GENOMICS

GENOMICS = GENOMIC_STANDARD × CANONIC = Structure(genomics) × (C1, C2, Temporal, Relational, C5, C6) = owned genomic data vertical

GENOMICS = C1 ∩ C2 ∩ Temporal ∩ Relational ∩ C5 ∩ C6 = ENTERPRISE (#63)

Genomics is full Enterprise because:

• C1: Variant classifications must be stated (pathogenic, benign, VUS)
• C2: Every classification must cite supporting evidence (ClinVar, COSMIC)
• Temporal: Variant classifications change over time (reclassification)
• Relational: Gene → variant → disease → treatment chains
• C5: CLIA compliance, genetic counseling requirements
• C6: GA4GH standards (VCF, FHIR Genomics, Phenopackets)

1. Patient Sovereignty Over Genomic Data

The patient owns their genomic data. Consent MUST be explicit for every use.

Example: A patient’s whole genome sequence is stored. Research use requires separate consent from clinical use. The patient can revoke access at any time. GINA protections apply.

2. Variant Classification Integrity

Variant classifications MUST follow recognized guidelines (ACMG/AMP) and be traceable.

Example: BRCA1 c.68_69delAG classified as “Pathogenic” — this MUST reference: ACMG criteria applied (PVS1, PM2, PP3), supporting evidence (ClinVar ID, publications), and date of classification. Reclassification creates new entry, preserving original.

3. Temporal Reclassification

Genomic knowledge evolves. Classifications MUST be versioned, not overwritten.

Example: A variant classified as VUS in 2023 is reclassified to Likely Pathogenic in 2025 based on new functional studies. Both classifications exist in the record with timestamps. Patients with this variant are notified of reclassification.

4. Cross-Domain Composition

Genomics composes with other medical subdomains for precision medicine.

Example: MEDICINE × GENOMICS = pharmacogenomics (drug response prediction). MEDICINE × ONCOLOGY × GENOMICS = tumor profiling (MAMMOCHAT + variant analysis). The genomic layer adds molecular evidence to clinical decisions.

5. Analytical Validity

Every genomic assay MUST demonstrate analytical validity before clinical use. Sensitivity, specificity, and reproducibility MUST be quantified.

Example: A clinical NGS panel for hereditary cancer genes MUST demonstrate: ≥99.9% sensitivity for SNVs, ≥99% sensitivity for small indels, ≥95% sensitivity for CNVs >1 exon, ≥99.9% specificity, and inter-run concordance ≥99.5%. These metrics MUST be established through validation studies using characterized reference materials (Genome in a Bottle NA12878). The assay does not go clinical until validation is complete and documented.

6. Genetic Counseling Requirement

Genomic results with clinical significance MUST be accompanied by genetic counseling. No result disclosure without interpretation support.

Example: A patient receives a positive BRCA1 pathogenic variant result. Before disclosure: a board-certified genetic counselor (CGC) reviews the case, prepares a counseling session covering penetrance estimates (72% breast cancer risk by age 80), risk management options (enhanced screening, prophylactic surgery, chemoprevention), family implications (50% chance for first-degree relatives), and psychological support resources. The result is NOT released directly to the patient portal without counseling. The counseling session is documented in the medical record with CPT 96040.

7. Bioinformatics Pipeline Governance

Every computational step from raw reads to variant calls MUST be versioned, reproducible, and validated. No black-box algorithms.

Example: A clinical WES pipeline consists of: FASTQ QC (FastQC v0.12.1) → alignment (BWA-MEM2 v2.2.1, GRCh38) → duplicate marking (GATK MarkDuplicates v4.5) → variant calling (GATK HaplotypeCaller v4.5) → annotation (VEP v110) → filtering (gnomAD v4.0, ClinVar 2025-01). Every tool version, reference genome build, and filter threshold MUST be documented. A pipeline version change requires re-validation with truth set comparison. Results from different pipeline versions MUST NOT be directly compared without harmonization.

Pattern: Higher analytical complexity → more lattice dimensions required. Clinical decisions MUST NOT be made on tests below PATENT tier.

Genomic variant classification is not static. Knowledge evolves. Reclassification is the temporal dimension that makes genomics governance uniquely complex.

