bio-clinical-databases-pharmacogenomics

Version Compatibility

Reference examples tested with: PharmCAT 2.13+, Cyrius 1.1+ (Chen 2021), Aldy 4.0+, Stargazer 2.0+, StarPhase 1.0+ (PacBio HiFi), HIBAG 1.40+, requests 2.31+, pandas 2.2+. CPIC guideline versions are gene-specific; PharmVar releases are quarterly. DPYD dosing uses the CPIC gene activity-score system (Amstutz 2018 Clin Pharmacol Ther 103:210, the 2017-update guideline); the 2025 TPMT/NUDT15 update (Maillard 2026) refines compound-IM dosing.

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. PharmVar is the authoritative star-allele source (https://www.pharmvar.org); the older Human CYP Allele Nomenclature Database was deprecated in 2017.

Pharmacogenomics; Star Alleles, Activity Scores, and CPIC/DPWG Guidance

'What is my patient's CYP2D6 metabolizer status and should I adjust their tamoxifen dose?' -> Call star alleles (haplotype-level), translate diplotype -> activity score -> phenotype, apply CPIC + DPWG dosing.

• CLI (recommended): pharmcat -vcf input.vcf.gz -o pharmcat_out; CPIC-recommended, single-tool reporting
• CLI (CYP2D6 SV-aware): cyrius -m sample.bam -o cyrius_out; mandatory addition for CYP2D6
• CLI (multi-gene CN-aware): aldy genotype -p illumina sample.bam; alternative
• CLI (long-read 8-field): PacBio HiFi starphase; transplant-grade including HLA
• R (SNP-array): HIBAG for HLA-B57:01/B15:02/B58:01/A31:01 imputation
• API: requests.get('https://api.pharmgkb.org/v1/data/clinicalAnnotation', ...)

Governance: CPIC vs DPWG vs PharmGKB vs FDA

These four authorities are routinely conflated. They differ in scope, scale, and recommendations:

Authority	Scope	Output	Anchors
CPIC (US Clinical Pharmacogenetics Implementation Consortium)	Once a result is available, what to prescribe	Level A/B/C/D gene-drug pair + strength of recommendation per phenotype + evidence quality	~26 guidelines, ~25 genes, 100+ drugs as of 2026
DPWG (Dutch Pharmacogenetics Working Group)	Whether to test AND what to prescribe	5-pt (0-4) evidence + 7-pt (AA-F) clinical-relevance scale	G-Standaard (Dutch EHR-integrated); RCT-validated via PREPARE
PharmGKB clinical annotation levels	Evidence cataloguing	1A/1B/2A/2B/3/4	1A = guideline OR medical-society OR PGRN/eMERGE implementation; NOT pure evidence
FDA Table of Pharmacogenomic Biomarkers	Drug label info	~300 drugs (informational)	NOT an actionability list; many entries are dosing-suggestion-only
FDA Table of Pharmacogenetic Associations	Actionable subset	Closer to CPIC	Compare head-to-head with CPIC

Bank et al 2018 Clin Pharmacol Ther 103:599 (DOI 10.1002/cpt.762) is the canonical CPIC-vs-DPWG comparison. Notable disagreements:

• CYP2D6 IM + multiple antidepressants: DPWG actionable; CPIC says insufficient evidence.
• HLA-B*15:11 carbamazepine: DPWG actionable; CPIC silent.
• CYP2C19 IM + voriconazole: dosing magnitudes differ 25-50%.

Common PGx-evidence critiques: (1) EUR over-representation in discovery cohorts; (2) most PGx RCTs are open-label / prescriber-unblinded; (3) publication bias in antiseizure PGx may overstate effects ~2x; (4) subjective composite endpoints.

PharmGKB Clinical Annotation Levels: What 1A Actually Means

Level	Requirement
1A	Variant-drug pair appears in CPIC guideline OR medical-society guideline OR is implemented at a PGRN/eMERGE site
1B	Replication in multiple cohorts; preponderance of evidence; no formal guideline yet
2A	Replicated association in a VIP (Very Important Pharmacogene)
2B	Replicated association in non-VIP gene
3	Single significant association OR mixed-evidence variant-drug pair
4	In vitro / case report / molecular evidence only

1A does NOT require RCT evidence; mechanism + guideline status suffices.

Star Allele Nomenclature (PharmVar)

PharmVar (https://www.pharmvar.org) is authoritative for: CYP1A1, CYP1A2, CYP1B1, CYP2A6, CYP2A13, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP2F1, CYP2J2, CYP2R1, CYP2S1, CYP2W1, CYP3A4, CYP3A5, CYP3A7, CYP3A43, CYP4A11, CYP4F2, CYP19A1, CYP26A1, DPYD, NUDT15, SLCO1B1, TPMT.

