New Year Offer End Date: 30th April 2024
Program

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

Engineering the Future of Precision Medicine with AI, CRISPR, and CAR-T Innovation.

Skills you will gain:

About Program:

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.

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.

Program Objectives:

  • 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.

What you will learn?

📅 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

Mentor Profile

Fee Plan

INR 1999 /- OR USD 50

Get an e-Certificate of Participation!

Intended For :

  • 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

Career Supporting Skills

Program 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.

FREEDOM TO LEARN • 10% OFF All Courses & Workshops • Use Code: NANOINDIA10 • ⏳ Offer Ends In: Loading... • Learn Today. Lead Tomorrow. • Explore Programs →
FREEDOM TO LEARN • 10% OFF All Courses & Workshops • Use Code: NANOINDIA10 • ⏳ Offer Ends In: Loading... • Learn Today. Lead Tomorrow. • Explore Programs →
Support