Developing the next-generation genomics toolkit

NGS is the key to leveraging genomic data both to make clinical decisions right now and for future research. But sharing data is a pain point for the laboratory industry. Many labs, especially from academic institutions, would love to share their variant interpretations and receive the benefits of such collaborations, but lack access to a unified platform.

From the beginning, collaboration was the focus of the IGT system. Once there is a significant number of cases held in the system, it opens up the possibilities of collaborations based on population-level, well-characterised data. This collaborative effort helps to accelerate the potential value of personalised medicine for the global patient population.

The developer

With some scientists estimating that there will be as many as 2 billion human genomes sequenced by 2025,¹ life science executives are inundated with numerous data points. Here, Bob introduces a platform that curates this information to provide the best next action.

Q: How can users ‘leverage next-generation sequencing (NGS) data’?

A: The NGS revolution happened years ago, and today we have incredible instruments for cost-effective DNA sequencing. However, using these instruments at their full potential remains a challenge. Currently, most genetic tests are non-NGS genotyping tests or targeted sequencing. While these tests do not produce such a large amount of data, and results are typically much easier to interpret, they offer only part of the picture. This is a significant limitation.

Consider the case of rare inherited diseases. Many patients today go through years of a diagnostic odyssey: a harrowing journey that can be avoided if we do a single WES or WGS test in the very beginning. Moreover, many inherited diseases can be effectively managed or even cured at an early age, and we are missing a window of opportunity by not leveraging the full power of NGS from the start.

Q: How did your experts collaborate on this project?

A: The IGT was the vision of Genosity’s C-Suite team and founders: Dr Marc Grodman (CEO) and Dr Bob Daber (President and CTO). At this point, it is the first end-to-end platform solution that provides greater effectiveness and efficiencies versus historical piece-meal offerings. So, while Genosity provided guidance at every step, EPAM was driving the product engineering.

Genosity engages with clients, and through meetings with the EPAM team, the two organisations worked on creating solutions to each client’s requests. This was a painstaking process of collaborating for product ideation, gathering, and analysing requirements, as well as prototyping and building the solution. And it was an experience of continuous learning for both sides and the EPAM team always needed to consider the big picture. It is not just a LIMS or a single bioinformatic pipeline working in isolation; it is a complex ecosystem of many interlocking moving parts that work in unison.

The genomics experts

Informatics enable genomics, and inspiration for the IGT was based on real-world experience in clinical genomics at the very outset of NGS. Here, Michael explains how EPAM collaborated with Bob and his team to help develop this solution.

Q: What exactly is included in the new end-to-end genomics solution?
A: Dr Daber, the chief architect of the IGT platform, started with a blank whiteboard, deconstructed the entire genomic workflow and built a system comprised of the following integrated modules:

• Gateway Portal to place orders and access result reports
• LIMS for handling lab workflows
• Bioinformatics Pipelines to process raw genomic data from multiple sources in real-time
• Case Analyser for data analysis, variant classification, and result reporting
• Genosity Cortex for storing genomic data for population-level analytics

Unlike standalone systems, this modular system allows seamless data flow between ordering, wet lab LIMS, and case analysis and reporting applications and can be integrated with existing systems if desired.

Q: How did your experts collaborate on this project?

A: It involved a detailed iterative process between both teams where EPAM did requirement gathering, prototyping, and development, and Genosity reviewed, tested, and provided constant feedback. Genosity had to learn or understand to the point where we had to decide between the different approaches that could be used to accomplish the end goals. Our technical team had enough knowledge of the subject matter to guide the project.

Q: How does NGS benefit patient care?

A: The majority of genetic conditions at this point have been known to be associated with multiple genes. NGS is the most efficient and cost-effective way to perform testing on all those genes at the same time in a shorter turnaround time without compromising the test sensitivity. Nextgen sequencing has allowed scaling of genetic testing and screening at the population level that could not have been imagined 15 years ago. This would not have been possible if the software systems did not mature along with sequencing equipment. Therefore, informatics solutions that can scale to handle massive amounts of genomic data are crucial for NGS-based testing to work.

References:

1. Stephens, Zachary D. et al. “Big Data: Astronomical or Genomical?” PLoS Biol
   13, no. 7 (2015). https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002195

Authors:

Bob Daber is responsible for emerging systems for precision medicine at Genosity; genosity.com

Michael Wong is a Director in EPAM’s Global Account Management team; epam.com