A star allele is a haplotype, not a single variant. Suballeles (*1.001, *1.002, etc.) encode the exact SNV+indel pattern within a defined functional haplotype.

*The 1 reference is the PharmVar consensus reference, NOT biological wild type. Defined as the absence of all known functional variants at the locus.

CYP2D6 Activity Scores (Caudle 2020 Clin Transl Sci; DOI 10.1111/cts.12692)

Phenotype	Activity score (AS) range
PM (Poor Metabolizer)	0
IM (Intermediate Metabolizer)	0 < AS < 1.25
NM (Normal Metabolizer)	1.25 <= AS <= 2.25
UM (Ultra-rapid)	AS > 2.25

Key per-allele activity values (selected):

Allele	Activity	Notes
*1, *2, *35	1.0	Normal
*3, *4, *5 (gene deletion), *6, *7, *8, *11, *12, *15, *19, *20, *36, *40, *42	0	No function
*9, *41, *17, *29	0.5	Decreased function (substrate-specific caveats for *17)
*10	0.25	Caudle 2020 RESET from 0.5 to 0.25; reclassified large fractions of East-Asian populations to IM
*68	0	Hybrid; non-functional

*4xN is clinically silent: a no-function allele multiplied by N is still no-function. Reporting *4xN as UM is the most-common reportable error in clinical PGx.

CYP2D6 Structural Complexity

CYP2D6 on 22q13.2 sits adjacent to the highly-similar CYP2D7 pseudogene. Four classes of structural variant that no SNV-only caller can resolve:

1. Gene deletion (*5): ~13 kb deletion; activity 0; diagnostic REP6/REP7 breakpoint.
2. Gene duplication/multiplication (*1xN, *2xN, *4xN, *10xN, *17xN, *35xN, *36xN): Tandem copies; clinical impact depends on which allele is amplified; *4xN is clinically silent.
3. CYP2D7 -> CYP2D6 hybrids (*13): Pseudogene fused 5'; non-functional.
4. CYP2D6 -> CYP2D7 hybrids (*36, *61, *63, *68, *83): 5' CYP2D6 with 3' pseudogene exon 9 conversion; typically embedded in duplications upstream of *10 (East Asian) or upstream of *4 (European).

GATK / DeepVariant alone cannot call any of these. They operate on multi-mapper-filtered BAMs; 97%+ identity between CYP2D6 and CYP2D7 produces silent miscalls of every *5, *13, *36, *68, *4xN sample.

Algorithmic Taxonomy: Star Allele Callers

Tool	CYP2D6 SV	CYP2D6 CN	Other PGx genes	Phased	Validation	Fails when
PharmCAT (Sangkuhl 2020 Clin Pharmacol Ther)	No (consumes outside SV calls)	No	21 CPIC genes; full clinical reporting	Phased or unphased VCF	High; CPIC reference	CYP2D6 SV-rich samples need Cyrius/StellarPGx upstream
Cyrius (Chen 2021 Pharmacogenomics J)	Yes (99.3% concordance)	Yes	CYP2D6 only	Phased haplotypes	GeT-RM 99.3%	Other genes (single-purpose tool)
BCyrius (PubMed 39901590, 2025)	Yes (extended)	Yes	CYP2D6 only	Phased	Extended SV diversity	Other genes
Aldy v4 (Numanagic 2018 Nat Commun)	Yes	Yes	CYP2D6, CYP2A6, CYP2B6, etc.	Phased	GeT-RM 82-87% (CYP2D6)	Less accurate than Cyrius for CYP2D6
Stargazer (Lee 2019 Genet Med)	Limited	Yes	~50 PGx genes	Statistical phasing	~84% (CYP2D6)	Fails on rare alleles; statistical phasing is unstable
StellarPGx	Yes (~99%)	Yes	CYP2D6 + others	Phased	GeT-RM ~99%	Less widely deployed than Cyrius
Astrolabe (proprietary, formerly Constellation)	Yes	Yes	Multi-gene	Proprietary	Industry-validated	License required
StarPhase (PacBio HiFi 2024+)	Yes	Yes	All CPIC Level A genes + HLA	Native phasing	Long-read gold standard	Requires PacBio HiFi

Canonical clinical workflow 2024-2026: PharmCAT for the panel + Cyrius (or StellarPGx) for CYP2D6 SVs + dedicated HLA typer (T1K, OptiType, HLA-LA) for HLA.

