2-Day National Workshop on

AI-Powered Next Generation Drug Designing & Discovery

From Algorithms to Molecules - Learn the Tools Reshaping Modern Drug Discovery

About the Workshop

Drug discovery is undergoing one of the most exciting transformations in its history. Artificial Intelligence and Machine Learning are no longer optional add-ons — they are now at the core of how molecules are designed, screened, optimised, and validated. From predicting binding affinities in seconds to generating entirely new chemical scaffolds, AI is reshaping every step of the pipeline.

This 2-Day National Workshop has been carefully designed to bridge the gap between traditional Computer Aided Drug Discovery (CADD) and the new wave of AI/ML-powered tools. Whether you are a beginner curious about how AI works, or a research professional looking to upgrade your skill set, this workshop will give you a structured, hands-on understanding of the tools, techniques, and career pathways that define this exciting space.

Across two intensive days, you will learn directly from accomplished researchers and industry experts through live demonstrations, hands-on training on real tools (SwissADME, ADMETlab 3.0, SwissDock, DiffDock, PyMOL, and more), and discussions on practical applications. The workshop ends with a dedicated career-focused session so you walk away not just with knowledge, but with a clear roadmap of where to go next.

Workshop Details:

Why Take This Workshop?

AI-driven drug discovery is one of the fastest-growing intersections of biology, chemistry, and computer science. Companies across India and abroad are actively hiring candidates who can combine domain knowledge with AI/ML skills — and the gap between demand and trained professionals is widening every quarter.

Here's what makes this workshop different:

• End-to-end coverage: From the basics of Machine Learning to advanced AI tools used in real-world drug discovery pipelines.

• Hands-on, not just theory: Every major session includes live demonstrations and guided practice on industry-relevant tools.

• Both classical and modern approaches: Learn traditional bioinformatics tools alongside cutting-edge AI tools — and compare them side by side.

• Faculty mix you won't find easily: Six experienced internal speakers plus an external expert bringing fresh industry perspective.

• Career clarity: A full session dedicated to job opportunities, hiring companies, and how to position yourself in this market.

• Beginner-friendly, professional-grade: Concepts are explained from first principles, but the tools and workflows are the same ones used by industry professionals.

Who Can Attend? (Eligibility)

This workshop has been structured to be accessible to learners across multiple disciplines. If you fall into any of the categories below, you are eligible to attend:

Students

• BSc / MSc / B.Tech / M.Tech / Integrated programmes in Bioinformatics, Biotechnology, Biochemistry, Microbiology, Pharmacy, Chemistry, Life Sciences, Computer Science (with biology interest), and allied fields.

• PhD scholars working in computational biology, medicinal chemistry, drug discovery, or related domains.

• Final-year students preparing for industry roles or higher studies in CADD / AI in life sciences.

Working Professionals

• Research Associates, Scientists, and R&D personnel in pharma, biotech, CRO, and CDMO companies.

• Bioinformaticians and computational biologists looking to add AI/ML tools to their workflow.

• Medicinal chemists and formulation scientists exploring AI-driven design strategies.

Faculty & Educators

• Assistant Professors, Lecturers, and academic researchers who want to integrate AI/ML in drug discovery into their teaching or research.

Career Switchers

• Professionals from adjacent fields (data science, software, chemistry) who want to enter the AI in drug discovery space.

Prerequisites: No prior coding or AI experience is required. A basic understanding of biology or chemistry concepts is helpful. A laptop / desktop with stable internet is recommended for hands-on sessions.

Key Benefits & What You Will Gain

Knowledge Outcomes

• A clear, structured understanding of AI and Machine Learning fundamentals, including supervised, unsupervised, and reinforcement learning.

• Working knowledge of how biological data is pre-processed, cleaned, parsed, and prepared for AI/ML pipelines.

• Conceptual clarity on Computer Aided Drug Designing (CADD) — both Ligand-Based and Structure-Based approaches.

• Understanding of QSAR modeling and how machine learning powers activity and toxicity prediction.

• Solid grasp of molecular docking principles and modern AI-driven docking workflows.

Hands-On Skills

• Run virtual screening using SwissADME and ADMETlab 3.0 to assess drug-likeness and ADME/T properties.

• Build and interpret a basic QSAR model using machine learning.

• Perform molecular docking using SwissDock (classical) and DiffDock (AI-based) — and compare results.

• Visualise and analyse docking results using Discovery Studio, RasMol, and PyMOL.

• Use AI/ML-based tools for virtual screening and drug discovery workflows.

Career Benefits

• Direct exposure to the AI in Drug Discovery career landscape — companies in India and abroad actively hiring in this space.

• Insights on how to build your network, identify the right job boards, and position your profile for AI-CADD roles.

