Williwaw Biosciences

A New Paradigm in Genetic Analysis

We haven't just improved existing methods, we've moved beyond the GWAS paradigm entirely. While the field debates common versus rare variants, we've discovered that the most valuable information is hidden in what everyone discards.

Proprietary Technology, Proven Results

Our patent-pending computational platform extracts molecular-based subtypes from data that traditional approaches systematically discard, enabling precision medicine for any complex disease, from existing datasets, at scale.

Different Biology, Different Treatment

Most complex diseases are not the same at the molecular level. What looks like one condition is actually several distinct subtypes, each requiring different approaches to treatment.

🧬 Our Proprietary Approach

Standard genetic analysis focuses on variants that pass strict quality control filters and discard genomic signals containing critical biological information. SNP array probe intensity anomalies are filtered out as technical artifacts. Copy number gains are dismissed as noise. Non-Mendelian inheritance patterns are excluded as errors.

Our breakthrough is recognizing that these "artifacts" actually harbor rich subtype-defining information. Our patent-pending methods extract rare variant signals and structural variations from widely available SNP arrays and achieve what is often missed by next-generation sequencing. By integrating family-based inheritance patterns with advanced pathway analysis, we reveal molecular subtypes invisible to both GWAS and traditional rare variant approaches.

How Our Platform Works

1

Family-Based Data

Analyze trio and family genomic data to capture inheritance patterns that standard case-only analyses miss

2

Signal Extraction

Apply proprietary algorithms to extract subtype-defining signals from genomic patterns typically filtered out as noise

3

Pathway Integration

Map extracted signals to biological pathways and molecular mechanisms using systems-level analysis

4

Subtype Discovery

Identify molecularly distinct subtypes with high statistical confidence and clinical relevance

Scientific Innovation

Transforming how we understand complex disease genetics

Patent
Pending Technology
Family
Trio-Based Analysis
Novel
Signal Extraction
Any
Disease or Trait

Why Our Approach Is Different

We've fundamentally rethought how to extract biological meaning from genetic data.

❌ Traditional Approaches

  • GWAS: common variants of small effect
  • Rare variant detection requires expensive NGS
  • Single-sample analysis misses inheritance patterns
  • Standard QC filters discard probe anomalies
  • Copy number gains treated as technical artifacts

✓ Williwaw Platform

  • Detects rare variants from accessible SNP arrays
  • Leverages family-based genomic patterns
  • Extracts signal from probe anomalies
  • Copy number gains reveal structural variants
  • Reveals subtypes invisible to GWAS

Unlocking Existing Data

Large-scale genetic databases already contain the subtyping information we need but it's been systematically filtered out by conventional pipelines. We don't need new data; we extract previously invisible biological signals from existing datasets.

100k+
Family trios in public databases
50+
Conditions with available data
1M+
Samples across biobanks

Proof of Concept: Autism Spectrum Disorder

We chose autism as our first application because it represents one of the most challenging conditions in medicine: highly heritable yet extremely heterogeneous, with no reliable biomarkers and limited treatment options. If our platform works for autism, it will work for anything.

Why Autism Is the Ultimate Test Case

Autism spectrum disorder encompasses the full complexity of human genetic architecture:

  • Extreme heterogeneity: Thousands of genes contribute to risk, with no single dominant cause
  • Polygenic and monogenic mechanisms: Both common variants and rare de novo mutations play roles
  • Variable expressivity: The same genetic changes produce vastly different clinical outcomes
  • Environmental interactions: Genetic factors interact with prenatal and postnatal environments
  • Diagnostic challenges: Purely behavioral diagnosis with no molecular biomarkers

Successfully stratifying autism demonstrates that our approach can handle the most complex genetic architectures in human disease.

Autism Analysis Results

Our platform identified 6 distinct molecular subtypes across 1,811 individuals

1,811
Individuals Analyzed
6
Distinct Subtypes
10⁻⁴⁰
Statistical Significance
8
Biological Pathways
Six biologically distinct autism subtypes

AI-powered molecular analysis reveals six biologically distinct autism subtypes with different underlying mechanisms

Autism Molecular Subtypes

Each subtype has distinct biological mechanisms, clinical characteristics, and therapeutic implications.

n=494 (27%)

High Genetic Burden

Key Features:

  • Polygenic architecture with highest variant load
  • Disruption across multiple biological pathways
  • No single dominant mechanism
  • Multiple biological pathways affected simultaneously
  • Includes more Simplex than Multiplex autism types