Twesigomwe 2020 npj Genom Med: inter-tool discordance 10-18% on CYP2D6; nearly all in samples carrying SVs.

HLA-Drug Associations: Mechanistically Distinct from CYP

HLA associations are idiosyncratic immune reactions, not dose-response phenomena. Effect sizes (OR 50-1000+) far exceed any CYP polymorphism. Testing rationale is screen-and-avoid, not dose-adjust.

Allele	Drug	Reaction	Population	Landmark
HLA-B*57:01	Abacavir	HSS	All ancestries (5-8% NFE)	Mallal 2008 NEJM (PREDICT-1)
HLA-B*15:02	Carbamazepine, oxcarbazepine, phenytoin, lamotrigine (weaker)	SJS/TEN	Han Chinese, Thai, Malay, Indian (>=5%)	Chung 2004 Nature; FDA black-box 2007
HLA-A*31:01	Carbamazepine	DRESS, MPE, SJS/TEN	Europeans (2-5%), Japanese	McCormack 2011 NEJM
HLA-B*58:01	Allopurinol	SJS/TEN, DRESS	Han Chinese (10-15%), Thai, Korean	Hung 2005 PNAS (OR ~580)
HLA-B*13:01	Dapsone	DDS	Han Chinese, SE Asian	Zhang 2013 NEJM
HLA-B*35:02 (NOT *35:01)	Minocycline	DILI	All	Urban 2017 J Hepatol
HLA-B*35:01	TMP-SMX	DILI, DRESS-like	African American	Li 2021 Hepatology
HLA-B*14:01	TMP-SMX	DILI	European American (OR 9.20)	Li 2021
HLA-A*33:01/03	Terbinafine	DILI	Multi-ancestry	Nicoletti 2017
HLA-DRB1*15:01-DQB1*06:02 haplotype	Amoxicillin-clavulanate	DILI	Europeans	Stephens 2013
HLA-B*15:13	Phenytoin	SJS	Malaysian	Chang 2017

Critical: HLA screening requires 4-field resolution. *57:01 (abacavir risk) vs *57:03 (no risk); *35:02 (minocycline DILI) vs *35:01 (TMP-SMX DILI). See clinical-databases/hla-typing for typing.

Non-CYP Pharmacogenes: Variant-Level Detail

DPYD (5-FU / Capecitabine / Tegafur); Activity Score Framework

The CPIC DPYD guideline (Amstutz 2018 Clin Pharmacol Ther 103:210) uses a gene activity score system. Activity values: normal-function = 1.0, decreased = 0.5, no function = 0.

Variant	rsID	Allele	Activity
c.1905+1G>A	rs3918290	DPYD*2A	0 (splice disruption)
c.1679T>G	rs55886062	DPYD*13 (p.I560S)	0
c.2846A>T	rs67376798	(p.D949V)	0.5
c.1129-5923C>G / c.1236G>A (HapB3)	rs56038477 / rs75017182	HapB3	0.5

Gene AS = sum of two lowest activities. Recommended dose: AS 2 = full dose; AS 1.5 = 50% start + TDM; AS 1.0 = 50% start + TDM; AS 0 = avoid.

c.85T>C (DPYD*9A) is NOT in the CPIC actionable set despite frequent commercial reporting; evidence does not support clinical decrement.

EU universal pre-treatment testing standard since Henricks 2018 Lancet Oncol (genotype-guided dosing lowered severe fluoropyrimidine toxicity in DPYD variant carriers, e.g. DPYD*2A grade >=3 toxicity RR 2.87 -> 1.31) and EMA 2020 endorsement. US lags; ASCO/NCCN moved 2022-2024.

TPMT + NUDT15 (Thiopurines); 2025 Update

Maillard 2026 Clin Pharmacol Ther update emphasizes greater dose reduction for compound TPMT/NUDT15 IM.

Gene	Variant	Activity	Population
TPMT *2	c.238G>C	0	--
TPMT *3A	c.460G>A + c.719A>G	0	EUR-common
TPMT *3B	c.460G>A	0	--
TPMT *3C	c.719A>G	0	AFR / EAS dominant
NUDT15 *3	c.415C>T (rs116855232)	0	~9.8% East Asian; <1% EUR

NUDT15 *3 is the dominant thiopurine determinant in East Asians; TPMT-alone testing misses these patients (Yang 2015 J Clin Oncol).

