Som specializes in integrating and analyzing multi-modal multi-analyte biomarker data from clinical and pre-clinical studies in a pharmaceutical setting to enable indication selection, patient stratification and indication expansion; demonstrated the ability to bridge clinical and pre-clinical research by providing informatics solutions under the umbrella of Translational R&D and by breaking silos in R&D at scientific and social
Som specializes in integrating and analyzing multi-modal multi-analyte biomarker data from clinical and pre-clinical studies in a pharmaceutical setting to enable indication selection, patient stratification and indication expansion; demonstrated the ability to bridge clinical and pre-clinical research by providing informatics solutions under the umbrella of Translational R&D and by breaking silos in R&D at scientific and social levels; strong understanding and background in autoimmune diseases, oncology and bio statistics; led complex matrix teams of discovery biologists, biomarker leads, statisticians, data scientists and clinicians.
Translational Bionformatics Team Lead, Immunology @ Specialties: Translational bioinformatics strategy development; data integration, analyses and visualization; data and results sharing; patient stratification; indication selection and expansion; biomarker selection; reverse translation
Therapeutic Area: Immuno Science
Leading a team of bioinformaticians to provide decision critical analyses to inform disease, patient and biomarker selection for BMS Immuno Science assets using integrated biomarker data and state of the art bioinformatics tools and techniques.
Leading efforts for integrating biomarker data and clinical data from BMS clinical trials and establishing ways to share integrated data across the organization by working closely with biomarker leads and IT; providing a means to use and reuse data from BMS clinical trials to impact multiple BMS assets at different stages of drug development.
Establishing best practices for analyzing multi-modal multi-analyte biomarker data from pre-clinical studies and clinical trials by working closely with biologists, biomarker leads and biomarker platform groups.
Assessing informatics gaps in the existing Translational Research & Development environment and working closely with biologists, informaticians, data scientists and statisticians and providing near term and long term implementable solutions to address them.
Enabling biologists and biomarker leads to interact with biomarker data and analyses results using interactive visualization and analyses tools.
Principal Scientist: 2014-Present
Senior Research Investigator: 2012-2014 From April 2012 to Present (3 years 7 months) Lawrenceville, NJClinical Genomics Expert, Bio Marker Development @ Specialities: Identification of prognostic, response and efficacy markers; integrated biomarkers; patient stratification; indication expansion; predictive modeling; machine learning
Identified prognostic and predictive markers for drug response using baseline gene expression data from whole blood of patients from phase 2a clinical trials
Identified new indications for Phase2b drugs using retrospective clinical trial biomarker data to impact prospective trials From December 2011 to April 2012 (5 months) Cambridge, MAComputational Biology Analyst, Development and Molecular Pathways @ Specialities: Experimental design, in vivo and in vitro models, pre-clinical and patient data, inflammatory diseases and cancer, understanding compound MOA, hypothesis generation and in silico validation, teaching
Analyzed and interpreted microarray (mRNA, miRNA, SNP, CNV, Chip-chip), proteomic (AMT, cellzome-pull down, aptamer) and HCS (siRNA, LMF, CTG) data
Designed and implemented large scale gene expression data mining strategies using highly curated and annotated public and proprietary microarray data to identify validatable disease targets.
Proposed early cancer and immune disease targets using orthogonal data types, gene set enrichment, literature mining tools and competitive intelligence information.
Identified gene signatures for HCS based assays; transcriptomic read-outs/end-points of biological processes/pathways; stratification of patients and compounds; and identification of disease relevant in vivo/in vitro models
Evaluated new technologies, software and algorithms relevant to drug discovery
Deeply involved in educating and training lab heads, bench biologists and biomarker leads about bioinformatics tools and techniques relevant to drug discovery
Received NIBR operational Excellence Team Award for identification and validation of a series of antibody drug conjugate (ADC) targets for tumor indications
Research Investigator II: 2010-2012
Research Investigator I : 2008-2010 From February 2008 to November 2011 (3 years 10 months) Cambridge, USAPostdoctoral Fellow, Systems Biology @ Integrated microarray and proteomic data with traditional toxicity data to establish a mouse model of COPD based on nose-inhalation exposure of cigarette smoke and LPS; identified biomarkers and disease pathogenesis pathways for LPS and smoke exposures.
Compared gene expression changes in a dose-dependent study of nano particles on mouse macrophages: constructed cell response networks that showed potential regulatory relationships between cell processes as a function of nano particle dose; identified size-dependent bio-signature of nano particle-induced inflammation
Analyzed time-course microarray and proteomic data from human mammary epithelial cells treated with growth factors to identify genes regulated by endogenous autocrine loops and distinguish early versus late signaling events in mammalian cell culture systems
Identified robust changes in gene expression in soluble paracrine factors induced by low dose radiation, that in turn, induces the transformation of bystander cells: understanding molecular mechanisms mediating the carcinogenic response to low dose radiation
Identified differentially expressed genes in normal thymus as compared to thymic lymphoma in presence and absence of a carcinogen and a chemopreventive agent in mice
Characterized the transcriptome of Brucella and Brucella-infected host cells during the initial infectious process for understanding the initial strategies employed for the pathogen to survive and replicate intracellularly and to identify perturbations of major gene(s) modulating critical cellular pathways during initial infection. From April 2006 to January 2008 (1 year 10 months) Richland/Kennewick/Pasco, Washington Area
Ph. D, Animal Science (Cardiovascular genomics) @ University of Wyoming From 2002 to 2006 Som Bandyopadhyay is skilled in: Immunology, Biomarkers, Drug Discovery, Genomics, Biomarker Discovery, Bioinformatics, Proteomics, Cheminformatics, Biostatistics, Microarray Analysis, Computational Biology, Gene Expression, Machine Learning, Predictive Modeling, Molecular Diagnostics, Oncology, Systems Biology, Translational Medicine, Molecular Biology, R, Pipeline Pilot, Spotfire, Biochemistry, Antibodies, Animal Models, Personalized Medicine, Lifesciences, Drug Development, Translational Research, Clinical Trials, Pharmacology, Clinical Development, Western Blotting, Cancer, In Vivo, Microarray, Inflammation, Cancer Research, real-time PCR, Science, High Throughput..., Cell Biology, Protein Chemistry, Genetics, DNA sequencing, Life Sciences, qPCR
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