Therapeutic Implications: Requires comprehensive, multi-system approach rather than single-pathway intervention

n=267 (15%)

Glutamate Dysfunction

Key Features:

  • Variants in glutamatergic signaling genes
  • Excitatory/inhibitory imbalance
  • Affected neurotransmission pathways
  • Sensory sensitivities
  • Seizure susceptibility

Therapeutic Implications: Harbors variants in glutamate receptors and ion channels with FDA-approved therapies for other conditions, making this subtype an immediate repurposing candidate

n=267 (15%)

Synaptic & Immune Regulation

Key Features:

  • Disruption of synaptic organization genes
  • Affected neuronal connectivity
  • Abnormal synapse formation and pruning
  • Disruption of the complement system

Therapeutic Implications: FDA-approved drug targets include cholesterol receptors, GABA-B receptors, and neurotrophin pathways. Pharmacogenetic considerations for medication dosing. Anti-inflammatory strategies may be particularly relevant

n=251 (14%)

Cholesterol & Steroid Metabolism

Key Features:

  • Diverse molecular mechanisms
  • Dominated by steroid synthesis in the brain
  • Multiple pathway involvement
  • May represent multiple rare subtypes

Therapeutic Implications: Potentially responsive to cholesterol-modulating drugs

n=273 (15%)

Cytoskeletal Organization & Neurodevelopment

Key Features:

  • Microtubule dysfunction
  • Affected neuronal migration and morphology
  • Axon guidance pathway genes
  • Motor coordination difficulties
  • Developmental delays

Therapeutic Implications: Early motor interventions; occupational and physical therapy focused on motor development

n=259 (14%)

Presynaptic Function

Key Features:

  • Serotonin receptor dysfunction
  • Presynaptic scaffolding disruption
  • Dendritic spine regulation
  • Limbic system involvement
  • Mood/anxiety vulnerabilities
  • Sleep disturbances possibles

Therapeutic Implications: Strong candidate for SSRI response. May respond to dietary tryptophan modulation.

Biological Pathways Identified in Autism

Our analysis identified 8 major biological pathways disrupted across the autism subtypes—demonstrating the platform's ability to map genetic variants to functional mechanisms.

Synaptic Function

Neurotransmission, vesicle recycling, and synaptic plasticity mechanisms

Ion Channel Activity

Excitability regulation, E/I balance, and action potential generation

Cell Adhesion

Cell-cell contacts, dendritic spine formation, and synapse stability

Cytoskeletal Structure

Microtubule organization, axon guidance, and neuronal polarity

Vesicle Trafficking

Intracellular transport, endosomal sorting, and membrane dynamics

Immune/Complement

Synaptic pruning, maternal immune activation, and inflammatory responses

Epigenetic Regulation

DNA methylation, RNA modification, and chromatin remodeling

RNA Processing

mRNA degradation, translation control, and post-transcriptional regulation

Rare Disease Applications

Our platform identifies molecular subtypes in any genetically complex condition—including diseases traditionally considered "simple" Mendelian disorders. Even single-gene diseases show unexpected molecular diversity.

Redefining "Simple" Genetic Diseases

Hereditary hemochromatosis and Niemann-Pick disease are classified as single-gene disorders, yet clinical presentation varies dramatically. Our analysis reveals why: molecular subtypes driven by modifier genes and regulatory variants that standard approaches miss.

Fe

Hereditary Hemochromatosis

Iron Overload Disorder

The Clinical Mystery

Patients with identical HFE C282Y/C282Y genotypes show 100-fold variation in outcomes:

  • Some develop severe cirrhosis by age 40
  • Others remain asymptomatic for life
  • Penetrance of HFE mutations: only ~1%
  • No clinical factors explain this variation
Hemochromatosis Missing Heritability

🔬 What We Discovered

Complete Missing Heritability Explained in this Family

HFE (C282Y, H63D) — Common variants

Traditional genetic testing identifies these, but they don't predict severity

MTF1 — Rare SNP, MAF=0.04 in Europeans

Metal transcription factor that regulates HAMP in response to zinc

SLC39A12 — Rare SNP, MAF=0.01 in Europeans

Zinc transporter; cryptic deletion detected only via NMI

Epistasis — All 4 mutations required

Iron + zinc dysregulation → severe phenotype

🧬 Novel Biology

Iron-Zinc Pathway Interaction

  • Both HFE (iron sensor) and MTF1 (zinc sensor) regulate HAMP expression
  • Zinc transporter disruption (SLC39A12) compounds the problem
  • First demonstration of iron-zinc epistasis in hemochromatosis
  • Both NMI loci are eQTLs regulating gene expression