• Workshop participation certificate from Biotecnika to add to your CV, LinkedIn, and academic record.

• Live Q&A with all speakers — an opportunity to clarify doubts and get personalised guidance.

• Access to recommended resources and further learning pathways shared by faculty.

Workshop Schedule

The workshop is structured across two days, building progressively from foundational AI/ML concepts to advanced AI-driven drug discovery workflows and career pathways.

DAY 1  —  FOUNDATIONS & CORE CADD

Friday, 23rd May 2026  |  10:00 AM – 1:30 PM IST

Session 0  ▸  Introduction   |   10:00 – 10:10 AM   |   Host

• Speaker addressal and introductory notes

Session I  ▸  Introduction to AI / ML   |   10:10 – 11:00 AM   |   External Speaker

• Introduction to AI and ML with examples

• Basic principles and types of ML algorithms

• Supervised, Unsupervised, and Reinforcement Learning

Session II  ▸  AI / ML in Biological Data Analysis   |   11:00 AM – 12:00 PM   |   Dr. Neeraj Kumar

• Introduction to AI/ML in biological data analysis

• Data pre-processing, cleaning, parsing, and handling missing data

• Importance and applications of AI/ML in biological data analysis

• Hands-on training: Biological data analysis using AI/ML algorithms

Session III  ▸  Introduction to Drug Discovery   |   12:00 – 1:00 PM   |   Dr. Bhupender Singh

• What is Computer Aided Drug Designing & Discovery (CADD)?

• Types of CADD: Ligand-Based and Structure-Based Drug Designing

• Methods of Virtual Screening: Drug-Likeness, ADME/T

• Hands-on training: Virtual Screening on SwissADME / ADMETlab 3.0

Session IV  ▸  QSAR Modeling in Drug Discovery   |   1:00 – 1:30 PM   |   Dr. Nilofer K. Shaikh

• QSAR workflow and model development

• Machine Learning in QSAR

• Applications in activity and toxicity prediction

• Hands-on training: Basic QSAR example

Closing  ▸  Conclusion of Day 1   |   1:30 PM   |   Host

• Recap of Day 1 and bridge to Day 2

DAY 2  —  AI TOOLS, DOCKING & CAREER

Saturday, 24th May 2026  |  10:00 AM – 1:30 PM IST

Introduction  ▸  Day 2 Opening   |   10:00 – 10:10 AM   |   Host

• Speaker addressal and introductory notes

Session I  ▸  Molecular Docking & Result Analysis   |   10:10 – 11:15 AM   |   Mr. Prodyot Banerjee

• Molecular Docking introduction and principles

• Hands-on training: Molecular Docking using SwissDock (Bioinformatics tool) and DiffDock (AI tool) — comparative analysis

• Hands-on training: Docking result and interaction visualization using Discovery Studio / RasMol / PyMOL

Session II  ▸  AI / ML in Drug Discovery   |   11:15 AM – 12:20 PM   |   Dr. Shubhi Singh

• Introduction to AI/ML in Computer Aided Drug Discovery (CADD)

• AI/ML-based tools for virtual screening and docking

• Importance and applications of AI/ML-based tools in CADD

• Hands-on training: AI/ML-based tools used in the drug discovery process

Session III  ▸  Career Prospects   |   12:20 – 1:00 PM   |   Dr. Elamathi

• Career and opportunities in AI-based Drug Discovery

• List of companies working in the field (India and Abroad)

• Job boards and how to build your network

Final Session  ▸  Q&A and Closing   |   1:00 – 1:30 PM   |   All Speakers

• Open discussion and questions

• Recap of key concepts and techniques

• Resources and further learning opportunities

• Future directions and emerging trends in AI-based Drug Discovery

• Conclusion and vote of thanks

Tools You Will Work With

This workshop is hands-on. You will see live demonstrations and follow along with the following industry-relevant tools across the two days:

• SwissADME — for drug-likeness and pharmacokinetic property prediction

• ADMETlab 3.0 — for advanced ADME/T property analysis

• SwissDock — classical molecular docking

• DiffDock — AI-based molecular docking

• PyMOL — molecular visualisation and analysis

• Discovery Studio — interaction analysis and visualisation

• RasMol — lightweight molecular structure visualisation

• AI/ML algorithms and frameworks for biological data analysis and QSAR

Certification

All participants who complete the workshop will receive a Biotecnika Workshop Participation Certificate. The certificate is suitable for use on your CV, LinkedIn profile, and academic portfolio, and serves as evidence of structured training in AI-powered drug discovery.

Seats are limited to ensure quality interaction during hands-on sessions. To register or for any queries, please reach out to the Biotecnika team at [email protected]

Step into the future of drug discovery — where biology meets AI.

Reserve your seat for the 2-Day National Workshop today.