A Case Study in
NGS data has revolutionized biotechnology and drug discovery, but comes with many challenges including highly specialized and time-consuming data analysis.
We have worked with clients to store and analyze their NGS data, in addition to providing statistical consultation and software development services to support their R&D efforts.
As a result, our clients spend less money and time on data analysis than their competitors and are flexible to try innovative study designs that get them closer to breakthrough biologic therapies for difficult-to-treat cancers and other diseases.
Since their emergence in the mid-2000s, next-generation sequencing (NGS) platforms have revolutionized gene sequencing, offering dramatically higher throughput and lower costs compared to traditional Sanger sequencing. When the Human Genome Project was completed in 2003, it had taken 13 years and an estimated $3 billion US. Today, sequencing a human-sized genome is estimated to cost around $1,000 and takes as little as a day .
While NGS is now ubiquitous in biological research and drug development, it represents both a tremendous opportunity and challenge. First, NGS works by sequencing millions of small fragments or reads, generating massive amounts of data requiring storage, processing, and assembly. As such, analyzing NGS data can be computationally demanding and expensive, and requires specialized expertise. Error rates also vary across NGS platforms and typically exceed those of traditional sequencing, underscoring the need for quality control and careful examination of the data. Lastly, as cutting-edge research harnesses NGS for new applications, workflows must be more customizable and agile than ever.
Today, most organizations spend vastly more time and resources on NGS data analysis than they do on sequencing itself.
Our data scientists have training and experience in the life sciences, allowing for seamless collaborations with research scientists and sequencing vendors. With strong foundations in biostatistics and study design, we offer a unique and rigorous perspective when it comes to statistical analysis, and work with clients to develop an approach best suited to address their research question.
With Precision Analytics, our clients also benefit from our in-house software development team, who can be deployed to implement high performance cloud computing solutions, data management platforms, visualization tools, and more. Moreover, we support our clients' research and development activities at all stages, above and beyond NGS.
The use of NGS is not limited to whole-genome sequencing. NGS can comprise a key component of drug discovery platforms, especially for therapeutic antibodies.
Since their advent in the late 20th century, antibody-based therapies (“biologics”) have rapidly become some of the world’s best-selling pharmaceuticals , upending the way we treat many cancers and autoimmune diseases. Drug development in this area is still rapidly evolving and holds promise for many therapeutic areas.
Technologies such as antibody phage display allow researchers to generate and analyze vast “immune libraries” of antibodies or antibody fragments with the aim of identifying ones that bind specifically to a biological target of interest. The challenge comes in finding and characterizing the “needle in the haystack”, which is where NGS can play a pivotal role.
For instance, “biopanning” experiments can enrich a sample with antibodies that have higher affinity for a disease-causing target. Those antibodies, once expressed, can be characterized by NGS to identify sequences of interest.
We work with clients to ensure that they are getting the most out of their NGS data at every stage of their drug development pipeline.
First, we work to transform our clients' raw NGS data into actionable results. Depending on their needs, this has included steps such as:
- Generating quality reports and performing quality control
- Merging reads from paired-end sequencing
- Identifying specific genes or experimental constructs
- Examining sequence enrichment patterns
- Performing sequence alignments (e.g., BLAST )
- Applying supervised and unsupervised machine learning approaches
- Simulation studies to inform complex experimental designs
Our team is able to leverage a variety of proprietary and open-source tools, giving us flexibility to accommodate a variety of experiment types and data sources.
Lastly, we help our clients integrate their NGS data into their other R&D efforts. Some examples include:
- Custom APIs for clients to access and report their data
- Data management platforms that link NGS data with other in vitro and in vivo results
- In silico modelling of proteins and interactions
We develop tailored, automated NGS pipelines to break up the data analysis bottlenecks facing our clients. By providing everything from data storage to results reporting, we help them move quickly while staying focused on R&D.
As a consultancy, we are often more cost-effective and flexible than an in-house data science team. Moreover, our services go above and beyond data analysis, helping our clients improve their scientific process and rate of lead generation.
We work with clients to create robust and scalable solutions that are flexible to grow and evolve with their research programs. As the result of our services, our clients stay at the forefront of drug discovery innovation without being burdened by data analysis.
We have extensive experience working with NGS and other data sources, especially in the context of drug discovery and development. Whether your NGS application is industry standard or completely new, we are excited to work together for a more seamless and modern R&D pipeline.