Empowering Clinical Genetics through
Privacy-First Innovation

Why We Built Biogistry

Clinical genetics software has traditionally been divided into two flawed paradigms: legacy desktop tools that lack modern web collaboration, or cloud platforms that require uploading sensitive patient genetic data to third-party servers.

Before Biogistry, clinicians and researchers had to stitch together multiple disconnected software packages. Creating pedigree charts, analyzing Punnett square crosses, mapping chromosome idiograms, drafting clinical reports, running risk calculation models, and sharing files required constant exporting, importing, copying data, and sending emails back and forth. Nothing was unified in a single seamless environment.

Furthermore, accessing advanced clinical genetics workbenches or risk calculation engines in legacy software often meant navigating lengthy sales calls, enduring month-long enterprise deployments, navigating complex IT onboarding, and spending weeks on software training. We eliminated all of that friction by delivering an instant, browser-native platform that works out of the box.

We engineered Biogistry to solve these challenges. Our mission is to unify standardized human pedigree drawing (NSGC and ACMG standards), Punnett square genotype probability analysis, ISCN 850-band chromosome idiogram mapping, and clinical report generation into a single high-performance workspace.

The Local-First Engineering Challenge

Choosing a local-first architecture was not the easy path. Managing complex calculations entirely client-side required significant engineering effort. Running heavy risk calculation models (including Gail BCRAT, Claus, PREMM5, and Bayesian peeling matrices) inside the browser required developing dedicated multi-threaded Web Workers and optimized memory structures.

Another key technical hurdle was supporting custom clinician scripting and institutional risk engines. We built a hardened, restricted MathJS evaluation sandbox operating inside Web Worker realms to execute basic-to-intermediate algebraic formulas and scope variables securely on device without exposing arbitrary code execution vectors.

What Drives Our Engineering

Engineered for Peak Performance

Biogistry is built on high-performance web standards to ensure rapid responsiveness and full offline functionality:

What We Envision in the Coming Years

As clinical genetics and genomic medicine evolve, our team is committed to advancing Biogistry along key strategic directions:

• Enhancing Risk Models & Custom Formulas: Expanding our custom formula authoring engine (building upon our current hardened MathJS sandbox that supports basic-to-intermediate algebraic expressions) to allow clinicians to define higher-order mathematical equations, multi-locus risk algorithms, and custom statistical functions directly inside Biogistry.
• Privacy-Preserving Local AI Assistance: Developing browser-native local AI models that assist clinicians in analyzing family trees, recognizing complex inheritance patterns, and supporting clinical decisions faster without ever transmitting or storing patient data on remote servers.
• Multi-Omics Family Tree Integration: Integrating somatic mutations (cancer genomics), epigenomics, transcriptomics, and metabolomics data layers directly into family tree nodes, pedigree relationships, and individual clinical profiles.
• Advanced Cytogenetic & Genomic Diagrams: Supporting specialized biological diagramming tools, including circular genome plots (circos maps), polygenic risk heatmaps, linkage disequilibrium graphs, and multi-locus haploblock diagrams.
• High-Throughput Probabilistic Simulations: Running real-time Monte Carlo simulations with thousands of probability permutations across complex pedigree graphs directly on client hardware.
• Zero-Knowledge Collaboration & EHR Sync: Advancing real-time co-editing capabilities for multi-disciplinary teams and strengthening FHIR and HL7 data connectors for seamless enterprise chart integration.