💊 Clinical Impact

  • Risk Stratification: Identify which C282Y homozygotes need aggressive phlebotomy vs. monitoring
  • Personalized Therapy: Zinc modulation for patients with MTF1/SLC39A12 variants
  • Family Counseling: More accurate recurrence risk based on complete genetic architecture
  • Novel Drug Targets: Zinc pathway modulators for treatment-resistant cases
  • Prognostic Testing: Predict severity at diagnosis, not years later

Iron-Zinc Pathway Interaction with Modifier Genes

Hemochromatosis Iron-Zinc Pathway

Complete iron-zinc regulatory pathway showing multiple hemochromatosis types. HFE (Type 1) requires modifier genes for severe phenotype. Rare variants in SLC39A12 (zinc transporter) and MTF1 (zinc-responsive transcription factor) regulate HAMP expression, creating epistatic interaction with HFE mutations. Other hemochromatosis genes shown: HJV (Type 2A), HAMP (Type 2B), TFR2 (Type 3), SLC40A (Type 4), FTH1 (Type 5), plus iron metabolism modifiers (TMPRSS6, BMP2, BMP6).

NP

Niemann-Pick Type C Disease

Severe Progressive Neurodegenerative Ataxia

The Paradigm Shift

Niemann-Pick has been misclassified as a cholesterol disease for decades:

  • Same NPC1 mutations cause infantile vs. adult-onset (decades apart)
  • Variable progression: rapid neurodegeneration vs. slow decline
  • ❌ Old view: Cholesterol storage → cholesterol drugs (limited efficacy)
  • ✓ New discovery: Iron-dependent ferroptosis → NRF2 activators available
Niemann-Pick Ferroptosis Discovery

🔬 What We Discovered

NPC1 Mutation + Ferroptosis Pathway Modifiers in this Family

NPC1 — Primary lysosomal mutation

Traditional focus: cholesterol accumulation, but triggers iron overload

Ferroptosis Genes — Iron-dependent cell death pathway

COX10, ALOX5, PSMB8, GCLC modulate lipid peroxidation sensitivity

NRF2 Pathway — Antioxidant defense system

Protective variants slow progression; target for FDA-approved drugs

Glutathione System — Cellular antioxidant defense

SLC7A11, SLC3A2 (System xc-) import cysteine for GSH synthesis

🧬 Novel Biology

From Cholesterol Storage to Ferroptosis

  • Iron accumulation: NPC1 defect causes Fe++ buildup in mitochondria
  • Lipid peroxidation: Iron catalyzes PUFA oxidation (arachidonic acid pathway)
  • GSH depletion: System xc- dysfunction prevents antioxidant synthesis
  • NRF2 failure: Insufficient stress response in severe cases

💊 Clinical Impact

  • Disease Reclassification: Ferroptosis disorder enables repurposing of FDA-approved drugs
  • Omaveloxolone (Skyclarys®): NRF2 activator already approved for Friedreich's ataxia
  • Combination Therapy: Iron chelation + NRF2 activation + lipid peroxidation inhibition
  • Prognostic Stratification: Ferroptosis modifier genes predict progression rate
  • Clinical Trial Design: Enrich for patients with druggable NRF2 pathway variants

Complete Ferroptosis Pathway with Modifier Genes & FDA-Approved Drug Targets

Niemann-Pick Ferroptosis Pathway with Modifiers

NPC1 oxidation triggers iron accumulation → lipid peroxidation → ferroptotic cell death. Modifier genes (highlighted in colored boxes) affect cholesterol pathway (NPC1, NPC2, MALL, COX10, GCLC), sphingomyelin pathway (SMPD1, AGMO, PAH, NPC2), and lipid peroxidase pathway (ALOX5, AGMO, PSMB8). NRF2 activation by omaveloxolone targets multiple pathway components including ALOX5, PSMB8, GCLC, STING, and SLC40A1.

The Paradigm Shift

Even "single-gene" diseases are molecularly heterogeneous. Standard genetic testing tells patients "You have the mutation" but can't predict severity or treatment response. Our platform reveals the modifier landscape that determines clinical outcomes—enabling true precision medicine even for rare diseases.