UGT1A1 (Irinotecan, Atazanavir)

• *28 (TA7 promoter repeat vs *1 = TA6, *37 = TA8); EUR-common
• *6 (c.211G>A, p.G71R); East Asian dominant
• Severe neutropenia in *28/*28 at irinotecan >=180 mg/m^2

CYP2C19 + Clopidogrel; The Most-Litigated Pair

• Pare 2010 NEJM: no benefit of clopidogrel in *2 carriers in CURE/ACTIVE-A.
• TAILOR-PCI (Pereira 2020 JAMA): 5,302 patients post-PCI; primary endpoint MACE @12mo HR 0.66, p=0.06 (negative by pre-specified alpha) but positive in sensitivity analyses.
• Pereira NL et al 2021 meta-analysis (7 RCTs, 15,949 patients): ~30% MACE reduction in CYP2C19 LOF carriers (JACC Cardiovasc Interv 14:739).
• Consensus 2024 (ACC/AHA/ESC): genotype-guided therapy reasonable; strongest in post-PCI ACS.

Warfarin (CYP2C9 + VKORC1 + CYP4F2)

• EU-PACT 2013 NEJM: PGx dosing positive (European).
• COAG 2013 NEJM: PGx dosing negative; worse in African Americans because algorithm omitted CYP2C9 *5, *6, *8, *11 alleles common in African ancestry. Paradigmatic ancestry-algorithm failure (Daneshjou 2014 Blood).
• IWPC algorithm explains 47-55% of dose variance.

SLCO1B1 + Simvastatin

• rs4149056 (c.521T>C, p.V174A); OR 4.5 per C allele for myopathy on 80 mg simvastatin (SEARCH 2008 NEJM).
• 2022 CPIC update broadened to all statins with SLCO1B1 substrate behavior.

Other Actionable

• *CYP2B6 6 (c.516G>T + c.785A>G): efavirenz dose 600 -> 400 mg in *6/*6 (ENCORE1).
• *CYP3A5 3 (rs776746): non-expressers (*3, *6, *7) are the common state in non-AFR; expressers need 1.5-2x higher tacrolimus dose.
• G6PD (CPIC 2022 Gammal 2023): X-linked; female heterozygotes have mosaic activity that single-timepoint assay misclassifies.

Decision Tree by Scenario

Scenario	Recommended path	Why
Multi-gene PGx panel from VCF	PharmCAT	CPIC-recommended; 21 genes + full clinical reporting
CYP2D6 with structural variants	Cyrius (or StellarPGx)	Only tools with reliable SV calling from short-read
All CPIC Level A + HLA from one sample	PacBio HiFi + StarPhase	Long-read single-pass typing
Pre-emptive panel for cohort	PREPARE-style 12-gene panel	Swen 2023 RCT-validated
HLA-B*57:01 abacavir screen	T1K or OptiType (4-field); HIBAG if SNP-array	Need 4-field specificity
African-ancestry warfarin	IWPC algorithm + CYP2C9 *5/*6/*8/*11 explicit	COAG failure paradigm
East Asian thiopurine	NUDT15 + TPMT	NUDT15 *3 is dominant in EAS
Compound IM (TPMT + NUDT15)	Apply 2025 update	More aggressive dose reduction than single-gene IM
Activity score interpretation	Caudle 2020 thresholds for CYP2D6; gene-specific for others	Per CPIC

PharmCAT Workflow (Recommended Multi-Gene Pipeline)

Goal: Generate CPIC-compliant pharmacogenomic report from a phased or unphased VCF covering 21 PGx genes.

Approach: Run PharmCAT on the VCF; supplement CYP2D6 with Cyrius output if SVs suspected; cross-reference HLA from separate typing.

# PharmCAT (CPIC-recommended; covers 21 genes including CYP2C19, CYP2C9, CYP2D6,
# DPYD, TPMT, NUDT15, UGT1A1, SLCO1B1, CYP3A5, CYP4F2, VKORC1, IFNL3/IFNL4, etc.)

# 1. Preprocess VCF (ensures correct ref allele alignment + chr formatting)
pharmcat_vcf_preprocessor.py \
    -vcf input.vcf.gz \
    -refFna GRCh38.fa \
    -o pharmcat_input/

# 2. Run PharmCAT
java -jar pharmcat.jar \
    -vcf pharmcat_input/input.preprocessed.vcf.bgz \
    -o pharmcat_output/

# Output: <sample>.report.html with phenotype, activity score, dosing recommendations

For CYP2D6 SV-rich samples, run Cyrius separately and pass outside calls to PharmCAT:

# Cyrius for CYP2D6 (99.3% concordance vs Aldy 82-87%, Stargazer 84%)
cyrius -m sample.bam -o cyrius_out --threads 8
# Output: cyrius_out/sample.tsv with diplotype + activity score

# Pass outside calls to PharmCAT
java -jar pharmcat.jar \
    -vcf pharmcat_input/input.preprocessed.vcf.bgz \
    -po cyrius_out/cyrius_for_pharmcat.tsv \
    -o pharmcat_output_with_cyrius/

CYP2D6 Activity Score Calculation

Goal: Convert CYP2D6 diplotype to activity score and phenotype with Caudle 2020 conventions.

