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Flagship Internship — Now Enrolling

AI-Powered Drug Design

A comprehensive industrial internship program covering the full pipeline of AI-driven drug design, from molecular biology to machine learning and real-world case studies.

10 WeeksWeekends Only2.5 hrs / SessionOnline & GlobalCertificate
Program Overview

This industrial internship program is designed for students and professionals who want to step into one of the most exciting intersections of biology and artificial intelligence. Over 10 weekend sessions, participants will build a solid understanding of the drug discovery pipeline, work with industry-standard computational tools, and apply machine learning to real pharmaceutical problems. The program concludes with an industry-based case study — a portfolio-ready project to present to employers or academic institutions.

Two Tailored Tracks
Track 1
Undergraduate Program
Tailored for final-year undergraduates. Foundational modules emphasised with guided practical sessions and dedicated mentorship.
Track 2
Postgraduate, PhD & Industry
Advanced track for postgraduates, PhDs and professionals. Deeper focus on AI/ML, molecular dynamics and industry case studies.
Program Modules
01
Introduction to Drug Design and AI
Drug discovery process, economics, and AI in pharmaceutical research.
02
Cellular and Molecular Biology
Cell structure, cell cycle, biomolecules, receptors and secondary signalling.
03
Computational Software and Tools
PyMOL, ChimeraX, AutoDock Vina, PyRx, GROMACS, RDKit, DeepChem, OpenBabel.
04
Introduction to Pharmacology
Routes of administration, pharmacokinetics, ADMET properties, molecular descriptors.
05
Quantum Chemistry and DFT
Quantum mechanics basics, DFT fundamentals, molecular orbitals, HOMO/LUMO analysis.
06
Molecular Modeling and Docking
Rational drug design, homology modeling, docking, SBDD/LBDD, virtual screening.
07
Molecular Dynamics Simulation
MD principles, simulation setup, RMSD/RMSF analysis, binding free energy.
08
QSAR Statistical Methods
QSAR history, Hansch analysis, regression, 3D-QSAR, COMFA and COMSIA.
09
AI and Machine Learning in Drug Design
Supervised/unsupervised learning, deep learning, generative AI, AI ethics in pharma.
10
Industry-Based Case Study
Real-world drug discovery project. Portfolio-ready deliverable.
Software and Tools
PyMOLChimeraXAvogadroAutoDock VinaPyRxSwissDockGROMACSNAMDRDKitDeepChemOpenBabelR / RStudioPythonJupyter Notebook