Home /Biotechnology /Workshop /AI-Assisted CRISPR and CAR-T Cell Engineering for Precision Medicine

AI-Assisted CRISPR and CAR-T Cell Engineering for Precision Medicine

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Delivery Mode
Virtual / Online
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Level
Moderate
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Duration
3 Days (60-90 minutes)
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Certificate
Mentor Based
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Language
English
Rating
5 Stars
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About Workshop

This hands-on workshop explores AI-assisted CRISPR genome editing and CAR-T cell engineering for precision medicine. Participants will learn computational approaches for guide-RNA design, therapeutic target prioritisation, immune-cell engineering, and AI/ML-based analysis. The workshop integrates CRISPR, CAR-T, multi-omics, and AI workflows to support next-generation therapeutic research.
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Aim

To equip participants with practical skills in therapeutic CRISPR strategy selection, disease-variant analysis, base- and prime-editing design, AI-assisted guide prioritisation, off-target assessment, and sequencing-based evaluation of genome-editing outcomes.
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What Participants Will Learn

  • Understand therapeutic CRISPR-Cas9, base editing, prime editing, and gene-regulation approaches.
  • Retrieve and interpret disease-associated variants using ClinVar and Ensembl.
  • Select suitable genome-editing strategies for specific variants.
  • Design base-editing guide RNAs and prime-editing pegRNAs.
  • Assess PAM compatibility, editing windows, and bystander mutations.
  • Rank guide candidates using efficiency, specificity, and AI-assisted scoring.
  • Identify and prioritise potential genome-wide off-target sites.
  • Analyse CRISPR amplicon-sequencing data using CRISPResso2.
  • Quantify intended edits, indels, frameshifts, and editing purity.
  • Generate research-oriented figures, summaries, and computational reports.
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Structure

Workshop Structure

📅 Day 1: AI-Guided CRISPR Design for Precision Genome Editing

  • CRISPR-Cas9 mechanism, DNA repair, and genome-editing strategies
  • Target-gene, transcript, exon, and variant selection
  • Guide RNA, PAM, and editing-window principles
  • AI/ML-assisted guide-RNA scoring and prioritisation
  • Base editing and prime editing overview
  • Off-target prediction, specificity, safety, and ethics
🛠️ Hands-on: Target selection, guide-RNA design, computational scoring, and off-target assessment using sample datasets. 🧰 Tools: NCBI Gene, Ensembl, UCSC Genome Browser, UniProt, PubMed, Google Colab, Python, BioPython

📅 Day 2: CRISPR-Supported CAR-T Cell Engineering

  • CAR-T architecture, generations, and therapeutic applications
  • Tumour-antigen selection and target prioritisation
  • Major targets: CD19, BCMA, HER2, EGFR, and MSLN
  • CRISPR-based immune-cell engineering and gene knockout strategies
  • Universal and next-generation CAR-T concepts
  • Antigen escape, T-cell exhaustion, tumour microenvironment, and safety
🛠️ Hands-on: Analyse tumour-antigen expression data, prioritise CAR-T targets, and assess on-target/off-tumour risks. 🧰 Tools: Google Colab, Python, Pandas, NumPy, Matplotlib, Scikit-learn

📅 Day 3: AI-Integrated CRISPR–CAR-T Precision Therapeutics

  • AI-assisted therapeutic target discovery and prioritisation
  • CRISPR screening for resistance genes and therapeutic vulnerabilities
  • Multi-omics and single-cell approaches in precision immunotherapy
  • AI-based therapeutic response and toxicity prediction
  • Next-generation CAR-T: logic-gated, armoured, and universal platforms
  • Translational, regulatory, ethical, and biosafety considerations
🛠️ Hands-on: Build an AI/ML workflow for therapeutic response prediction and interpret key predictive features. 🧰 Tools: Google Colab, Python, Pandas, NumPy, Scikit-learn, Matplotlib, SHAP

Important Dates

Registration Ends

4:30 PM

Workshop Dates

2026-08-17
5:30 PM
5:30 PM
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What You Will Gain

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

  • Interpret disease-associated variants using ClinVar and Ensembl.
  • Select appropriate CRISPR, base-editing, or prime-editing strategies.
  • Design and rank guide RNAs and pegRNAs.
  • Assess PAM compatibility, bystander edits, and off-target risks.
  • Analyse amplicon NGS data using CRISPResso2.
  • Quantify editing efficiency, indels, substitutions, and frameshifts.
  • Prepare research-oriented figures, summaries, and analysis reports.
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Who Should Attend

  • UG and PG students in biotechnology, bioinformatics, genetics, genomics, molecular biology, and life sciences
  • Ph.D. scholars, research fellows, faculty members, and academicians
  • Bioinformaticians, computational biologists, and NGS professionals
  • Biotechnology, pharmaceutical, and clinical research professionals
  • Researchers interested in CRISPR, gene therapy, precision medicine, and therapeutic genome editing
Basic knowledge of molecular biology is recommended. Prior experience in CRISPR, programming, or NGS analysis is not mandatory.
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Deliverables

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