Key Takeaways
- Prioritize Experience: Choose labs with a proven track record in clinical trial study designs and regulatory compliance.
- Advanced Technology: Ensure the facility utilizes modern Next-Generation Sequencing (NGS) and has strong bioinformatics capabilities.
- Verify Accreditations: Only work with labs holding ISO 15189 or CLIA certifications to guarantee data validity.
- Data Security: Confirm strict adherence to GDPR and HIPAA standards to protect sensitive participant information.
Lab expertise and clinical trial experience
Expertise in genomic sequencing for clinical trials is not the same as general sequencing capability. Labs that perform high-throughput research sequencing may lack experience with the specific requirements of clinical study protocols, including chain-of-custody documentation, regulatory-grade reporting, and variant interpretation aligned with clinical endpoints.
When evaluating a lab, assess their experience with the specific assay type your study requires. A lab with deep expertise in targeted gene panels may not be the right fit for whole exome or whole genome sequencing, and vice versa. The complexity of bioinformatics pipelines, variant calling accuracy, and reporting standards varies significantly across these modalities.
Regulatory knowledge is equally important. In multi-country studies, labs must navigate differing requirements across jurisdictions. A lab that operates compliantly in one region may not meet the standards required in another. Understanding how a lab handles these regulatory variations is essential to maintaining data integrity and avoiding delays.
Sequencing technology and bioinformatics capabilities
The sequencing platform a lab uses has direct implications for data quality and study outcomes. Next-generation sequencing (NGS) encompasses a range of technologies, each with different strengths. Short-read platforms are well-suited for targeted panels and common variant detection, while long-read sequencing may be required for structural variants or complex genomic regions.
Beyond the instrument itself, evaluate the lab's capacity to handle your study's sample volume and complexity. Ask about library preparation methods, sequencing depth, and how the lab manages batch effects across large sample sets.
Bioinformatics capability deserves equal scrutiny. The accuracy of variant calling, annotation, and classification depends on validated analytical pipelines. Ask how the lab validates its bioinformatics workflows, how it handles ambiguous variants, and whether its pipelines are configured for clinical-grade reporting or research-only analysis. A lab with strong sequencing hardware but weak analytical infrastructure will produce data that is difficult to act on.
Quality control and accreditation
Accreditation provides a baseline assurance that a lab operates within recognized quality frameworks. For clinical trial sequencing, relevant certifications include ISO 15189 for medical laboratories and CLIA (Clinical Laboratory Improvement Amendments) for labs operating in or reporting to the United States. These certifications confirm that the lab follows standardized procedures for testing, reporting, and documentation.
Accreditation alone is not sufficient. Evaluate the lab's internal quality control processes, including how it tracks samples from receipt through reporting, how it detects and manages errors, and how it validates data before release. Ask whether the lab participates in external proficiency testing programs and whether it can demonstrate concordance with other certified laboratories. In a trial context, the credibility of sequencing data depends on the rigor of these processes.
Turnaround time
In precision medicine trials, sequencing turnaround time is not simply a lab performance metric. It directly affects how quickly patients can be confirmed as eligible and enrolled. When results are delayed, patients wait in uncertainty, sites lose momentum, and enrollment timelines extend.
Evaluate the lab's end-to-end turnaround: from sample receipt through sequencing, analysis, and result delivery. Understand how the lab manages capacity during peak periods and whether it can maintain consistent timelines as sample volumes increase over the course of a study.
It is also worth understanding where time is spent. In some cases, delays occur not during sequencing itself but during data analysis or quality review. Identifying these bottlenecks in advance allows teams to plan accordingly and set realistic expectations with sites and participants. The goal is not simply the fastest result, but a predictable and reliable timeline that supports the overall enrollment plan.
Data security and confidentiality
Genetic data carries heightened sensitivity. In many jurisdictions, it is subject to protections beyond those applied to standard health information. Selecting a lab requires understanding not only whether it complies with GDPR and HIPAA, but how it handles the specific obligations that apply to genetic information.
Assess the lab's data management practices in detail: how data is stored, encrypted, and access-controlled, and how long it is retained. Ask about the lab's policies for data de-identification and whether its systems support pseudonymization in compliance with study protocols.
For multi-country studies, cross-border data transfer introduces additional complexity. Understand how the lab moves data between jurisdictions, what transfer mechanisms it relies on (such as Standard Contractual Clauses under GDPR), and whether its infrastructure supports region-specific data residency requirements. These are not theoretical concerns. Regulatory exposure from mishandled genetic data can delay or compromise an entire program.
Conclusion
Lab selection is one of the earliest decisions in a precision medicine trial, and one of the most consequential. The lab you choose affects data quality, enrollment velocity, patient experience, and regulatory standing. Treating it as a standalone procurement step, rather than a strategic decision connected to the broader study design, introduces risk that compounds over time.
The criteria outlined here are not independent checkboxes. Expertise, technology, quality systems, turnaround reliability, and data security interact with each other and with the operational realities of your study. Evaluating them together, in the context of your specific protocol and geography, produces better outcomes than assessing each in isolation.
Sano works with GxP/CLIA-CAP-certified lab partners that have been vetted across these dimensions. Rather than leaving sponsors to manage lab relationships, logistics, and participant support independently, Sano coordinates genetic testing, counseling, sample collection, and result delivery within a single integrated workflow. This reduces the operational burden on sponsors and sites while maintaining the rigor that precision medicine trials require.
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