Reclassification Triggers

Reclassification Protocol

`` IF reclassification_event:

1. Generate new classification with timestamp
2. Preserve original classification (MUST NOT overwrite)
3. Document delta: which evidence codes changed and why
4. Identify all patients who carry this variant
5. Notify ordering providers of reclassification
6. Update clinical decision support rules
7. Trigger genetic counseling for affected patients if clinically significant change
8. Submit to ClinVar with assertion criteria `

Temporal Complexity

` Variant: BRCA2 c.8167G>C (p.Asp2723His)

Timeline: 2018-03: Classified VUS (PM2, PP3) 2019-11: Functional study published — abnormal HDR assay 2020-02: Reclassified Likely Pathogenic (PM2, PP3, PS3_moderate) 2021-08: Second functional study confirms — splicing defect 2021-09: Reclassified Pathogenic (PM2, PP3, PS3_strong, PS4_moderate) 2021-10: 47 patients notified, 12 management changes, 3 prophylactic surgeries

Each classification = immutable record Each reclassification = new record pointing to previous Chain = complete temporal governance of genomic knowledge ``

`` DECLARE(ClinicalGenomics) = ACMG_AMP × CANONIC

Where: ACMG/AMP provides Structure: - 28 evidence criteria (PVS1, PS1-4, PM1-6, PP1-5, BA1, BS1-4, BP1-7) - 5-tier classification (Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign) - Gene-disease clinical validity framework - Variant curation workflow

CANONIC provides Governance: - C1: Variant classification claims with evidence codes - C2: Supporting evidence (ClinVar, functional data, population frequency) - Temporal: Classification date, reclassification history - Relational: Gene → variant → disease → treatment chain - C5: Lab operations (CLIA compliance, genetic counseling) - C6: ACMG/AMP/GA4GH conformance

Result: ClinicalGenomics = ENTERPRISE (#63)

Classification Lifecycle: Sequence — Specimen processed, variants called Annotate — Population frequency, in silico predictions Classify — ACMG criteria applied, evidence weighed Report — Clinical report issued, counseling provided Govern — ClinVar submission, reclassification monitored `

` DECLARE(TumorProfiling) = AMP_ASCO_CAP × CANONIC

Where: AMP/ASCO/CAP provides Structure: - 4-tier somatic variant classification - Therapeutic, diagnostic, prognostic significance - Biomarker reporting requirements - Companion diagnostic linkage

CANONIC provides Governance: - C1: Variant significance claims (Tier I-IV) - C2: Evidence (clinical trials, FDA approvals, NCCN guidelines) - Temporal: Knowledge base update cycle, reclassification - Relational: Tumor → variant → therapy → trial chain - C5: Lab operations (CLIA, CAP proficiency testing) - C6: AMP/ASCO/CAP/FHIR Genomics conformance

Result: TumorProfiling = ENTERPRISE (#63)

Profiling Lifecycle: Biopsy — Specimen accessioned, tumor content verified Sequence — NGS panel run, variants called Interpret — AMP/ASCO/CAP criteria applied Report — Actionable variants reported to oncologist Treat — Matched therapy initiated, trial enrolled `

` DECLARE(PharmacogenomicsGuidance) = CPIC × CANONIC

Where: CPIC (Clinical Pharmacogenetics Implementation Consortium) provides Structure: - Gene-drug interaction guidelines (>25 gene-drug pairs) - Diplotype to phenotype translation tables - Dosing recommendations per metabolizer status - Allele function assignments - Frequency tables per biogeographic group

CANONIC provides Governance: - C1: Metabolizer phenotype claims (PM, IM, NM, RM, UM) - C2: Genotyping evidence (star allele calls, activity scores) - Temporal: Guideline version, allele definition updates - Relational: Gene → diplotype → phenotype → drug → dose chain - C5: Clinical decision support rules, pharmacist review - C6: CPIC/PharmGKB/FHIR PGx conformance

Result: PharmacogenomicsGuidance = PATENT (#57)

PGx Lifecycle: Genotype — Star alleles called from sequencing data Translate — Diplotype → phenotype per CPIC table Recommend — Dosing recommendation generated Review — Pharmacist reviews, CDS fires in EHR Govern — CPIC guideline version tracked, updates trigger re-review `

` DECLARE(LiquidBiopsy) = FDA_CDx × CANONIC

Where: FDA Companion Diagnostic Framework provides Structure: - Premarket approval (PMA) or 510(k) pathway - Analytical validation requirements - Clinical validation (concordance with tissue) - Intended use statement (specific drug/indication) - Labeling requirements

CANONIC provides Governance: - C1: Variant detection claims per analyte (ctDNA, CTCs) - C2: Analytical evidence (LOD, sensitivity at 0.1% VAF, specificity) - Temporal: Sample collection to result TAT, ctDNA half-life considerations - Relational: Blood draw → cfDNA extraction → library → sequencing → variant chain - C5: Lab operations (pre-analytical: tube type, processing time, storage temp) - C6: FDA CDx/CAP/CLIA/FHIR Genomics conformance

Result: LiquidBiopsy = ENTERPRISE (#63)

Testing Lifecycle: Collect — Streck tube, processed within 72h Extract — cfDNA isolated, quantity assessed Sequence — Panel sequenced, UMI error correction Call — Variants called above LOD threshold Report — Actionable variants reported, CDx match Treat — Matched therapy, monitoring schedule set `

