What’s next for NGS?

It’s not that the solution choice is necessarily more important for a scientist working in NGS. I believe that choosing the right lab informatics platform is critically important no matter the application area, NGS or otherwise. The issue is that there is a higher probability of making the wrong choice for NGS because of the more involved protocols for gene-based medicine’s highly unique and nuanced requirements. A lot of scientists focused in cell and gene therapy find themselves with the wrong solution.

Supporting NGS-powered work in metagenomics, transcriptomics, epigenetics, whole genome sequencing you name it… brings data demands and workflow demands that the scientific ecosystem as a whole has never before seen. The reality is that most solutions get winded when dealing with that kind of data. They struggle when dealing with that kind of workflow complexity and data volumes.

Some scientists will go with a well-known solution in the LIMS or ELN scientific community. The problem is that this choice is often not made based on the requirements of the science and peculiarities of genomics pipelines; it needs to be made based on the scientists’ needs. Frequently, these solutions offer no NGS-specific functionality at all. As with many complex things, the devil is in the details, and this becomes apparent when you start implementing the workflows and data management requirements around NGS. Most solutions cannot deal with one or both of these.

Another option is to build your own NGS-specialized lab informatics solution. The problem is that homegrown solutions will never be a company’s core competency and will, therefore, never receive the kind of product development and innovation effort needed to keep pace with demands, particularly in a fast-moving area like gene-based medicine. Also, this holds you captive to the developers who made the system to maintain it. If they leave, you are in trouble.

Some labs find solutions that say they only do NGS. However, we are seeing such an incredible blending of specialties in science right now, which requires solutions with capabilities to track the entire pipeline – of which NGS is just one component. So going with such a system now means you must use multiple systems, get them to talk to each other, implement each one, train users on each one, etc. It just doesn’t make economic sense to go with point solutions anymore.

Well, if you go with a solution that is not already close to your needs, then it will require a lot of implementation work, and if the system is not a platform, then this will be costly and time-consuming. This slows down your payback period on the system and your important R&D work, or in the case of a clinical pipeline, your time to market for your test. But customization also equals system fragility. For many systems, when subsequent updates are made to a heavily customized system, the system will be vulnerable to breaks and downtime, representing even more time and money.

Homegrown solutions are even more expensive and time-consuming and have a shorter shelf life than those whose developer is 100% focused on keeping ahead.

And using multiple systems with different implementations, user experiences, and data representations will not be tenable soon—particularly as AI and machine learning become more central to scientific progress.

An out-of-the-box solution provides the best built-in capabilities and configurability to empower NGS cell and gene therapy companies to hit the ground running while tailoring the platform to their requirements over time—and doing so without code. Let me expand on that a bit. Our solution at Sapio delivers out-of-the-box NGS functionality.

That means our solution has pre-built templates that can be instantly configured, activated, and usable immediately. We find these templates, combined with our no-code Rules meet the vast majority of NGS requirements. But it couples these templates with radical levels of no-code configurability, empowering scientists to tightly align the platform’s workflows with their actual workflows. Add in highly scalable data management, powerful sample and material management capabilities, best-in-class search and data visualizations, and robust instrument integrations—and you have an out-of-the-box NGS solution.

Sapio also has the only truly unified science-aware LIMS and ELN with built-in large molecule tools such as plasmid design tools so you can track the entire cell and gene therapy pipeline with all the data in one system, uniformly represented, searchable, visualizable, and analyzable all in one place. The Sapio platform does this at scale so that you can track very high throughput workflows and resulting data without unusable slowness, etc. you would see with other systems.

Candidly, I hear excitement almost every single time. The truth is that many of these incredible scientists, these innovators, have never seen a platform that works the way they do, understands the science, and tracks the whole pipeline—and does so right from the start. Sapio’s built-in NGS capabilities are intended to fill a very specific gap that exists in the market today, and they do so very well. Whenever we provide an NGS demo, I am very confident that the value of the product will shine.