Biomedical evidence and product strategy

Scientific products depend on evidence, usability, documentation, and trust.

In life-science products, scientific quality depends on more than the method. It depends on the data model, interface, documentation, claims, regulatory posture, identifiers, provenance, and the parts of the system most users never see. My work connects scientific software, biomedical evidence systems, precision medicine infrastructure, and product-facing research.

What this work resolves

Taste as technical judgement

Scientific products need the same care inside the system as on the visible surface. Data models, routes, identifiers, documentation, defaults, and edge cases all shape trust.

Evidence into product

Methods become useful when users can reach a defensible interpretation without assembling evidence manually across fragmented tools, papers, databases, and local scripts.

Trust before claims

Users infer scientific quality from behaviour: stable pages, clear definitions, fast loading, consistent filters, visible provenance, accessible design, and disciplined language.

Commercial viability

Naming, ownership, domains, documentation, support, licensing, and lifecycle maintenance affect whether a useful scientific product can survive beyond the first release.

Evidence at a glance

Bench to system experience from molecular biology and disease discovery to software, documentation, regulation, and adoption
Public technologies scientific software and data products spanning genomic evidence, reporting, visualisation, and infrastructure
30+ stakeholders engaged across biotech, healthcare, academia, public-sector genomics, and clinical research
Product chain naming, UX, data architecture, documentation, IP, regulatory posture, distribution, and lifecycle maintenance

Portfolio samples

Product strategy and design systems

Product judgement

Product positioning, user needs, workflow design, feature discipline, adoption logic, product taxonomy, documentation, stakeholder alignment, and release communication.

Scientific UX

Search-first workflows, result ranking, filter logic, linked molecular context, structure viewing, table behaviour, state preservation, accessibility, and inspectable evidence.

Evidence architecture

Data provenance, field definitions, score meaning, versioned sources, stable identifiers, linked records, uncertainty, claim structure, and reproducible interpretation.

Technical architecture

Next.js, React, TypeScript, Tailwind, R, Python, SQL, PostgreSQL, APIs, server routes, modular components, secure access, caching, logging, and scalable data systems.

Trust and governance

IP review, trademark logic, domain strategy, ownership checks, documentation discipline, regulated claims, auditability, quality language, and lifecycle maintenance.

Growth and distribution

Search structure, indexable pages, documentation hubs, backlinks, technical content, scientific publishing, LinkedIn distribution, usage signals, and institutional credibility.

Selected product examples

  • Switzerland Omics: scientific product identity, technical writing, regulatory positioning, and product architecture for probabilistic genomics and biomedical evidence systems.

  • Genomic Vault: secure genomic custody and controlled access concept for long-term biomedical data use.

  • Archipelago: Manhattan plots are for GWAS. Archipelago plots are for complex variant association studies, published in Lawless et al (2026). CRAN version CRAN downloads

  • QuantBayes: standardises how evidence strength is expressed - quantifying genomic variant evidence sufficiency with Bayesian posterior intervals, preprinted in Quant Group et al (2025) CRAN version. CRAN downloads Zenodo DOI

  • PanelAppRex AI: harmonised disease-gene panels from structured clinical and genetic queries, preprinted in Quant Group et al (2025). GitHub stars Dataset DOI

  • VCFheader: parsing VCF headers and generating structured standalone HTML reports, described in Lawless (2026). CRAN version CRAN downloads

Selected publications

ORCID record: ORCID iD 0000-0001-8496-3725

Application of qualifying variants for genomic analysis. Bioinformatics, 42(2), btaf676, 2026.

Relevant product work

Switzerland Omics · product system

Scientific brand, product architecture, and evidence design

Built a complete scientific product environment for probabilistic genomics, including public positioning, visual language, product taxonomy, regulatory framing, technical writing, and user-facing evidence concepts.

Switzerlandomics.ch, Quant DB, Quant Scan, Quant Calc, Genomic Vault, evidence frameworks, regulatory positioning, product pages, scientific documentation, and market-facing technical communication.

Variant Impact · product design book

Protein variant interpretation as a complete product system

Designed the product logic for a web system that connects missense variant prediction, protein structure, functional annotation, and molecular context into one navigable interpretation workflow.

Naming, positioning, canonical domain strategy, UX, search logic, route structure, data model, UniProt, gnomAD, AlphaFold, ClinVar, MANE, documentation, security, cost control, IP, regulation, SEO, and commercial model.

Scientific software · public tools

Methods translated into usable scientific products

Developed software and data products that give statistical and biomedical methods a clear visual, conceptual, and operational form.

Archipelago, QuantBayes, VCFheader, PanelAppRex AI, Qualifying variant database, IEI genetics database, CRAN releases, structured HTML reports, YAML criteria, and publication-linked software.

Institutional identity · trust and adoption

Public-facing biomedical systems with institutional credibility

Built or shaped public identities for scientific and clinical initiatives where clarity, restraint, governance, and trust matter more than novelty.

SwissPedHealth, Swiss Genomics Association, Switzerland Omics, collaborator-facing communication, clinical research positioning, biomedical infrastructure messaging, and high-trust public presentation.

Working fit

Biomedical product teams need scientific systems that are credible, usable, documented, and reviewable. The useful output is a product where the science, data model, interface, documentation, claims, regulation, and adoption path form one coherent system.