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May 1, 2026

Registration closes May 1, 2026

TechBio Unleashed: AI, Automation, and the Future of Biotechnology

Where Biology Meets Intelligence, Automation, and Innovation

  • Mode: Virtual / Online
  • Type: Mentor Based
  • Level:
  • Duration: 3 Days (1.5 Hours Per Day)
  • Starts: 1 May 2026
  • Time: 8:00 PM IST

About This Course

This workshop provides a practical overview of the TechBio ecosystem, including AI/ML in biotech R&D, robotic lab automation, cloud-based data pipelines, synthetic biology platforms, digital twins, and smart biomanufacturing. Participants will explore real-world use cases and future career pathways in AI-enabled biotech innovation.

Aim

This workshop aims to introduce participants to the emerging field of TechBio, where biotechnology meets AI, automation, robotics, and data-driven discovery. It focuses on how modern biotech companies use digital tools to accelerate research, product development, and biomanufacturing. Participants will learn how AI and automation are transforming drug discovery, synthetic biology, diagnostics, omics, and lab workflows. The program prepares learners for the future of technology-enabled biotechnology.

Workshop Objectives

  • Understand the TechBio landscape and its impact on biotechnology.
  • Explore AI and machine learning applications in biotech R&D.
  • Learn how automation and robotics improve lab productivity.
  • Understand digital tools for omics, diagnostics, drug discovery, and biomanufacturing.
  • Identify future opportunities in AI-driven biotechnology careers.

Workshop Structure

Day1: Introduction to TechBio and AI-Driven Biotechnology

  • Role of AI, automation, and biological data in biotechnology 
  • Data challenges: complexity, noise, high dimensionality 
  • Explore a biological dataset in Google Colab
  • Inspect data using Pandas
  • Visualize biological features
  • Perform BLAST sequence search
  • Explore protein data in UniProt
  • View protein interaction network in STRING
  • Build a simple ML classification workflow
  • Tools: Google Colab, NCBI, PubMed / literature search & demo & UniProt

Day 2: AI Drug Discovery, Protein Intelligence, and Generative Biology

  • Search molecules in PubChem
  • Extract SMILES notation
  • Analyze molecular properties using RDKit
  • Check drug-likeness using SwissADME
  • Build a simple compound activity prediction workflow
  • Explore protein structures using AlphaFold DB
  • Visualize protein structures using Mol* / PyMOL
  • Understand molecular docking through a concept demo

Day 3: Lab Automation, Self-Driving Labs, and Future TechBio Innovation

    • Design a closed-loop TechBio workflow
    • Create a simple lab experiment tracker
    • Build an AI-assisted bioprocess monitoring plan
    • Map input variables such as temperature, pH, dissolved oxygen, and feed rate
    • Identify output variables such as growth rate, yield, and contamination risk
    • Create a no-code automation concept for experiment updates and notifications
    • Prepare a basic responsible AI checklist for biotech workflows
    • Tools: Python / Google Colab 

Who Should Enrol?

  • Undergraduate/postgraduate degree in Biotechnology, Bioinformatics, Life Sciences, Computational Biology, Data Science, or related fields.
  • Professionals working in biotech, pharma, diagnostics, AI/ML, automation, or biomedical R&D sectors.
  • Data scientists and AI/ML engineers interested in applying technology to biotechnology workflows.
  • Individuals with a keen interest in the future of AI-powered biotechnology and bio-innovation.

Important Dates

Registration Ends

May 1, 2026
IST 7:00 PM

Workshop Dates

May 1, 2026 – May 3, 2026
IST 8:00 PM

Workshop Outcomes

Participants will be able to:

  • Understand how AI and automation are transforming biotechnology.
  • Identify key TechBio applications in drug discovery, diagnostics, and omics.
  • Explain the role of robotics and smart labs in modern biotech workflows.
  • Recognize career pathways in AI-driven biotechnology.
  • Develop a future-ready perspective on digital and automated biotech innovation.

Meet Your Mentor(s)

Mentor Photo

DR. SUBARNA THAKUR

Assistant Professor
Department of Bioinformatics, University of North Bengal

Dr. Subarna Thakur is an Assistant Professor in the Department of Bioinformatics at the University of North Bengal. She received her Ph.D. Degree in Botany from the University of North Bengal in 2014 and then worked as a Post Doc in various institutes like JNU, Bose Institute and IRHS, Angers, . . . France for 4 Years. She is having more than 10 Years of Experience in the field of Computational Biology and Genomics. Her Area of Expertise includes NGS Data analysis, Transcriptomics, Network Biology. She is the author of 10 original research articles in high-impact peer-reviewed journals.

Fee Structure

Student Fee

₹2499 | $65

Ph.D. Scholar / Researcher Fee

₹3499 | $75

Academician / Faculty Fee

₹4499 | $85

Industry Professional Fee

₹5499 | $95

What You’ll Gain

  • Live & recorded sessions
  • e-Certificate upon completion
  • Post-workshop query support
  • Hands-on learning experience

Need Help?

We’re here for you!


(+91) 120-4781-217

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