Case Study: How a Therapeutics Company Built an NGS Core Service That Scaled to Serve 60+ Scientists
Client | Clinical Stage Therapeutics Company |
Service | NGS core lab workflow optimization and Benchling/LIMS integrations |
Key Results |
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A clinical-stage therapeutics company was standing up a company-wide next-generation sequencing (NGS) core service, but were struggling to reliably track samples from intake through sequencing and into analysis. A small team of scientists handled requests from animal studies, cell-based studies, and other R&D work, and were constantly running into copy-paste errors, broken handoffs due to lack of standardization, and hard-to-query data from incorrectly configured relationships between intermediate samples. Working with Karchem, this company optimized the end-to-end workflow, introduced unique sample identifiers carried across the full analysis pipeline, and built automated, error-free sample sheets for a variety of sequencers including MiSeq, NextSeq, and NovaSeqs from data entered in Benchling. The result was more samples processed, standardized submissions from 60+ scientists across the organization, and reliable forecasting for runs, budget, and project timelines.
Introduction
Our client is a clinical-stage therapeutics company building an internal NGS core service to support research across the organization. Their core team of eight scientists prepares and submits samples for sequencing on behalf of internal groups, animal studies, cell-based studies, and discovery R&D, then routes results to a separate analysis team. Because sequencing touches nearly every research function, the core service needed to operate as reliable shared infrastructure, not a bottleneck.
Challenge
The new NGS core service had no reliable way to track a sample from intake to sequencing to analysis. Many tasks were manual, and a broken data setup in Benchling meant results couldn't always be traced back to the right sample.
Sample tracking was slow and manual
Copy-pasting caused repeated errors
Work was fragmented across teams and hand-offs
Benchling relationships were set up incorrectly, so sample lineage broke
Sample-level tracking limited scope and scalability
Solution / Approach
Karchem rebuilt the workflow from intake to analysis, fixing the data model first, then adding tracking, templates, metadata, and forecasting to enable scalable operations.
Fixed the Benchling data model so sample lineage held together
Added unique IDs that follow each sample through the whole pipeline
Built automated sample sheets to remove copy-paste errors for a variety of sequencers including MiSeq, NextSeq, and NovaSeqs
Filled in the missing steps in the process
Enabled data ingestion directly from instruments
Created reusable templates for every team
Added metrics to enable forecasting runs, resourcing, and timelines
Outcome
Our solution became a database infrastructure the whole company uses, with errors gone and capacity the team can actually plan around.
60+ scientists now submit through one standard process
Copy-paste and formatting errors eliminated
Fewer tasks to manage with plate-based tracking
Up to 7 instruments integrated in tracked workflows
Reliable forecasting for runs, resourcing, and budget
