Cell and gene therapy have emerged as promising approaches for the treatment of various diseases. These innovative therapies involve manipulating cells or genes to restore or enhance their function. Next-Generation Sequencing (NGS) plays a crucial role in the field of cell and gene therapy, providing researchers with valuable insights into genetic information and enabling personalized treatment strategies. This article explores the use of NGS in cell and gene therapy, highlighting its applications, advantages, challenges, and future perspectives. Additionally, it delves into the specific applications of NGS for Contract Research Organizations (CROs) and Contract Development & Manufacturing Organizations (CDMOs) involved in cell and gene therapy research, development & manufacturing.
Understanding NGS (Next-Generation Sequencing)
What is NGS?
NGS, also known as high-throughput sequencing, is a cutting-edge technology that allows rapid sequencing of DNA and RNA molecules. Unlike traditional Sanger sequencing, which can only sequence a single DNA fragment at a time, NGS enables the simultaneous sequencing of millions of DNA fragments. This massive parallel sequencing capability revolutionized genomics research and opened new avenues in various fields, including cell and gene therapy.
How does NGS work?
NGS involves several steps, starting with the fragmentation of DNA or RNA molecules into small fragments. These fragments are then amplified, sequenced in parallel, and aligned to a reference genome or transcriptome. The resulting sequences are analyzed using bioinformatics tools to identify genetic variations, gene expression patterns, and other relevant information. NGS techniques, such as whole-genome sequencing, targeted sequencing, and RNA sequencing, provide comprehensive genetic profiles for individual patients, facilitating personalized treatment approaches.
Advantages of NGS in cell and gene therapy
NGS offers several advantages in the context of cell and gene therapy. Firstly, it allows for a comprehensive analysis of genetic information, enabling researchers to identify disease-causing mutations, genetic variations, and therapeutic targets. This information is crucial for designing precise interventions tailored to individual patients. Secondly, NGS provides a high-throughput and cost-effective approach for large-scale sequencing, making it feasible to analyze a large number of patient samples. Additionally, NGS enables real-time monitoring of treatment response and the detection of minimal residual disease, enhancing treatment efficacy and patient outcomes.
Applications of NGS in Cell and Gene Therapy
Disease identification and diagnosis
NGS plays a pivotal role in identifying and diagnosing genetic diseases. By sequencing the entire exome or specific disease-related genes, researchers can pinpoint causative mutations responsible for inherited disorders. This information not only aids in accurate diagnosis but also guides treatment decisions, such as selecting the most appropriate gene therapy approach.
Gene editing and modification
NGS facilitates gene editing and modification by providing a comprehensive view of the genome. Researchers can identify target genes, design gene-editing tools like CRISPR-Cas9, and verify the success of gene modifications through NGS analysis. This precise gene editing allows for the correction of disease-causing mutations and the introduction of therapeutic genes, offering potential cures for genetic disorders.
Monitoring treatment response
NGS enables the monitoring of treatment response in cell and gene therapy. By analyzing the genetic profile of cells before and after therapy, researchers can assess the impact of the treatment on gene expression, identify off-target effects, and evaluate the persistence and integration of genetically modified cells. This information guides treatment optimization and ensures patient safety.
NGS has revolutionized personalized medicine in cell and gene therapy. By analyzing an individual’s genetic information, including variations in drug metabolism, therapeutic targets, and disease predispositions, NGS enables the development of tailored treatment strategies. Personalized medicine maximizes treatment efficacy while minimizing adverse effects, leading to improved patient outcomes.
Preclinical research and development
CROs and CDMOs utilize NGS in preclinical research to investigate the safety and efficacy of cell and gene therapies. By sequencing animal models’ genomes, researchers can identify potential safety concerns and evaluate the therapy’s impact on gene expression and cellular function. NGS provides valuable data for optimizing therapy protocols and ensuring the success of subsequent clinical trials.
Safety and efficacy assessments
NGS enables CROs and CDMOs to perform safety and efficacy assessments of cell and gene therapies. By analyzing the genomic profile of treated cells or tissues, researchers can identify unintended genomic modifications, off-target effects, or potential immune responses. This information helps ensure the safety of the therapies and provides insights into their effectiveness.
Quality control and process optimization
CROs and CDMOs rely on NGS for quality control and process optimization throughout the manufacturing and development of cell and gene therapies. NGS allows for the comprehensive characterization of starting materials, intermediate products, and final therapeutic products. By analyzing the genetic profile of cells or vectors used in manufacturing, NGS helps ensure consistency, purity, and integrity. It also aids in optimizing manufacturing processes for improved efficiency and scalability.
