Infrastructure for reproducible life-science R&D
About Thoa
Thoa makes computational life-science research reproducible, shareable, and verifiable by default. Every job on Thoa automatically captures the full execution context: data, software, environment, and infrastructure, packaging it into a reusable, auditable artifact that can be re-run or shared across organizational boundaries. Researchers get instant compute without cloud or DevOps expertise. Institutions get governance-grade traceability and cost control.
Mission
Remove the barriers between data and discovery. Make it possible for any life-science team, regardless of cloud expertise or infrastructure budget, to run, reproduce, and share computational research at scale.
Vision
Every life-science result should be reproducible, shareable, and verifiable by default. Reproducibility is an infrastructure primitive, not a documentation exercise.
The Problem We Solve
In modern life-science, a result is rarely a single file. It is the output of a chain of computational steps: data retrieval, quality control, alignment, quantification, statistical modeling, and visualization, requiring the exact software versions, dependencies, environment, reference data, and compute configuration used at execution time.
In practice, most teams don't preserve this full context. When a reviewer asks to reproduce an analysis, when a new hire joins and the pipeline breaks, or when a collaborator needs to rerun your workflow. The typical path looks like this:
Chase missing details buried in methods sections or Slack threads
Locate and curate input datasets scattered across repositories
Infer software versions and dependencies that were never documented
Rebuild a compute environment (Conda, Docker, cluster modules) from scratch
Provision cloud accounts, IAM roles, buckets, and networking, or request HPC allocations
Iterate through bugs and incompatibilities for days or weeks
Package results for sharing via ad-hoc scripts and manual file transfers
The root cause is missing infrastructure for capturing and reusing full execution context. Approximately 78% of life-science computational results cannot be reproduced, and irreproducible preclinical R&D is estimated to cost $90 billion per year.
Why Existing Tools Fall Short
Most tools solve one layer well, but stop short of full-stack reproducibility. The missing piece is an infrastructure layer that makes reproducibility automatic and portable across organizational boundaries, with no extra effort on the part of the scientist.
| Category | What they solve | Why reproducibility still breaks |
|---|---|---|
| Workflow engines (Snakemake, Nextflow) | Define pipeline logic | Don't preserve infrastructure, data context, or long-term execution provenance |
| Data repositories (Zenodo, GEO) | Store datasets | Don't capture the compute environment or exact pipeline used to generate results |
| BYOC platforms (Seqera, LatchBio) | Run workflows in a cloud account | Require cloud expertise; limited portability across organizations; no built-in data-level reproducibility |
| Institutional HPC (Slurm) | Central compute resources | Hard to share; non-portable environments; limited traceability; long queue times |
What Thoa Does
Each run is executed in an isolated environment, with provenance captured at execution time. Thoa automatically records the pipeline run, software versions, environment configuration, machine characteristics, datasets used, and run parameters, turning results into auditable, reusable assets.
Speed
Reduce reproduction and validation overhead from weeks to minutes. No cluster queues, no cloud accounts, no DevOps. Provision high-memory VMs and run your workflow immediately.
Compliance
Provenance and audit trails designed into execution, not bolted on. Every job produces a traceable record aligned with 21 CFR Part 11, GDPR, and ISO-pathway requirements.
Cost
Zero-egress storage, compute cost guardrails, and multi-cloud optimization reduce cloud spend by 15–35% per customer. Pay only when you run; nothing idle.
Collaboration
Share complete, reproducible analyses via a single link, terabyte-scale datasets included. Collaborators can re-run your exact workflow without mirroring infrastructure.
Who We Serve
Our beachhead is pre-compliance life-science teams: those who feel the reproducibility gap most acutely and can adopt immediately. We expand into regulated pharma and biotech R&D as our compliance roadmap matures.
Genomics & Genetics Research Labs
Head of Bioinformatics · Computational Biologist · Lab Manager
Common pains
Analyses in genomics labs often take weeks to reproduce. Pipelines depend on undocumented environments, and when a team member leaves, institutional knowledge leaves with them. Sharing data with collaborators or satisfying a reviewer's reproducibility request means days of manual work. Thoa solves these pains by:
- Providing instant compute with no cloud account or DevOps knowledge required
- Automatically capturing code, environment, data, and parameters on every run
- Making sharing with collaborators and reviewers a single step
Biotech Startups (Pre-Compliance)
Head of Bioinformatics · CTO · Computational Biology Lead
Common pains
In early-stage biotechs, engineers spend more time managing cloud infrastructure than doing science. Pipeline fragmentation slows iteration, and compute costs are unpredictable, creating anxiety at every billing cycle. Thoa solves these pains by:
- Delivering faster time-to-analysis with lower cloud spend and no infra team needed
- Keeping scientists focused on science, not IAM roles and bucket policies
- Providing reproducibility that holds up under investor and partner scrutiny
CROs (Sequencing & Bioinformatics Services)
Head of Bioinformatics · Director of Operations · Technical Director
Common pains
CROs face constant pipeline firefighting across client projects, growing audit demands that require reproducible outputs, and compute cost pressure that erodes margins on TB-scale jobs. Standardization is hard when every client project is different. Thoa solves these pains by:
- Delivering client-isolated, reproducible pipelines with full audit trails as standard
- Eliminating egress cost surprises with zero-egress storage and predictable per-project billing
- Standardizing onboarding for new client projects without custom infrastructure work
Genomics Core Facilities
Core Facility Director · Head of Bioinformatics · Platform Manager
Common pains
Core facilities serve many researchers across many projects simultaneously, leading to pipeline inconsistencies, onboarding bottlenecks, and queue pressure. Sharing data in a way that meets peer-review expectations is slow and often requires custom scripts. Thoa solves these pains by:
- Enabling instant researcher onboarding without provisioning cluster accounts
- Standardizing workflows so every project runs reproducibly, regardless of who ran it
- Making publication-ready data sharing a built-in feature, not an afterthought
Bioinformatics Learning Programs
Professor · Course Director · Program Coordinator
Common pains
Bioinformatics courses routinely lose weeks of teaching time to student environment setup. Students break each other's configurations, results vary across the cohort due to environment drift, and compute budget management becomes a course-management overhead. Thoa solves these pains by:
- Giving every student a ready-to-run environment with one click, no cluster allocations needed
- Ensuring consistent, reproducible results across the entire cohort
- Providing centralized compute control and spend guardrails per course
Compliance Roadmap
Now (MVP)
- Isolated, ephemeral compute
- Full run provenance capture
- Audit-ready job history
- Role-based access control
Stage 1 (Q3 2026)
- Baseline security audit
- GDPR-aligned data processing agreements
- HIPAA & 21 CFR Part 11 gap analysis
- ISO certification pathway planning
Stage 2 (Q2 2027)
- ISO certification
- HIPAA + FDA 21 CFR Part 11 compliance
- On-prem / Swiss-hosted deployment
- Enterprise licensing for regulated environments
Explore Thoa
Jump straight into the platform or learn how Thoa works.