From Pipeline Maintenance to Scientific Insight
Learn how cloud-native bioinformatics pipelines improve reproducibility, control costs and scale multi-omic analysis securely - so your team spends less time managing infrastructure and more time on science.
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Five Challenges This Webinar Addresses
Kai and Gerard structure the entire session around five problems teams encounter when running omics pipelines in real biotech and pharma environments.
Ease of Use
Complex workflows require specialist knowledge across multiple tools, languages and formats - creating barriers for non-coding users and clinical teams.
Reproducibility
Without standardised workflows, version tracking and parameter capture, results can be inconsistent - with real consequences for regulatory submissions and published science.
Cost
Infrastructure setup, mid-run failures and inefficient cloud configuration make pipeline execution far more expensive than it needs to be.
Scalability
Large multi-omic datasets quickly exceed local compute capacity. Scaling to hundreds of samples requires cloud infrastructure designed for it from the ground up.
Security
Open-source pipelines are typically built by academics. Without additional controls, running them on patient data in pharma or biotech environments carries real compliance risk.
Real Numbers From a Real Run
Demonstrated live in the session: a 660-sample RNA-seq analysis run end-to-end on Sonrai Pipelines. These are the actual figures from that execution, presented by Kai during the webinar.
660
Samples processed in a single run
~640GB compressed / ~2TB uncompressed input
20,500
Tasks executed automatically
~7,600 tasks/hour - one every half second
2h 40m
End-to-end execution time
~4 samples processed per minute
7.4TB
Output generated from a single run
Automatic cleanup keeps storage lean and cost-effective
Questions This Webinar Helps Answer
The session covers practical answers to the questions bioinformatics and engineering teams face when running production omics pipelines.
How Do I Make Pipeline Results Reproducible Across Projects?
Learn how Docker containers, parameter capture, validated sample sheets and version-controlled workflows ensure consistent, auditable results - and how AI-assisted log summaries make debugging accessible without deep technical expertise.
How Do I Reduce Failed Runs and Debugging Time?
See how pre-run validation catches errors before compute starts - including a live demonstration of sample sheet validation catching a formatting error before the pipeline is submitted.
Should I Build, Outsource or Use a Platform?
Gerard walks through the practical trade-offs of each approach - covering setup cost, security requirements, ongoing maintenance and the point at which running your own pipelines becomes significantly more cost-effective than outsourcing.
How Do I Run Open-Source Workflows Securely?
Understand the specific compliance risks in NF-core pipelines and how production-ready controls - container scanning, private repositories, firewalling and data residency enforcement - address them.
What You'll Learn
Ease of Use and Reproducibility
Kai introduces the core challenges of bioinformatics pipelines then demonstrates Sonrai Pipelines live - including RNA-seq setup, sample sheet validation, error handling, quality control reporting and downstream analysis options including no-code and notebook environments.
Cost, Scalability and Security
Gerard covers the practical cost of cloud pipeline execution, the 660-sample benchmark, a build vs outsource vs platform comparison, and a detailed walkthrough of security risks in open-source NF-core pipelines - including live examples of container vulnerabilities.
Live Q&A
Kai, Gerard and Hamzah answer questions on proteomics and mass spec support, batch effect handling, build vs platform decisions and how Sonrai Discovery serves teams across discovery, R&D and clinical stages.
Secure Pipelines for Pharma and Biotech
Open-source bioinformatics workflows are typically built by academics rather than security engineers. Deploying them on patient data without additional controls can create serious compliance exposure.
NF-Core Container Vulnerabilities
Many NF-core Docker containers contain unpatched critical vulnerabilities. Some - including the widely used QuantMS proteomics pipeline - send data to third parties by default, which can constitute a data breach when run on patient data.
Sonrai's Controls
All pipelines are pulled into a private repository, vulnerability-scanned, sanitised and firewalled. Data residency controls ensure patient data never leaves the designated region - an important requirement for EU clinical data under GDPR.
Regulatory Alignment
Sonrai's infrastructure is designed to meet ISO 27001, GDPR and HIPAA requirements. The EU Cyber Resilience Act - which comes into full effect in December 2027 - will extend these obligations to software suppliers across the supply chain.
Build, Outsource or Platform?
Example figures discussed by Gerard during the session. Actual costs will vary by dataset size and configuration.
Outsource to CRO
~$105 per sample
Weeks turnaround. No direct data control. Limited iteration. Best suited to one-off requirements.
Sonrai Pipelines - example run cost
~$1.60 per sample
Hours turnaround. Full data control. Run iteratively with different parameters as needed.
DIY cloud build
Variable - often higher than expected
Requires cloud and security engineering. A $10 run done wrong can cost $2,000. Ongoing maintenance overhead is significant.
Built for Bioinformatics and Engineering Teams
Particularly relevant if your team is running or planning to run omics pipelines at scale - or evaluating platform options for multi-omic analysis.
Bioinformatics and Platform Leads
Building and maintaining omics pipelines who want better reproducibility, pre-run validation, easier debugging and no-code tools that don't sacrifice technical flexibility.
Translational Scientists
Wanting faster access to processed, reproducible multi-omic data without depending on bioinformatics queue times or manual pipeline management.
Data Science and Bioinformatics Leads
Evaluating cloud infrastructure and platform options for scaling omics analysis - including cost modelling, security compliance and cross-team accessibility.
IT, Engineering and Quality Managers
Responsible for security, compliance and supplier assessment in pharma and biotech environments where patient data handling and regulatory requirements apply.
Meet the Speakers
Bioinformatics, engineering and strategic perspectives from Sonrai's technical team.
Kai Lawson-McDowall
Senior Bioinformatician, Sonrai Analytics
Kai specialises in multi-omic pipeline development and automation on Sonrai Discovery. He leads the live RNA-seq demonstration in this session and co-authored a published case study on reducing research timelines by 70% using cloud-native pipeline infrastructure.
LinkedIn ↗
Gerard Loughran
Head of Engineering, Sonrai Analytics
Gerard leads Sonrai's cloud infrastructure and engineering team. He covers cost, scalability and security in this session - including the 660-sample benchmark, a real-world cost comparison and a practical walkthrough of NF-core pipeline security risks.
LinkedIn ↗
Dr Hamzah Syed
Director of Bioinformatic Solutions, Sonrai Analytics
Hamzah hosts the session and connects the technical content to practical outcomes for research and clinical teams. With a background spanning bioinformatics and customer success, he translates platform capabilities into programme-level impact.
LinkedIn ↗Access the Full Session
Watch Kai's live demonstration of Sonrai Pipelines, Gerard's cost and security walkthrough, and the full Q&A - including the 660-sample RNA-seq benchmark and a practical guide to running NF-core pipelines securely.
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