr. Han’s research group, with his research projects related to the synthesis of water-soluble and non-blinking Quantum Dots (QD) for use in MERFISH and other imaging techniques for biomolecules. As part of my work, I synthesized the Cadmium Selenide and Zinc-Cadmium Sulfide quantum dot cores and the monomer ligands necessary for derivatization. I helped with Dr. Park’s research into developing a novel shelling method for smaller quantum dot cores. The revised method utilized a unique precursor chemistry to separate the nucleation and growth stages for QD synthesis. When combined with a newly devised high-yield chemistry, the shelling method can remove a resource-intensive purification step which could improve cost-effectiveness for scale-up manufacturing. Because of my significant contribution to the evolution of the research, I am a co-author of two publications in ACS Nano and Nature Communications about our research into QD shelling.

Master Of Science - Ms, Biomedical/Medical Engineering

Bachelor Of Science - Bs, Chemical And Biomolecular Engineering, 3.65/4.0 With Distinction

Activities and Societies: I was an undergraduate research assistant in the Hee-Sun Han lab where I helped conduct research into novel.