` DECLARE(NewbornScreeningGenomics) = ACMG_RUSP × CANONIC

Where: ACMG/RUSP provides Structure: - Recommended Uniform Screening Panel (37 core conditions) - Secondary conditions (26 conditions) - Screening algorithm per condition - Confirmatory testing requirements - Follow-up and treatment protocols

CANONIC provides Governance: - C1: Screening result claims (positive/negative/borderline) - C2: Confirmatory evidence (biochemical, molecular, functional) - Temporal: Critical time windows (e.g., PKU treatment within 7 days) - Relational: Newborn → specimen → screen → confirm → treat → follow-up chain - C5: State NBS program operations, parental notification - C6: ACMG/RUSP/CLSI NBS01 conformance

Result: NewbornScreeningGenomics = AGENT (#127) — time-critical, life-or-death

Screening Lifecycle: Collect — Heel prick, DBS collected 24-48h after birth Screen — MS/MS or molecular screening performed Flag — Positive screen flagged, parent notified Confirm — Confirmatory testing (sequencing, enzyme assay) Treat — Treatment initiated within time window Govern — Long-term follow-up, outcome tracking Protect = AGENT (#127) — Time-critical governance, no delay tolerated ``

GENOMICS × MEDICINE = Precision medicine (ACMG/AMP + mCODE + FHIR Genomics) GENOMICS × MEDICINE/ONCOLOGY = Tumor profiling, matched therapy (AMP/ASCO/CAP + NCCN) GENOMICS × MEDICINE/PHARMACY = Pharmacogenomics, CDS alerts (CPIC + PharmGKB + FHIR PGx) GENOMICS × AGRICULTURE = Crop genomics, GMO governance (NOP + sequencing protocols) GENOMICS × DEFENSE = Biosurveillance, pathogen genomics, biodefense (DoD + CDC + BARDA) GENOMICS × EDUCATION = Bioinformatics curriculum, genetic counseling training (ABET + ACGC) GENOMICS × QUALITY = Lab accreditation, proficiency testing, EQA (CAP + ISO 15189 + EMQN) GENOMICS × ROBOTICS = Automated sequencing, liquid handling, lab automation (IEC 61010 + GA4GH) GENOMICS × FINANCE = Genetic testing market, DTC regulation, health economics (FDA + FTC + ICER) GENOMICS × LOGISTICS = Biospecimen shipping, cold chain, biobanking (IATA DG + GDP + ISBER) GENOMICS × MANUFACTURING = Sequencer manufacturing, reagent production (ISO 13485 + GMP) GENOMICS × ENERGY = Bioenergy, microbial genomics for biofuels (DOE JGI + GA4GH) GENOMICS × REAL_ESTATE = Lab facility design, BSL compliance (CDC/NIH BMBL + building codes) GENOMICS × LAW = Genetic privacy, GINA enforcement, forensic DNA (DOJ + CODIS + GINA) GENOMICS × AUTOMOTIVE = Biosensor automotive, allergen monitoring (emerging)

15 cross-domain compositions. Each strengthens PROV-001 and PROV-003 patent claims.

Gap: No existing system provides governance-gated genomic classification with O(1) bitwise compliance checking across variant interpretation, reclassification tracking, pipeline versioning, genetic counseling enforcement, and cross-domain composition. Every competitor addresses one slice. CANONIC governs the full chain: specimen → pipeline → classification → reclassification → counseling → clinical action → outcome tracking.

To create a CANONIC genomics vertical:

Identify genomics domain (clinical genetics, somatic, pharmacogenomics, reproductive, newborn screening, population, functional, metagenomics) Determine classification framework (ACMG/AMP germline, AMP/ASCO/CAP somatic, CPIC pharmacogenomics) Determine CLIA complexity and map to MAGIC tier — clinical decisions require PATENT (#57) minimum Create scope with CANON.md inheriting /GENOMICS/ Define variant classification claims per evidence criteria — all 28 ACMG codes if germline, 4-tier if somatic Version bioinformatics pipeline — every tool version, reference genome, annotation database documented Map to regulatory framework (CLIA, CAP, GA4GH, FDA IVD/LDT, GINA, state laws) Implement reclassification protocol — temporal governance of evolving variant knowledge Enforce genetic counseling requirement — no result disclosure without interpretation support Implement validators for classification evidence, pipeline reproducibility, counseling compliance Document coverage with lab evidence — proficiency testing results, analytical validation data Submit to community databases — ClinVar, ClinGen, PharmGKB as governed contributions

Result: Owned genomics vertical with classification-governed, temporally-versioned, evidence-traced, counseling-enforced operations. The deepest governance chain in CANONIC because genomic knowledge is the most dynamic — every classification is a living document.