We design and build the software and AI layer behind blood-based cancer detection — lab management, genomic pipelines, AI risk models, and physician dashboards, built by one team.
Most liquid biopsy teams have world-class assay science and a sequencer humming in the lab — but the software connecting blood draw to physician report is still spreadsheets, manual variant review, and scripts one bioinformatician maintains alone.
Manual sample tracking and hand-off between lab, bioinformatics, and reporting teams stretches a 3-day assay into a 2-week wait for the physician.
Sequencers, LIMS, barcode scanners, and reporting tools don't talk to each other, so results get copy-pasted between systems by hand — a real error risk.
The FDA's laboratory-developed test final rule is phasing in through 2028, and labs without audit-ready, validation-documented software are exposed.
Cancer-risk and tumor-origin models built as research notebooks rarely hold up as clinical-grade software with QC, versioning, and audit trails.
A confusing PDF with raw variant calls and no clear clinical context gets ignored — physicians need a dashboard that speaks their language.
Homegrown scripts that worked at 50 samples a month break at 500 — and hiring more bioinformaticians isn't a scalable fix.
A liquid biopsy platform is the software and AI layer, not the lab hardware. It's what helps laboratories and clinicians analyze a routine blood draw to detect cancer, monitor treatment response, or identify actionable mutations — without a surgical tissue biopsy.
We build that layer: the systems that track the sample, process the genomic data, run the AI models, and turn a sequencer's raw output into a report a physician can act on with confidence.
This is the process our platforms are built to run end-to-end — with our software owning steps 1 through 5 once the sample reaches the lab.
A standard blood draw from the patient — no surgery or needle biopsy required.
The lab isolates ctDNA, cfDNA, CTCs, RNA, or exosomes for analysis.
The sample is sequenced using next-generation sequencing (NGS) instruments.
Our software analyzes the genomic data for variants, mutations, and cancer signal.
The platform generates a clear, actionable report for the ordering physician.
Our data pipelines and AI models are designed around the analytes your assay actually produces — not a one-size-fits-all schema.
Circulating tumor DNA — the leading biomarker type, projected at ~42% of category revenue share in 2026.
Cell-free DNA — the fastest-growing biomarker segment in 2026, core to multi-cancer early detection panels.
Whole tumor cells shed into the bloodstream, useful for phenotypic and single-cell level analysis.
Expression-level signal that complements DNA-based variant calling with functional tumor activity data.
Tumor-derived vesicles carrying protein and nucleic acid cargo, an emerging early-detection signal source.
Epigenetic patterns in cfDNA increasingly used in multi-cancer early detection (MCED) screening models.
The market, the regulatory pathway, and clinical adoption are all moving at once — the platforms built now shape who leads the category.
The global liquid biopsy market is projected to grow at double-digit CAGR through the early 2030s across multiple analyst estimates.
ctDNA-based testing is projected to lead biomarker revenue share in 2026 as treatment-monitoring use cases expand.
Multi-cancer early detection panels are pulling cfDNA and methylation-based screening into mainstream clinical pilots.
The FDA's LDT final rule (phasing in through May 2028) is pushing labs toward validated, audit-ready software now.
Precision oncology and genomics remain a well-funded category for diagnostics startups building differentiated platforms.
Large hospital networks are actively evaluating liquid biopsy vendors for both screening and treatment-monitoring programs.
Pharmaceutical companies and CROs increasingly need liquid biopsy platforms to support trial biomarker stratification.
Cancer-risk and tumor-origin prediction models have matured enough to move from research papers into deployable software.
Building diagnostics software means understanding variant calling and physician workflows just as well as system architecture — that's the team we bring.
Our bioinformatics engineers understand NGS pipelines, variant calling, and VAF thresholds — not just generic backend architecture.
We build with validation, audit trails, and electronic-record controls in mind from day one, not bolted on before a lab inspection.
We take cancer-risk and tumor-origin models from research notebooks to versioned, monitored, clinical-grade production services.
We've integrated Illumina and Ion Torrent instruments, LIMS platforms, and EHR systems into unified data pipelines.
Clinical dashboards designed with practicing oncologists in mind — clear cancer probability, mutations, and next steps, not raw data dumps.
We've taken diagnostics platforms from first pilot cohort through thousands of samples a month without a rebuild.
Talk to our team about your biomarker panel, sample volume, and regulatory pathway.
The liquid biopsy software market is early enough that platform decisions made now shape who leads the category over the next decade.
Sources: market sizing and CAGR estimates aggregated from published 2025-2026 liquid biopsy market research reports; biomarker share figures reflect 2026 category analyst projections.
From lab management through AI models to physician reporting — mapped to the five components a liquid biopsy platform actually needs.
Sample tracking, barcode scanning, chain-of-custody logging, and lab workflow automation from accession to result.
Full sample traceability with tamper-evident audit logs, ready for CLIA/CAP inspection.
Bioinformatics pipelines that ingest raw sequencer output and produce quality-controlled, analysis-ready data.
DNA sequence analysis, variant calling, and mutation detection tuned to your biomarker panel and VAF thresholds.
Automated quality-control checkpoints throughout the pipeline to flag low-quality samples before they reach a physician.
Machine learning models trained to predict cancer risk and probability from genomic and clinical signal.
Models that predict likely tumor origin from ctDNA signal, an increasingly requested feature for MCED platforms.
Software to support your research team's biomarker discovery work alongside the production clinical pipeline.
Screening-focused models tuned for high specificity, built for multi-cancer early detection use cases.
Physician-facing dashboards showing detected mutations, cancer probability, biomarkers, and patient history.
Track a patient's biomarker trends across multiple draws to monitor treatment response over time.
Clear, clinically actionable PDF reports and physician summaries generated automatically from platform data.