Why Traditional Approaches Miss This

❌ Standard Genetic Testing

Identifies the primary mutation (HFE, NPC1) but ignores modifier variants that determine severity

❌ Whole Genome Sequencing

Generates millions of variants but lacks framework to identify which modifiers matter

✓ Our Platform

Extracts subtype-defining signals from family data and integrates regulatory variants to reveal functional subtypes

Rare Disease Applications

Our platform applies to any genetically complex rare disease:

📊 Clinical Trial Stratification

Enrich for drug-responsive molecular subtypes

🎯 Prognostic Precision

Predict disease severity at diagnosis

💊 Treatment Selection

Match patients to optimal therapies

🧬 Drug Development

Identify novel therapeutic targets per subtype

Explore Rare Disease Collaborations

Platform Applications

Our molecular subtyping platform enables precision medicine across diverse therapeutic areas and stakeholders.

🧬 For Genetic Testing Companies

Enhanced Test Reports

  • Molecular subtype classification for any condition
  • Pathway-based interpretation of variants
  • Actionable insights beyond standard VCF analysis
  • Clinical trial matching opportunities

🏥 For Healthcare Systems

Clinical Decision Support

  • Subtype-specific treatment recommendations
  • Risk stratification for comorbidities
  • Prognostic information
  • Integration with existing EHR workflows

💊 For Pharmaceutical Companies

Patient Stratification

  • Identify mechanistically-defined patient populations
  • Enrich clinical trials with responders
  • Reduce trial failure rates
  • Enable precision medicine drug development

🔬 For Research Institutions

Discovery Platform

  • Identify novel disease subtypes
  • Generate mechanistic hypotheses
  • Prioritize therapeutic targets
  • Enable population-scale studies

Platform Versatility: Any Disease, Any Trait

Our autism analysis proves the power of mining genomic signals that others discard. The same proprietary methods apply to any complex condition with genetic contributions.

Potential applications include: psychiatric disorders (schizophrenia, bipolar disorder, ADHD), neurodevelopmental conditions (intellectual disability, epilepsy), cancer molecular subtypes, cardiovascular disease stratification, autoimmune conditions, rare disease characterization, pharmacogenomic response prediction, and complex trait architecture. Our platform scales from focused cohorts to biobank-level datasets.

Partnership Opportunities

We're seeking strategic partners to scale our molecular subtyping platform across therapeutic areas and bring precision medicine to patients worldwide.

Ready to Enable Precision Medicine?

Contact us to discuss how our platform can transform diagnostics and treatment in your therapeutic area.

Get In Touch

Leadership Team

MG

Michael R. Garvin, Ph.D.

Founder & Chief Scientific Officer | Research Professor, University of New Mexico

Dr. Garvin is a molecular geneticist with over 20 years of experience in precision medicine and computational biology. He holds a Ph.D. from the University of Alaska Fairbanks and a Certificate in Personalized & Genomic Medicine from the University of Colorado Denver. His career spans Oak Ridge National Laboratory, Oregon State University, and biotechnology companies including Tularik (Amgen) and CV Therapeutics (Gilead).

His research focuses on identifying the genetic basis of complex diseases through novel computational approaches. With over 37 peer-reviewed publications in journals including Genome Biology, eLife, and PLoS Genetics, and over $5 million in NIH and DOE funding, Dr. Garvin has established himself as a leader in precision medicine research.

His COVID-19 research became the 2nd most viewed article in eLife history with over 154,000 views. Dr. Garvin founded Williwaw Biosciences after discovering that family-based genomic data contains rich subtyping information systematically discarded by conventional analysis pipelines—a breakthrough that enables precision medicine across any complex disease.

BG

Ben Garvin

Co-Founder & Chief Business Officer

Ben Garvin brings extensive experience in technology commercialization and strategic partnerships, with a proven track record of successfully selling advanced algorithms and technology solutions to large enterprises in the internet advertising space.

As Chief Business Officer, Ben leads business development, strategic partnerships, and commercialization efforts, translating Williwaw's scientific innovations into market-ready solutions for the precision medicine industry.

Contact Us

Interested in applying our platform to your therapeutic area or exploring partnership opportunities?

[email protected]

For clinical partnerships, licensing inquiries, or investment opportunities, please reach out directly.