Catherene Tomy Drug Discovery Scientist,
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With approximately three years of industrial experience in drug discovery and chemoinformatics, combined with a solid foundation in disease biology and molecular biology, I am equipped to offer comprehensive educational sessions. My expertise extends to providing detailed insights into AI-based drug discovery, designing and implementing projects and pipelines in this domain from scratch.
I offer hands-on guidance with bioinformatics tools and databases such as Molecular Docking, PyMOL, QSAR modeling, PDB, ChEMBL, UniProt, and more. Additionally, I can assist in dissecting and analyzing research publications, helping you understand and evaluate various components of scientific studies. My goal is to facilitate a deeper understanding and practical experience in these cutting-edge fields.

Subjects

  • Biotechnology and Bioinformatics IGCSE-Masters/Postgraduate

  • Pharmacoinformatics, Chemoinformatics and Bioinformatics Beginner-Expert

  • Drug discovery Beginner-Expert

  • Molecular docking Beginner-Intermediate

  • QSAR Modeling Beginner-Expert

Experience

  • Drug Discovery Scientist (Jan, 2023–Present) at Boltzmann Labs, Bangalore
    I leverage my expertise in bioinformatics, disease biology, and artificial intelligence to spearhead drug discovery programs and develop AI-based tools for small molecule drug discovery. My role involves designing comprehensive workflows for various stages of drug development, including Hit Generation, Lead Generation, and Lead Optimization. I utilize a range of bioinformatics techniques, such as QSAR modeling, Molecular Docking, Molecular Dynamic Simulations, and De-novo molecule generation. Additionally, I simplify and convey complex drug discovery and biological concepts to AI professionals, enabling them to create innovative tools.
  • Research Fellow (Sep, 2022–Mar, 2023) at Omics Logic, Pine Biotech
    I conducted a study on the RNA expression dataset for pancreatic cancer to analyze its transcriptomic profile using unsupervised machine learning techniques. The project can be explored through this link: https://omicslogic.com/projects/JcMPhm4vgAXStSQWGTsTe4W8Ehg2/exploring-the-transcriptomic-landscape-of-pancreatic-cancer-through-unsupervised-machine-learning
  • M.Tech (Sep, 2021–Aug, 2022) at Amrita School of Nanosciences and Molecular medicine
    I conducted a comprehensive Quantitative Structure-Activity Relationship (QSAR) analysis on small molecules to investigate their properties. Based on the insights gained from this study, I designed small molecule inhibitors. The results of this research were published in the Elsevier Journal: https://doi.org/10.1016/j.aichem.2023.100012
  • B.Tech (Sep, 2019–Jun, 2020) at Karunya University, Coimbatore
    Conducted a study to examine the synergistic effects of Sorafenib combined with a plant extract from Platycladus orientalis. This research utilized molecular biology techniques including the MTT assay and RT-PCR. The findings are published in:https://doi.org/10.14393/BJ-v39n0a2023-62558

Education

  • RESEARCH FELLOWSHIP PROGRAM (Sep, 2022–Mar, 2023) from Omics Logic
  • M.TECH IN MOLECULAR MEDICINE (Jul, 2020–Aug, 2022) from Amrita university coimbatore–scored 9.54
  • B.TECH IN BIOTECHNOLOGY (Jul, 2016–May, 2020) from KARUNYA UNIVERSITY,Coimbatore–scored 8.92

Fee details

    ₹1,500–7,000/hour (US$17.84–83.24/hour)

    For beginner students learning basic biological concepts, the rates will be lower. However, if the content involves advanced topics such as core drug discovery, chemoinformatics, or assistance with running a drug discovery pipeline and using specialized tools and methods, the rates will be higher.

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