HL7/FHIR-based integration so results flow directly into the physician's existing EHR and the lab's LIS.
Guidance on building CLIA/CAP-validation-ready and FDA LDT-aware software architecture from the start.
Ongoing support, model performance monitoring, and drift detection after your platform goes live.
The same platform, three purpose-built experiences — for the lab, the physician, and the compliance team.
These are the teams that typically need custom software around their laboratory and AI workflows.
A structured process built around how diagnostics software actually gets validated and shipped.
We map your biomarker panel, sample volume, and target regulatory pathway.
We design a HIPAA-aware, CLIA/CAP-ready system architecture before writing code.
Lab management, data pipeline, dashboard, and reporting built in transparent sprints.
Cancer-risk and tumor-origin models built, trained, and validated against your data.
Sequencer, LIMS, and EHR integrations tested end-to-end with real sample workflows.
Go-live support plus continuous model monitoring and platform maintenance.
We build the AI layer as production software — versioned, monitored, and validated against held-out data — and connect it to the instruments and systems your lab and physicians already use.
A validation-minded process built for regulated diagnostics software, not a generic app-dev checklist.
Biomarker panel, sample volume, regulatory target, and stakeholder workflows mapped.
HIPAA-aware, CLIA/CAP-ready architecture and data model design.
Sample tracking, barcode scanning, and chain-of-custody workflow development.
Variant calling, mutation detection, and QC automation development.
Cancer-risk and tumor-origin models trained, tested, and validated.
Clinical dashboard, PDF reporting, and EHR/LIS integration built and tested.
Validation documentation, go-live support, and ongoing model monitoring.
We adapt this stack to your existing lab systems — nothing here is a forced migration.
Liquid biopsy software fails quietly if it's built by a team that hasn't shipped regulated genomics platforms before.
Diagnostics software carries real regulatory weight — we build with validation and audit-readiness as first-class requirements, not an afterthought.
Architecture built to support CLIA-certified laboratory operations and their validation requirements.
Documentation and audit-trail practices designed to align with CAP accreditation expectations.
We build with the FDA's laboratory-developed test final rule (phasing in through May 2028) in mind for tests moving toward device-level oversight.
Electronic records and signature practices modeled on 21 CFR Part 11 expectations for regulated data.
Encryption at rest and in transit, minimum-necessary access, and BAAs across every vendor in the stack.
Every sample, variant call, and report action logged and traceable for inspection readiness.
Validation documentation practices informed by BLOODPAC's published, FDA-reviewed liquid biopsy protocols.
Data residency and consent controls available for labs and trials operating outside the US.
We are a software development partner, not a regulatory law firm or CRO — we build the technical controls and documentation scaffolding your compliance and lab-director team needs, and always recommend pairing us with qualified regulatory counsel.
We help you architect the platform around the commercial model you're actually pursuing.
License the platform to molecular diagnostic labs running their own validated assays.
Deploy across hospital networks as an enterprise platform for screening and monitoring programs.
Support clinical trial biomarker stratification with data and platform access agreements.
Offer the platform white-labeled to diagnostics companies who want to launch under their own brand.
Representative engagements across diagnostics labs and precision medicine companies building liquid biopsy software.
Built a CLIA-lab-ready sample management and reporting platform from zero to first patient cohort in under 6 months.
Automated a manual variant-review workflow into a QC-gated bioinformatics pipeline, cutting result turnaround significantly.
Replaced a raw-data PDF report with a physician-facing dashboard showing mutations, probability, and trends over time.
"Idea Usher understood variant calling and VAF thresholds from the first call — we didn't have to educate them on genomics before we could talk about software."
"Our lab director signed off on the audit trail and validation documentation without a single follow-up question. That doesn't happen with generic dev shops."
"Physicians actually open our reports now. The dashboard turned a wall of variant data into something an oncologist can act on in two minutes."
Tell us about your biomarker panel, sample volume, and regulatory pathway — we'll map what an MVP and full platform would look like.
A liquid biopsy platform is the software layer, not the lab hardware. It typically includes five parts: lab management (sample tracking, barcode scanning, chain of custody), genomic data processing (variant calling, mutation detection, QC), AI models (cancer risk and tumor-origin prediction, early detection), a clinical dashboard (mutations, biomarkers, longitudinal trends), and physician reporting (PDF reports, EHR integration, clinical recommendations).
A focused MVP covering sample tracking, a bioinformatics pipeline, and a physician report typically takes 4-6 months. A full platform with AI risk models, a clinical dashboard, EHR/LIS integrations, and CLIA/CAP-aligned validation documentation usually takes 9-14 months, depending on how many biomarker types and how many AI models are in scope.
We build the software platform — lab management, bioinformatics pipelines, AI models, dashboards, and reporting. We integrate with your sequencers, LIMS, and wet-lab assay rather than developing the assay itself, and we work alongside your lab and regulatory teams on CLIA/CAP validation documentation.
Yes. We've built integrations with Illumina and Ion Torrent sequencing instruments, common LIMS/LIS systems, and EHR platforms over HL7/FHIR. We map your existing lab workflow into the platform rather than asking you to change instruments.
We build audit trails, electronic records controls aligned with 21 CFR Part 11 practices, and validation-ready documentation from day one, and we work with your regulatory and lab-director team as tests move through CLIA/CAP validation or, where applicable, the FDA's laboratory-developed test pathway. We are a software development partner, not a regulatory law firm or CRO, and always recommend pairing us with your compliance counsel.
Most engagements range from $90,000 for a focused MVP to $450,000+ for a full platform with multiple AI models, a physician-facing dashboard, and deep LIMS/EHR integrations. We scope a fixed range after a discovery call once we understand your biomarker types, sample volume, and target regulatory pathway.
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