01

AI-Powered Drug Repurposing for Flaviviruses

Targeting the NS5 protease of Dengue, Zika, and Japanese Encephalitis viruses using a combined AI and structure-based virtual screening strategy. The goal is to identify repurposable small molecules from existing drug libraries with therapeutic potential against flaviviral infections.
02

Structure-Based Inhibitor Discovery for AMR

Developing a multi-step computational pipeline targeting antimicrobial resistance in Acinetobacter baumannii (CRAB). This includes ligand filtering, molecular docking, MD simulations, and in vitro validation of hits against carbapenem-resistant proteins.
03

AI-Guided Single-Cell Atlas for Early Cancer Biomarkers

Using single-cell RNA-seq and spatial transcriptomics to map immune and stromal cell interactions in early pancreatic cancer. The goal is to identify early-stage biomarkers and therapeutic targets through integrative AI-based analysis.

Medical Data Science Lab

The Medical Data Science Lab is a multidisciplinary research group at the forefront of biomedical innovation, integrating data science, artificial intelligence (AI), and computational biology to address some of the most pressing challenges in medicine and healthcare. Our mission is to harness the power of data-driven technologies to accelerate discoveries in disease mechanisms, diagnostics, therapeutics, and personalized medicine.

We specialize in Multi-Omics Data Integration, Machine Learning Model Development, Drug Discovery, and Host-Pathogen interaction studies. Our lab's work spans diverse disease domains, including infectious diseases, cancer, neurodegenerative disorders, and metabolic syndromes. We combine cutting-edge computational tools with rich biological datasets to generate actionable insights that support translational research and precision medicine.

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About Principal Investigator

Dr. Yogesh Kumar is a leading scientist in the field of Medical Data Science, with expertise spanning bioinformatics, artificial intelligence, computational drug discovery, and multi-omics integration. He is the founder and Principal Investigator of the Medical Data Science Lab, where he leads a multidisciplinary team focused on developing innovative, data-driven solutions for challenges in modern biomedical research.

Dr. Kumar holds a strong academic and research background, with more than 30 publications in reputed international journals. His research integrates computational biology, machine learning, and systems medicine, aiming to transform biological data into clinically actionable insights. His work addresses critical areas such as host-pathogen interactions, antimicrobial resistance, cancer biology, and personalized medicine.

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LATEST Research

EVALUATION OF THE CURRENT SAFETY
WE ARE THE TRUSTED EXPERTS

AI-Powered Drug Repurposing for Flaviviruses

Targeting the NS5 protease of Dengue, Zika, and Japanese Encephalitis viruses using a combined AI and structure-based virtual screening strategy. The goal is to identify repurposable small molecules from existing drug libraries with therapeutic potential against flaviviral infections.

Structure-Based Inhibitor Discovery for AMR

Developing a multi-step computational pipeline targeting antimicrobial resistance in Acinetobacter baumannii (CRAB). This includes ligand filtering, molecular docking, MD simulations, and in vitro validation of hits against carbapenem-resistant proteins.

AI-Guided Single-Cell Atlas for Early Cancer Biomarkers

Using single-cell RNA-seq and spatial transcriptomics to map immune and stromal cell interactions in early pancreatic cancer. The goal is to identify early-stage biomarkers and therapeutic targets through integrative AI-based analysis.

Our Team

Assistant Professor (PI)

Dr. Yogesh Kumar

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Research Associate

Dr. Kratika Singh

Research Associate

Dr. Yogita