About Workshop
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.
What Participants Will Learn
- 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.
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
- 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
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- 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
Important Dates
Registration Ends
7:00 PM
Workshop Dates
2026-05-01
8:00 PM
8:00 PM
What You Will Gain
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.
Who Should Attend
- 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.