Skip to content
Skip to content

NextGenAMR — a product by Vanguard Biotech Systems

Research & surveillance

VBS develops controlled bioinformatics infrastructure to organise whole-genome-sequencing workflows within its published scope, preserve provenance, structure AMR-related evidence and produce reviewable results. For research and surveillance, the value is reproducibility, consistency between runs, traceability, versioning, comparison and structured reporting.

Being validated

NextGenAMR is a functional platform in controlled preview. Validation is ongoing, and the product is not presented as an autonomous diagnostic or treatment-decision system.

Current status

NextGenAMR is in controlled preview and validation; its scope is versioned and limited. It is not presented as an autonomous diagnosis or treatment-decision system. A research or surveillance collaboration is not a clinical licence or an authorisation for care use.

Within a published scope

NextGenAMR interprets antimicrobial resistance from whole-genome sequencing of bacterial isolates. In the current operational scope, the supported species is Escherichia coli, with a closed panel of 9 antibiotics (Amoxicillin–clavulanic acid, Ampicillin, Ciprofloxacin, Ceftazidime, Gentamicin, Meropenem, Nitrofurantoin, Piperacillin–tazobactam and Trimethoprim–sulfamethoxazole), each backed by a 6-model ensemble. The output is a calibrated resistance probability, never a categorical S/I/R result. It is in internal, non-clinical validation; it is not a diagnosis and not a regulatory-cleared medical device.

Why reproducible, controlled execution helps

Research and surveillance workflows often face avoidable sources of divergence. NextGenAMR can help study and organise these within its real scope — it does not claim existing tools or practices are inadequate.

  • Divergence between component and database versions
  • Manual handoffs between steps
  • Heterogeneous, hard-to-compare outputs
  • Difficulty reconstructing exactly how a run was produced
  • Inconsistent reporting between analyses

Capabilities for research & surveillance

Each capability is labelled by its real state — implemented, available to evaluate, agreement-dependent or planned. Nothing here is presented as more mature than it is.

  • Run provenanceImplemented

    Each analysis records the context needed to understand and reconstruct how it was produced.

  • Component & database versioningImplemented

    Component and reference-database versions are recorded, so runs are comparable and reconstructable.

  • Parameter recordsImplemented

    The parameters of a run are captured as part of its record.

  • Warnings & abstentionImplemented

    The system surfaces warnings and can abstain rather than force a result — abstentions are never hidden.

  • Structured outputsImplemented

    Results are produced as structured, machine-readable outputs (JSON) alongside human-readable reports.

  • Scope controlImplemented

    Analysis is bounded to a versioned, published scope; the system does not answer outside it.

  • Calibrated probability outputImplemented

    Within scope the system reports a calibrated probability, never a categorical S/I/R interpretation.

  • Comparison between runsAvailable to evaluate

    Comparing runs and configurations is something a collaboration can explore against real data.

  • Reporting structureAvailable to evaluate

    Defining a reporting template for a research or surveillance workflow is something to shape together.

  • Systems & platform integrationAgreement-dependent

    Integration with sequencing platforms, storage, APIs or LIMS is assessed and agreed per project.

Ways to collaborate

Possibilities subject to an evaluation of fit, scope, data, resources, approvals and agreement.

What VBS can bring

What VBS can bring

  • The NextGenAMR platform within its published scope
  • Workflow architecture, normalisation and orchestration
  • Scope control and aggregation of evidence
  • Provenance, versioning and abstention handling
  • Structured outputs, reporting and interfaces
  • Technical expertise and the ability to define controlled evaluations

What a collaborator normally brings

Depending on the project — not universal requirements.

  • A defined research or project question
  • Scientific and technical leads
  • Legitimately accessible data, with provenance and quality information
  • A reference standard when applicable
  • Ethical or institutional approvals and transfer agreements
  • Success criteria and the ability to review results

Possible outcomes

Deliverable-shaped possibilities — not promised results, publications, metrics or deployments.

  • A defined protocol
  • A feasibility assessment
  • A dataset characterisation
  • A reproducible analysis
  • A provenance package
  • A comparison of runs
  • An integration feasibility assessment
  • A reporting template
  • A methodological result
  • A technical contribution to a consortium
  • A defined next phase

Start the conversation

Identify a collaboration modality and tell us about your project. No sensitive data is requested.