Challenges and Limitations of NGS in Cell and Gene Therapy
Data analysis and interpretation
The enormous amount of data generated by NGS presents a significant challenge in terms of data analysis and interpretation. Advanced bioinformatics tools and algorithms are required to analyze the complex genomic data and extract meaningful insights. Additionally, the interpretation of genetic variants requires expertise and careful consideration of various factors, such as variant pathogenicity, population frequency, and functional impact. Fortunately, commercial bioinformatics software solutions can help to demystify the analysis process and make NGS significantly easier to adopt as a technology. Most such approaches automate the analysis workflow, allowing users to easily upload their sequencing data, perform quality control, align reads to a reference genome, and detect genetic variants. Moreover, they nearly always incorporate state-of-the-art algorithms and tools, enabling users to obtain accurate and meaningful insights from their NGS data without requiring extensive bioinformatics expertise.
Regardless of the choice of vendor however, it is important to make sure that any such platform be usable by research scientists as well as bioinformaticians. Although ease of use is subjective, it is advisable to avoid software with overly functional graphical user interfaces that require several days of training for a researcher with a non computational background to become proficient with them. This reduces the number of individuals in any one organization who can perform the analysis and can ultimately lead to bottlenecks in the analysis part of the workflow. The approach of a point & click interface to run out of the box industry standard, powerful bioinformatics pipelines to simplify the complex process of NGS data analysis is a good one to take for those who are new to NGS and lack the in house expertise of what tools to use and how to set up the necessary IT infrastructure to run them. Alternatively, workflows that have been approved by an internal bioinformatician and that can be deployed to research scientists through the same intuitive interface represents an equally viable alternative. This approach of democratizing access to and analysis of NGS data to a wider group of scientists often frees up bioinformaticians to focus on more complicated data analysis problems.
Although analysis of the raw NGS data is essential, it’s equally important that the end result is not just a series of files available for download by the individual who has run the analysis itself. This could lead to the data needing to be interpreted by an expert bioinformatician, resulting in the aforementioned bottlenecks. Instead, consider choosing something that not only facilitates collaboration with colleagues, collaborators and even customers through secure data access and project management tools, but one that also generates interactive visualizations, such as heatmaps, volcano plots, and pathway enrichment analyses. This will enable research scientists to independently gain deeper insights into their experiment to more quickly make a determination of what the data means.
Standardization and quality control
Standardization and quality control are critical in NGS to ensure accurate and reliable results. Due to the rapid evolution of sequencing technologies and platforms, establishing standardized protocols and quality control measures is essential to minimize technical variability and ensure reproducibility across different laboratories and studies. For further information about the best practices associated with QC and pre-processing of NGS data, see this blog article.
Although the cost of NGS has significantly decreased over the years, it remains a significant factor to consider, especially in large-scale studies or clinical applications. It’s important to bear in mind that the total cost of leveraging NGS as a technology isn’t just the cost of the sequencing and library preparation. Data storage, bioinformatics analysis and the specialist personnel needed to do this should be carefully evaluated to ensure cost-effectiveness and sustainable implementation of NGS in cell and gene therapy. Consider using commercial bioinformatics software as a cost-effective solution for NGS data analysis. Instead of investing in expensive computational infrastructure and hiring bioinformatics experts, wet lab scientists can learn how to use hosted platforms such as the one provided by Basepair in a matter of hours. It’s also important to find a solution that can offer flexibility where pricing and licensing is concerned. If you plan to start off small with relatively few samples there is little point splashing out on a high up front license fee to use commercial software. Instead, consider opting for something that has a pay-as-you-go per sample usage model with no upfront license fee to start, with the option to migrate to an annual license at some point in the future if and when an increase in sample volume would justify the investment. Finally, be mindful of licensing models that are based on marking up compute and storage as a way of charging for commercial software. Cloud computing costs are only going to continue to come down, so a model like this can leave an organization with little to no control over those costs as sample volumes increase. Instead consider opting for a solution that leverages the compute & storage in your organization’s own cloud account to drive it. This leaves you in complete control of compute & storage costs as you own the contract with the infrastructure provider such as AWS. Moreover, leaving the data where it is helps alleviate data security & privacy compliance concerns, as well as helping you remain connected to the other resources you might have there.
The use of NGS in cell and gene therapy is expected to continue expanding in the future. Technological advancements will further enhance the speed, accuracy, and cost-effectiveness of NGS, making it more accessible for clinical applications. Additionally, integrating NGS data with other -omics technologies and artificial intelligence approaches will unlock new opportunities for personalized treatment strategies and precision medicine.
Next-Generation Sequencing (NGS) has revolutionized the field of cell and gene therapy, enabling a deeper understanding of genetic information and personalized treatment approaches. NGS plays a crucial role in disease identification, gene editing, treatment monitoring, and the development of personalized medicine. Its applications in CROs and CDMOs extend to preclinical research, safety assessments, efficacy evaluations, and quality control. Despite challenges in data analysis, standardization, and cost considerations, commercial bioinformatics software such as the Basepair platform can help address some of these concerns. Ultimately NGS holds immense potential for advancing cell and gene therapy and improving patient outcomes. As such it should be on every organization’s list of technologies to evaluate if it has not already been adopted.