nCounter® Gene Therapy Optimization Panel

A Circular diagram about gene therapy

Helping Your Research

Some genetic diseases are caused by malfunctioning or missing genes. Gene therapy can deliver life-changing therapies by adding, inhibiting, editing, or functionally replacing the malfunctioning gene. However, the promise of gene therapy does not come without technical challenges. Unwanted immune reactions can be triggered by the therapeutic vector, or the vector can target the wrong cell. Vector introduction can also cause an unintended infection or lead to the development of a tumor. Finally, the introduced gene must get activated and remain functioning in the intended state. Therapy development is thus complex and requires optimization, in addition to monitoring throughout the entire development process.  

The nCounter® Gene Therapy Optimization Panel standardizes the entire gene therapy process from vector development and viral manufacturing to post-treatment monitoring. The panel content measures innate and adaptive immune responses, and addresses critical questions related to host-vector interactions. The panel can also be used to understand toxicities resulting from gene therapy treatments.

How It Works

Feature Details
Customization
Data Analysis
Feature Details

Feature Details

  • Directly profile 800 genes across 40 pathways
  • Study processes known to impact gene therapy development and manufacturing
    • Cell State
    • Host-Vector Interactions
    • Innate Immune Response
    • Systemic Immunity
    • Toxicity
  • Understand factors influencing optimal gene therapy development and manufacturing
  • Monitor for toxicities
  • Quantify the presence and relative abundance of different immune cell types present during therapy
  • Customize to incorporate therapy specific biology, enabling parallel monitoring of therapy and host response biology
  • Generate data in 24 hours with less than 30 minutes hands on time and simple data analysis
Customization

Customization with Panel Plus

Customize your research project by adding up to 55 user-defined genes of interest with nCounter Panel Plus. Panel Plus capacity enables researchers to address content specific to their research areas of interest. Incorporate gene therapy specific biology to monitor therapy-based biology and host response biology in parallel. Measure unique viral vector expression or perform viral vector optimization.

Data Analysis

Data Analysis

In addition to the standard nSolver™ Analysis Software, genes included in the Gene Therapy Optimization Panel are organized and linked to various advanced analysis modules to allow for efficient analysis of relevant pathways.

Analysis Modules available for Gene Therapy Optimization: 

  • Normalization
  • Quality Control
  • Individual Pathway Analysis
  • Cell Profiling
  • Differential Expression
  • Gene Set Analysis
  • Built-in compatibility for Panel Plus and Protein analysis

ROSALIND® Platform

ROSALIND is a cloud-based platform that enables scientists to analyze and interpret differential gene expression data without the need for bioinformatics or programming skills. ROSALIND makes analysis of nCounter data easy, with guided modules for:

  • Normalization
  • Quality Control
  • Individual Pathway Analysis Differential Expression
  • Gene Set Analysis

nCounter customers can access ROSALIND free of charge at https://www.onramp.bio/nanostring.

Contact Us

Related Resources

Product Bulletin nCounter® Gene Therapy Optimization Panel – Product Bulletin
Brochure Cell & Gene Therapy Solutions Brochure

Product Information

Product Specifications
Themes
Immune Cell Profiling
Support Documents
Catalog Information
Product Specifications

Product Specifications

Themes

Panel Themes

The Gene Therapy Optimization Panel includes annotations across 5 functional themes related to gene therapy development and manufacturing. Pathway coverage is outlined in the table below.

Immune Cell Profiling

Immune Cell Profiling Feature

Genes included in the Gene Therapy Optimization Panel provide unique cell profiling data to measure the relative abundance of 14 different immune cell types. The table below summarizes the genes included in each cell type signature, as qualified through biostatistical approaches and selected literature in the field of immunology.

Support Documents

Support Documents

Catalog Information

Catalog Information