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Nanotechnology · Moderate · Live online

AI-Powered CRISPR/Cas9 Nanoparticle Delivery: Non-Viral Gene Editing

From Guide RNA Design to Smart Nanoparticle Delivery — Use AI to Optimize Non-Viral CRISPR/Cas9 Gene-Editing Systems.

★ 4.2 (9 ratings)26–28 Oct 20265:30 PM IST3 Days (1.5 Hours Per Day)Certificate
The live sessions are over · get the full recording

About This Course

This 3-day virtual hands-on workshop introduces participants to the integration of CRISPR/Cas9 gene editing, non-viral nanoparticle delivery, and AI-based formulation optimization. Participants will learn how to design and evaluate guide RNAs, explore nanoparticle and molecular properties, build AI-ready delivery datasets, and use machine learning to predict gene-delivery performance and interpret key formulation parameters.

Aim

The aim of this workshop is to equip participants with practical knowledge of CRISPR/Cas9 target design, nanoparticle-based non-viral delivery, and AI-assisted delivery optimization for gene-editing applications.

Workshop Objectives

  • Understand CRISPR/Cas9 editing principles and major non-viral delivery strategies.
  • Design and evaluate guide RNAs using computational CRISPR tools.
  • Explore nanoparticle composition, physicochemical properties, and cargo-delivery mechanisms.
  • Build machine-learning models for predicting CRISPR delivery performance.
  • Apply explainable AI to identify formulation parameters influencing efficiency and safety.
Next: Day-by-day →

Workshop Structure

📅 Day 1: CRISPR/Cas9 Target Design, Guide RNA Selection & Off-Target Analysis

  • CRISPR/Cas9 mechanism, sgRNA design, PAM recognition, and gene-editing applications
  • Principles of guide-RNA selection and on-target efficiency
  • GC content, specificity, and guide-quality metrics
  • Off-target prediction and genome-editing safety
  • Comparative use of CRISPOR and CHOPCHOP
  • Selection of high-quality guides for therapeutic delivery

🛠️ Hands-on:

  • Select a target gene
  • Design guide RNAs using CRISPOR
  • Compare guide candidates using CHOPCHOP
  • Evaluate on-target and off-target scores
  • Rank guide RNAs for nanoparticle delivery

🧰 Tools Covered:

CRISPOR, CHOPCHOP, genomic sequence resources, and guide-ranking templates


📅 Day 2: Nanoparticle Design for Non-Viral CRISPR Delivery

  • Viral versus non-viral CRISPR delivery
  • Delivery of DNA, mRNA, sgRNA, and Cas9 RNPs
  • Lipid, polymeric, hybrid, and inorganic nanoparticle systems
  • Particle size, surface charge, composition, stability, and cargo loading
  • Cellular uptake, endosomal escape, and targeted delivery
  • Cytotoxicity, immune response, and biocompatibility
  • Structure–property relationships for CRISPR nanocarriers
  • Preparation of formulation data for AI modelling

🛠️ Hands-on:

  • Retrieve nanoparticle-related molecular data from PubChem
  • Generate descriptors and fingerprints using RDKit
  • Combine molecular and formulation properties
  • Visualise structure–property relationships
  • Prepare an AI-ready nanoparticle formulation dataset

🧰 Tools Covered:

PubChem, RDKit, Google Colab, Python, pandas, NumPy, Matplotlib, and formulation datasets


📅 Day 3: AI Prediction, Explainable Optimization & CRISPR Delivery Prioritization

  • Machine learning for nanoparticle formulation screening
  • Delivery-efficiency and safety prediction
  • Feature engineering for molecular and formulation parameters
  • Random Forest and XGBoost modelling
  • Model validation and performance evaluation
  • Explainable AI using SHAP
  • Identification of key drivers of delivery efficiency and toxicity
  • Multi-parameter formulation prioritization
  • Translational considerations in non-viral CRISPR delivery

🛠️ Hands-on:

  • Train an XGBoost model for delivery-performance prediction
  • Evaluate predictive accuracy
  • Interpret important features using SHAP
  • Compare nanoparticle candidates by predicted efficiency and safety
  • Integrate guide-RNA quality with formulation performance
  • Rank CRISPR delivery candidates for further validation

🧰 Tools Covered:

Google Colab, Python, RDKit, XGBoost, SHAP, pandas, scikit-learn, Matplotlib, and formulation-ranking templates

Who Should Enrol?

  • Graduate and Postgraduate Students in Biotechnology, Nanotechnology, Genetics, Molecular Biology, Bioinformatics, Biomedical Sciences, Pharmaceutical Sciences, and related disciplines
  • PhD Scholars and Researchers working in CRISPR/Cas systems, gene therapy, nanomedicine, drug/gene delivery, biomaterials, or computational biology
  • Academicians and Faculty Members interested in genome engineering, nanobiotechnology, translational research, and AI-assisted therapeutic development
  • Industry Professionals from biotechnology, pharmaceutical, gene-therapy, nanomedicine, formulation, preclinical R&D, and AI/ML drug-development teams
  • Basic knowledge of molecular biology or biotechnology is recommended; prior experience with CRISPR, Python, or machine learning is helpful but not mandatory
Next: Dates →

Important Dates

Registration Ends

October 26, 2026
IST 4: 30 PM

Workshop Dates

October 26, 2026 – October 28, 2026
IST 5:30 PM

Workshop Outcomes

  • Explain the CRISPR/Cas9 editing mechanism and major delivery challenges.
  • Design and compare guide RNAs using CRISPOR and CHOPCHOP.
  • Assess on-target efficiency and predicted off-target effects.
  • Understand major nanoparticle systems used for non-viral CRISPR delivery.
  • Evaluate formulation properties influencing cellular uptake and cargo delivery.
  • Retrieve molecular information from PubChem.
  • Generate molecular descriptors using RDKit.
  • Prepare AI-ready nanoparticle formulation datasets.
  • Train XGBoost models for delivery-performance prediction.
  • Evaluate predictive models using appropriate performance metrics.
Next: Mentor →

Meet Your Mentor(s)

Mentor Photo

Prof. Kumud Malhotra

Professor and Dean

Biotechnology

more


Next: Fees →

Recording fee

Participants in India

₹2,499

Participants outside India

$50

  • All session recordings
  • Study material
  • Certificate after completion
  • 1-year access

Get the recording

The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.

Next: FAQ →

Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

We’re here for you!


(+91) 120-4781-217
WhatsApp +91 99581 61117

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