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Dr Reetu Sharma

Dr Reetu Sharma

Artificial Intelligence & Data Science Scientist

Artificial Intelligence | Generative AI | LLMs | Data Science | AI Platforms | Biomedical AI

Scientific Profile

Dr Reetu Sharma is an Artificial Intelligence and Data Science scientist with over 15 years of experience spanning biomedical analytics, artificial intelligence, Generative AI, machine learning and applied healthcare research. She holds a PhD from the National University of Singapore and Masters from IIT Bombay. Her work focuses on applying AI, machine learning, LLMs and data-driven methods to healthcare, biomedical research and real-world applications. She has led the development of AI-enabled platforms for healthcare analytics, medical information, geromedicine and biomedical knowledge discovery, translating advanced AI and data science methods into practical solutions with measurable impact.

Dr Reetu Sharma

AI, Data Science & Technology Platforms

MediConsultAI | MedGeroX | GeroMedAI | ChemGraphX | MolSimAI | AI-MolProp Visualizer | PK Insight | DeepToxiLens | AI-Tox Predictor | MolProp Analyzer | MolSketch Analyzer | ClinPKPD | MPDS

MediConsultAI 
LLM- and RAG-based medical information assistant combining a curated medical knowledge base, vector retrieval, Gemini, LangGraph, and real-time web search to ground health responses in retrieved medical information and extend coverage to current, time-sensitive health topics.

MedGeroX 
AI- and LLM-enabled geromedicine platform integrating biomedical data and knowledge to analyse aging and longevity, accelerate evidence synthesis and support data-driven hypothesis generation for age-related health research.

GeroMedAI
AI framework integrating multi-omics data and biomedical knowledge to investigate ageing biology and healthy longevity.

ChemGraphX
Biomedical knowledge graph integrating over 2.8 million drug–target–disease relationships for systems-level biological discovery.

MolSimAI
AI platform for molecular similarity analysis, virtual screening and drug repurposing in early-stage drug discovery.

AI-MolProp Visualizer
Interactive platform for predicting, visualising and interpreting molecular physicochemical and drug-like properties.

PK Insight
Computational platform for analysing pharmacokinetic and pharmacodynamic relationships to support translational research.

DeepToxiLens
Deep learning framework for predicting compound toxicity and identifying potential safety liabilities during drug development.

AI-Tox Predictor
Machine learning platform for early prediction of toxicity profiles using molecular descriptors and biological data.

MolProp Analyzer
Computational tool for rapid analysis of molecular properties relevant to medicinal chemistry and lead optimisation.

MolSketch Analyzer
Interactive application for molecular sketching, property calculation and structural analysis of chemical compounds.

ClinPKPD
AI-enabled platform integrating pharmacokinetic and pharmacodynamic data to support precision medicine and clinical research.

ChemAICluster
AI-based molecular clustering and visual analytics platform for exploring chemical space, identifying structural relationships and prioritising compounds for drug discovery.

MPDS (Molecular Property Diagnostic Suite)
Computational framework for evaluating molecular properties and prioritising compounds for drug discovery applications.

Research Areas

Artificial Intelligence | Generative AI & LLMs | Data Science & Machine Learning | Biomedical Data Analytics | AI & Data-Driven Healthcare | Biomedical Informatics | Knowledge Graphs

