by Pedro Echave, Ph.D., Senior Product Manager, Revvity
As the bioprocessing industry expands to include more intricate biotherapeutics and bioprocesses, each presenting distinct challenges, next-generation sequencing (NGS) is becoming a cornerstone technology. NGS is proving to be a valuable tool for enhancing product quality, safety and workflow efficiency, as demonstrated by research studies.
The core principle underpinning NGS that is massively parallel sequencing represents a fundamental departure from the serial processing characteristic of traditional Sanger sequencing, allowing the shift from analyzing one DNA strand at a time to simultaneously processing millions or even billions of fragments.1
The introduction of NGS has instigated a significant paradigm shift in bioprocessing analytics, offering capabilities that far surpass those of conventional molecular techniques such as Sanger sequencing and quantitative polymerase chain reaction (qPCR).
Transforming the bioprocessing pipeline
1. Cell line characterization and development
In the early stages of bioprocessing, NGS provides a powerful tool for characterizing and optimizing production cell lines, such as Chinese hamster ovary (CHO) cells, which are the most widely used mammalian host for biologics manufacturing. NGS can verify cell line identity, assess genomic integrity and stability, and profile gene expression patterns to ensure consistent, safe and effective production of biopharmaceuticals. It can identify genetic variants, insertions, deletions, and off-target integration events, supporting regulatory compliance and product quality.
- Monoclonality and stability: NGS is used to confirm that a production cell line originates from a single cell ("monoclonality"). It can also track the genetic stability of the cell line over many generations to prevent genetic drift, which could change the properties of biologics.
- Host cell characterization: Regulatory guidelines require thorough genetic characterization of host cell lines. NGS provides a comprehensive "genomic fingerprint" that confirms its identity and detects unwanted mutations or structural variants.
A review has been recently published on how NGS is used to characterize the genome, epigenome, and transcriptome of cell lines. Applications include monitoring genetic variability, confirming the sequence and integrity of plasmids before transfection, mapping integration sites of therapeutic genes, and verification of a cell line's monoclonality. This molecular understanding helps build a data-driven foundation for rational engineering strategies to improve cell line performance.2
2. Viral safety testing and adventitious agent detection (ADD)
NGS is now widely used to detect both known and unknown viral contaminants, offering a significant advantage over traditional, targeted methods limited to expected sequences. This capability is particularly critical for the production of vaccines, monoclonal antibodies, and gene therapies. When used as an adventitious agent detection (AAD) tool, NGS can screen for viruses, bacteria, and mycoplasma in a single assay, supporting the safety of both the final product and the manufacturing process. Its unbiased nature is especially valuable for detecting unexpected or emerging agents that might be missed by conventional methods.
A study by Charles River Laboratories and PathoQuest published in Vaccine, demonstrated that a proprietary NGS-based assay was more effective at detecting viral contaminants than traditional in vivo animal-based assays. The authors concluded that it offers a robust and effective alternative, aligning with the updated ICH Q5A(R2) guideline, which endorses the use of NGS to reduce or replace animal testing in biologics safety evaluation.3
3. Bioprocess monitoring and quality control (QbD)
Beyond biosafety, NGS supports bioprocess monitoring and quality control, aligning with Quality-by-Design principles. Applied from cell line development to final product release, NGS offers molecular-level insight into the genetic stability and identity of production systems, enabling consistent, reproducible biomanufacturing.
- Genetic identity: NGS confirms the integrity of the transgene and absence of unintended sequence changes introduced during cell banking or scale-up.
- Post-translational modification: Many biopharmaceuticals, such as monoclonal antibodies, require specific post-translational modifications (like glycosylation) to be effective. While NGS cannot directly measure post-translational modifications NGS, its integration with proteomics and metabolomics helps link transcriptional changes to variations in post-translational modifications that affect product quality.
An industry survey by Genedata involving over 30 biopharmaceutical companies highlighted that NGS is becoming the method of choice for master cell bank (MCB) release testing. This ensures cell line product quality across different manufacturing sites and batches, a crucial step for maintaining compliance with GMP regulations. The survey also found that NGS-based assays are frequently used for adventitious agent and variant detection.4
4. Optimizing productivity
One of the key goals in bioprocessing is maximizing yield without compromising quality. NGS contributes to this goal in several ways:
- Integration site analysis (ISA): In gene therapy and other applications, a new gene is inserted into the host cell's genome. NGS precisely maps where a viral vector (e.g., a lentivirus) has been inserted. This is a critical safety and efficacy measure required for new gene therapies because the insertion site can impact the stability and expression level of the therapeutic gene.
This analysis aims to confirm, for example, that the gene has not inserted near a proto-oncogene. It also helps to monitor the long-term stability and clonal expansion of the gene-corrected cells.
- Gene expression analysis: RNA-seq can profile transcriptional differences between high- and low- producing clones, identifying pathways that limit productivity or affect protein quality, and allowing for targeted engineering to improve the cell line's performance.
The pharmaceutical company Merck, in collaboration with the Moffitt Cancer Center, utilized sRNA-seq to profile the tumor microenvironment and develop predictive biomarkers for response to the immunotherapy pembrolizumab (KEYTRUDA). By analyzing a large cohort of tissue samples researchers identified a “T-cell inflammation” gene expression profile, alongside of signatures linked to angiogenesis and other biological pathways.
These transcriptional signatures provided a more precise means for stratifying individuals beyond traditional PD-L1 expression testing. The successful identification of these transcriptional markers helps select appropriate therapies and informs the development of future combination therapies.5
These examples illustrate the shift from traditional, often slower and less comprehensive, methods to a more efficient, data-rich approach using NGS. The technology's ability to provide deep molecular insights at every stage of the bioprocessing workflow is making it an indispensable tool for the biopharmaceutical industry.
Navigating the NGS implementation hurdles
While implementing NGS presents significant opportunities in bioprocessing, companies must carefully navigate a range of operational and regulatory challenges for its adoption. Chief among these are the "big data" demands of NGS and the need for clear, standardized workflows. Key barriers include:
- Complex bioinformatics and data management
- Lack of standardization and QA
- Regulatory ambiguity and validation requirements
- Shortage of skilled personnel
- Sample preparation and technical limits
As NGS-based assays are increasingly used in biopharmaceutical development and manufacturing for product characterization and biosafety testing their implementation in a GMP (Good Manufacturing Practice) environment, known as a GxP environment, requires specialized tools and reliable workflows to ensure data integrity and regulatory compliance.
NGS datasets can range from several gigabytes to hundreds of gigabytes per sample. For example, a 30× whole human genome typically generates ~150 GB of raw data. Even smaller-scale assays require significant computational resources and secure, compliant storage.6
The power of a strong collaboration
In regulated biomanufacturing, the successful implementation of NGS relies on close collaboration among developers, manufacturers, and technology providers. Pre-competitive industry initiatives are helping to define standards, streamline workflows, and align with evolving regulatory guidance. Regulatory authorities are increasingly providing frameworks for NGS validation in GMP contexts, ensuring data integrity and reliable performance.
By committing to shared standards and knowledge exchange, the industry can accelerate the transition from discovery-stage NGS applications to fully compliant, production-ready workflows, enabling faster, safer and more effective delivery of biotherapeutics.
About the author
Pedro Echave, Ph.D., is a Senior Product Manager at Revvity, specializing in next-generation sequencing (NGS) solutions. With a strong background in molecular biology, he is part of the team at Revvity driving the development and commercialization of innovative products for genomics research.