NextGen Drug Discovery
with AI
Master Computational Drug Discovery through Cheminformatics, Structural Bioinformatics, Molecular Modeling, Molecular Dynamics, and Artificial Intelligence.
Your path from foundations to frontier AI
Nine progressive stages take you from Python fundamentals to a fully integrated, AI-driven drug discovery pipeline.
Foundations
Python programming, scientific computing, and the core biology/chemistry needed for computational drug discovery.
Where computation meets the frontier of medicine
NextGen Drug Discovery with AI is a rigorous, hands-on program built for the new era of AI-accelerated pharmaceutical research.
Why Computational Drug Discovery
Traditional wet-lab drug discovery takes over a decade and billions of dollars per approved drug, with high attrition at every stage. Computational methods let researchers simulate, screen, and prioritize candidates in silico — dramatically cutting cost, time, and risk before a single compound reaches the lab bench.
The AI Revolution in Pharma
AI and deep learning are reshaping every stage of the pipeline — from predicting protein structures with tools like AlphaFold and ColabFold, to generating novel molecules and forecasting binding affinity with graph neural networks. This program builds the exact skill set the AI-driven pharma industry is hiring for right now.
Real Pharmaceutical Applications
Learn the same workflows used inside pharmaceutical and biotech R&D — target identification, virtual screening, molecular docking, molecular dynamics validation, and lead optimization — using the industry-standard open-source tools that power real drug discovery programs.
Growing Industry & Research Demand
Computational and AI drug discovery roles are among the fastest-growing in biotech, pharma, and academic research. This program prepares you for careers and research opportunities in cheminformatics, structural bioinformatics, CADD, and AI-driven molecular design.
8 modules, one integrated pipeline
Each module builds directly on the last, culminating in a complete, end-to-end computational drug discovery project.
- Python for scientific computing
- Drug discovery pipeline overview
- Biology & chemistry primer for computation
- Working in Google Colab Pro
Build a portfolio that proves you can do the work
Every concept is reinforced with a real, hands-on project using authentic research data and industry-standard tools.
Drug Discovery Pipeline
Build a complete target-to-lead computational pipeline from scratch.
Molecular Docking
Dock small molecules against a protein target using AutoDock Vina.
Virtual Screening
Screen large compound libraries to identify promising hit candidates.
Molecular Dynamics
Simulate protein-ligand complexes and analyze stability over time.
Protein Structure Analysis
Analyze binding pockets and structural features from PDB structures.
AI Molecular Property Prediction
Train ML models to predict bioactivity and physicochemical properties.
Graph Neural Networks
Represent molecules as graphs and predict properties with GNNs.
Protein-Ligand Prediction
Predict binding affinity using deep learning on structural data.
Lead Optimization
Optimize hit compounds into viable leads using computational strategies.
20+ industry-standard tools, hands-on
Every module is taught with the real open-source software used across pharma and academic computational research.
What you'll walk away able to do
By the end of the program you'll have practical, portfolio-ready command of the full computational drug discovery stack.
Built for the next generation of drug discovery scientists
Whether you're starting out or advancing an existing research career, this program meets you where you are.
Everything you need to know
Learn from a computational drug discovery team
A program lead and a team of pharmacy graduates and CADD experts guiding every session.
Md. Jubayer Hossain
Founder & CEO, DeepBio Ltd
Bioinformatician and computational biologist who has trained 3,000+ students since 2020. Every student in this program works directly with him — not a TA, not a substitute — toward a real, submittable research output.
You bring the curiosity — I bring the roadmap, the tools, and the accountability to get you there.
0+
Years Research
Computational chemistry & structural bioinformatics.
0+
Years Mentoring
Guiding beginners through graduate researchers.
3K+
Students Trained
Live cohorts and workshops since 2020.
0+
Publications
Peer-reviewed cheminformatics & AI research.
Instructors
Earn a certificate that proves what you can build
Complete the program and capstone project to receive an official DeepBio Academy certificate of completion.
DeepBio Academy
Certificate of Completion
This certifies that
Your Name Here
has successfully completed the NextGen Drug Discovery with AI program, covering cheminformatics, structural bioinformatics, molecular dynamics, and AI for drug discovery.
Issued
Upon Completion
Signed
Lead Instructor
Frequently asked questions
No prior computational background is required. The program starts with Python foundations and a biology/chemistry primer before progressing into advanced cheminformatics, structural bioinformatics, and AI topics.
Become the Next Generation
Drug Discovery Scientist.
Seats for the live cohort are limited. Apply today and start building your computational drug discovery portfolio in three months.