Selective Peer-Reviewed Research Articles

  • Sharma R* (2024). Impact of Comorbidity on Severity of COVID-19 Patients: A Network of Target Coding Genes Perspective. Research Square (Preprint).
  • Sharma R* (2021). Network-based Approach Highlighting Interplay among Antihypertensives, Target-Coding Genes and Diseases. Scientific Reports, 10, 20152.
  • Sharma R* (2020). Data Science-Driven Analyses of Drugs Inducing Hypertension as an Adverse Effect. Molecular Diversity.
  • Sharma R* (2020). Cluster Analysis to Identify Prominent Patterns of Antihypertensives: A Three-Tiered Unsupervised Learning Approach. Informatics in Medicine Unlocked.
  • Sharma R*, Sagurthi SR, Sastry GN (2019). Elucidating the Preference of Protein Oligomerization for Thermal Stability. Journal of Molecular Graphics and Modelling, 96, 107530.
  • Gaur AS, Bhardwaj A, Sharma A, John L, Vivek MR, Tripathi N, Bharatam PV, Kumar R, Janardhan S, Mori A, Banerji A, Lynn AM, Hemrom AJ, Passi A, Singh A, Kumar A, Muvva C, Madhuri C, Choudhury C, Kumar DA, Pandit D, Bharti DR, Kumar D, Singam EA, Raghava GPS, Sailaja H, Jangra H, Raithatha K, Tanneeru K, Chaudhary K, Karthikeyan M, Prasanthi M, Kumar N, Yedukondalu N, Rajput NK, Saranya PS, Narang P, Dutta P, Krishnan RV, Sharma R, Srinithi R, Mishra R, Hemasri S, Singh S, Venkatesan S, Kumar S, Jaleel U, Khedkar V, Joshi Y, Sastry GN (2017). Assessing Therapeutic Potential of Molecules: Molecular Property Diagnostic Suite for Tuberculosis (MPDSTB). Journal of Chemical Sciences, 129(5), 515–531
  • Sharma R, Saha S, Badrinarayan P, Sastry GN (2014). Modeling Chemical and Biological (Re)activity. Book Chapter in Current Research & Information on Pharmaceutical Sciences.
  • Sharma R, Kothapalli R, Dongen AMJV, Swaminathan K (2012). Chemoinformatic Identification of Novel Inhibitors against Mycobacterium tuberculosis L-Aspartate α-Decarboxylase. PLoS ONE, 7, e33521.
  • Sharma R, Florea M, Nau W, Swaminathan K (2012). Validation of Drug-like Inhibitors against Mycobacterium tuberculosis L-Aspartate-α-Decarboxylase Using NMR. PLoS ONE, 7(9), e45947.
  • Singh NS, Shao N, McLean JR, Sevugan M, Ren L, Chew TG, Bimbo A, Sharma R, Tang X, Gould KL, Balasubramanian MK (2011). SIN-Inhibitory Phosphatase Complex Promotes Cdc11p Dephosphorylation and Propagates SIN Asymmetry in Fission Yeast. Current Biology, 21(23), 1968–1978

Teaching, Mentoring & Professional Education

  • Artificial Intelligence & Machine Learning
  • Generative AI, LLMs & AI Applications
  • Data Science & Biomedical Data Analytics
  • AI for Healthcare and Digital Health
  • Biomedical Informatics
  • AI systems, data-driven methods and scientific computing
  • Undergraduate and postgraduate teaching
  • Research mentoring and student supervision
  • Professional workshops, technical training and hands-on learning 

Consulting, Industry & Applied Research

  • AI & Data Science Solutions: Leads applied AI, Generative AI and data science initiatives, translating advanced methods into practical technology solutions and analytical systems.
  • AI & GenAI Platforms: Led the development of AI-enabled platforms including MediConsultAI, MedGeroX, GeroMedAI and ClinPKPD, applying LLMs, knowledge retrieval, machine learning and data-driven methods to real-world problems.
  • Biomedical Data & AI: Applies machine learning, LLMs, knowledge graphs and multi-source data integration to support data-driven discovery, evidence synthesis and applied research.
  • Research-to-Technology Translation: Translates research methods into deployable AI platforms, analytical tools and data-driven systems, bridging scientific research with real-world applications.
  • Industry & Research Collaboration: Works across multidisciplinary scientific and technical teams on applied AI, data science, technology development and research-driven solutions.
  • Technical Leadership: Provides scientific and technical direction across AI, Generative AI, LLMs and data science projects, including solution design, research strategy, technology development and evaluation.
  • Professional Engagement: Engages with researchers, technical professionals and stakeholders through scientific presentations, mentoring, workshops, technical training and knowledge-sharing activities. 

Professional Affiliations

  • American Chemical Society (ACS) — Member
  • Biotech Research Society, India (BRSI) — Life Member
  • National Academy of Biological Sciences (NABS) — Life Member
  • Peer Reviewer — Computers in Biology and Medicine, Molecular Diversity, Journal of Chemical Sciences