It’s time for translational science teams to upgrade from traditional bioinformatics platforms
In today’s translational science landscape, data is abundant, but insights are still hard-won. Teams are generating more multi-omics data than ever before, but stitching together results from fragmented capabilities, manual pipelines, and static reports often slows progress when speed and precision matter most.
If your translational team is still relying on traditional bioinformatics platforms, it's time to rethink your stack.
Pluto is changing the game by offering an end-to-end solution that not only handles data analysis but also accelerates collaboration, insight generation, and decision-making. Here’s why the future of translational discovery is full-stack, and why upgrading your platform could be the most important move you make this year.
From friction to flow: Why a full-stack approach matters
Think of your discovery pipeline as a stack—from infrastructure and data processing at the bottom to insight and decision-making at the top. When these layers are disconnected, handled by different platforms, teams, or workflows, the result is friction. That friction slows time to insight, increases the risk of error, and makes collaboration more difficult.
A full-stack platform like Pluto removes that friction by integrating the entire workflow. Here’s how it works, layer by layer:
Layer 1: Infrastructure – Built for scale, security, and speed
Translational science teams in pharma and biotech work in complex, regulated environments. Pluto is cloud-native, deployed securely in AWS and GCP, and built to meet the needs of enterprise teams. Whether you're managing protected health information or coordinating globally distributed teams, Pluto delivers compliance and performance out of the box.
Layer 2: Ingestion & processing – From raw data to rapid discovery
Too many teams lose time and clarity during the earliest stages of analysis, waiting on pipeline handoffs or navigating complex platforms just to get normalized data. Pluto simplifies this step with seamless ingestion pipelines that process FASTQ files into analysis-ready data, all within a single, intuitive environment.
No more manual pre-processing or juggling systems. The data flows—clean, organized, and ready for analysis.
Layer 3: Analysis – Multi-omics without the mess
Pluto brings together internal experimental data and public datasets like TCGA, CCLE, and GTEx for rich, comparative analysis. Whether you’re profiling a novel biomarker or benchmarking a candidate target, Pluto lets you ask complex questions across diverse datasets and get answers fast—without exporting to R, chasing spreadsheets, or jumping between tools.
Layer 4: Biological insight – More than just data
Data without context isn’t insight. Pluto helps teams curate, prioritize, and understand potential targets and biomarkers through a biological knowledge layer that captures metadata, links evidence, and ensures reproducibility.
The result: a clear, evidence-linked path to decision-making you can trust.
Layer 5: Decision collaboration – Where science becomes strategy
Most bioinformatics platforms stop at analysis. Pluto supports real-time, cross-functional collaboration among scientists, bioinformaticians, and project leaders.
With visual storytelling, an interactive canvas, and program-level organization, Pluto turns raw data into living narratives that evolve with a project—whether you’re reviewing findings or planning your next experiment.
Real-world use case: Oncology
Oncology in action: Accelerating biomarker discovery with Pluto
Imagine a translational oncology team working to identify predictive biomarkers for immunotherapy response in a new tumor subtype. They begin with RNA-seq data from preclinical models and early patient samples, comparing it to large-scale public datasets like TCGA to identify patterns, stratify responders, and prioritize biomarkers.
With Pluto:
- The team uploads raw FASTQ files and runs end-to-end pipelines instantly.
- Benchmarks gene expression patterns against TCGA cohorts using integrated analysis.
- Links candidate biomarkers to supporting evidence from public datasets and internal work.
- Collaborates in a shared workspace with visual storytelling for interpretation and review.
Impact: Within days, the team moves from raw data to an evidence-backed shortlist, aligned on next steps and ready for data-driven decisions.
From platforms to performance: A solution built for teams
Traditional bioinformatics platforms are built for individual analysts. Pluto is built for teams. In modern translational research, the breakthrough isn’t just in the data—it’s in how teams work together to interpret it.
Pluto removes silos, enabling faster, more reproducible, and more collaborative discovery.
The future of translational discovery is integrated
The complexity of modern drug discovery demands more than just better analysis—it demands better integration. Pluto delivers a unified, full-stack platform that takes you from raw omics data to confident therapeutic decisions faster and more collaboratively.
If you’re still stitching together platforms and workflows to answer mission-critical questions, maybe it’s time to upgrade your stack.
Ready to see Pluto in action?
Let’s talk about how we can support your next discovery program.