Celleome Biosciences specializes in the field of Artificial Intelligence and applying machine learning principles on Next Generation Sequencing (NGS) data derived from patients, to identify unique and novel molecular signatures in diseases. In the last decade, NGS has provided new insights into human disease pathobiology with enormous data made available for a wide range of diseases. This is especially relevant for Tuberculosis (TB), an infection caused by the bacterium Mycobacterium tuberculosis (MTB) and the leading cause of death due to an infectious disease in the world. Considering that a third of the human population is believed to be infected with MTB and causing approximately 1.6 million deaths each year, the scourge of TB is compounded by the fact that deaths occur in India (World Health Organization Global Report 2019). Our expertise in public health, bioinformatics, and biomarker discovery allow us to identify at risk patients vulnerable to developing ATB, with a goal towards developing a rapid screening assay, benefitting the society at large.
Dr Vivek Yadav is a medical graduate and holds a Master’s degree in Public Health. He is a public health professional with nearly 20 years of experience with a focus on maternal and child health and family planning. He has provided national-level leadership to key programs that strengthen Family Planning and Maternal Health programs at scale with innovation and integration of digital technology and AI led solutions. He has also been part of the national consultative group for Quality Assurance for improving quality of services at public health facilities as well as for introduction of newer contraceptives.
Dr. Boyanapalli is a expert in diagnostic biomarkers and assay development. He is a partner consultant with Celleome Biosciences. In addition, he is working for the last three years as a biomarker lead at Wave Life Sciences, Cambridge, Massachusetts, USA. Prior to joining the team Dr. Boyanapalli worked at Takeda, via legacy Shire Pharmaceuticals, as a Senior Scientist. At Shire, he was a program team for bioanalytical and biomarker development strategies. He previously held roles of increasing responsibilities at Nivalis Therapeutics in biomarker discovery and development in cardiopulmonary diseases. He also worked at RoMonics and Boulder Diagnostics, Boulder, Colorado on point of care assay development and product delivery divisions. He held various positions of increasing responsibilities working on drug discovery, molecular and cellular assays, biomarker, immunogenicity, PK / PD assay development. Dr. Boyanapalli earned his PhD in Biology from Bowling Green State University and completed a post-doctoral fellowship in Immunology and Biochemistry at the University of Colorado.
Sandeep Namburi is a technical leader in cloud computing and software engineering. He has expertise in designing and implementing cloud-based, secure, and scalable data analysis systems. He has worked to implement and enable genomics data analysis on the public cloud for the Scientists at the Jackson Laboratory for Genomic Medicine. He earned his Masters in Bioinformatics from Georgia Institute of Technology, Atlanta.
A computational immunologist by training, Prashant has long been associated with NGS data generation and analysis having worked closely with world renowned Immunologists at the Jackson Laboratory for Genomic Medicine, and the University of Connecticut, Farmington CT, USA. Working to characterize unique transcriptional signatures in patients with autoimmune disorders, he has employed the latest NGS technologies to identify sequences which could potentially be used for therapy. Interestingly , inflammatory gene signatures in TB and autoimmune disorders have much in common, which has led to him becoming interested in TB.
David Dorsky is an infectious diseases clinician and virologist. His research interests include T-cell immunology, vector design, herpesvirus DNA polymerases and point-of-care diagnostics involving isothermal DNA amplification. He is currently Adjunct Associate Professor of Medicine at the University of Connecticut School of Medicine, where he served on the active faculty for 28 years.
Javad Noorbakhsh is a computational biologist focused on cancer genetics and AI. He has a PhD in physics and did his postdoctoral research in computational modeling of cancer genetics and heterogeneity. He has worked as a staff scientist at the Jackson Laboratory for Genomic Medicine studying cancer genetics and histopathology using machine learning. He currently is a lead computational scientist at the Broad Institute working on genetics and transcriptomics of cancer cell lines using computational approaches.