Approach: Look up per-allele activity values; handle copy-number duplications; apply Caudle 2020 phenotype bins.

# Caudle 2020 activity values; *10 reset from 0.5 to 0.25 in 2020
CYP2D6_ACTIVITY = {
    '*1': 1.0, '*2': 1.0, '*35': 1.0,
    '*3': 0.0, '*4': 0.0, '*5': 0.0, '*6': 0.0, '*7': 0.0, '*8': 0.0,
    '*11': 0.0, '*12': 0.0, '*15': 0.0, '*19': 0.0, '*20': 0.0,
    '*36': 0.0, '*40': 0.0, '*42': 0.0, '*68': 0.0,
    '*9': 0.5, '*41': 0.5, '*17': 0.5, '*29': 0.5,
    '*10': 0.25,
    '*13': 0.0,
}


def cyp2d6_activity(diplotype):
    '''Convert CYP2D6 diplotype to activity score.

    Accepts e.g. '*1/*4' or '*2xN/*10' or '*4xN/*10'. Copy-number-aware:
    - *4xN is clinically silent (no-function * N = 0)
    - *1xN, *2xN multiply functional activity
    '''
    left, right = diplotype.split('/')
    return _allele_activity(left) + _allele_activity(right)


def _allele_activity(allele_str):
    '''Handle copy-number suffix xN. *4xN remains 0 (the most common mis-classification).'''
    if 'x' in allele_str:
        base, n = allele_str.split('x')
        copies = int(n) if n != 'N' else 2  # 'N' usually >=2; clinical assumes 2 unless quantified
        return CYP2D6_ACTIVITY.get(base, 1.0) * copies
    return CYP2D6_ACTIVITY.get(allele_str, 1.0)


def cyp2d6_phenotype(activity_score):
    '''Caudle 2020 phenotype bins.'''
    if activity_score == 0:
        return 'Poor Metabolizer'
    if activity_score < 1.25:
        return 'Intermediate Metabolizer'
    if activity_score <= 2.25:
        return 'Normal Metabolizer'
    return 'Ultrarapid Metabolizer'


# Example: *4xN/*10; the classic clinical-silence footgun
diplotype = '*4xN/*10'
score = cyp2d6_activity(diplotype)  # 0 (from *4xN) + 0.25 (from *10) = 0.25
print(f'{diplotype}: AS={score}, phenotype={cyp2d6_phenotype(score)}')  # IM, NOT UM

DPYD Activity Score (CPIC)

DPYD_2024_ACTIVITY = {
    'c.1905+1G>A': 0.0,    # *2A; splice donor
    'c.1679T>G': 0.0,      # *13; p.I560S
    'c.2846A>T': 0.5,      # p.D949V
    'HapB3': 0.5,          # c.1129-5923C>G linked with c.1236G>A
}


def dpyd_activity(variants):
    '''Compute DPYD gene activity score from observed variants.

    Sum the two lowest activities across the two alleles. CPIC dosing:
    - AS 2.0: full dose
    - AS 1.5: 50% start + TDM
    - AS 1.0: 50% start + TDM
    - AS 0.0: avoid
    '''
    activities = sorted([DPYD_2024_ACTIVITY.get(v, 1.0) for v in variants])
    return sum(activities[:2])


def dpyd_dosing(activity_score):
    if activity_score >= 1.99:
        return 'Full dose'
    if activity_score >= 1.0:
        return '50% starting dose + therapeutic drug monitoring'
    return 'Avoid fluoropyrimidines'

PharmGKB API for Drug-Gene Pair Lookup

import requests

PHARMGKB = 'https://api.pharmgkb.org/v1'


def clinical_annotation(gene_symbol):
    '''Query PharmGKB clinical annotations by gene.'''
    r = requests.get(f'{PHARMGKB}/data/clinicalAnnotation',
                     params={'view': 'base', 'location.genes.symbol': gene_symbol},
                     timeout=30)
    return r.json().get('data', [])


def cpic_guideline(gene_symbol):
    '''Query CPIC guidelines via PharmGKB.'''
    r = requests.get(f'{PHARMGKB}/data/guideline',
                     params={'view': 'base', 'relatedGenes.symbol': gene_symbol, 'source': 'CPIC'},
                     timeout=30)
    return r.json().get('data', [])

Per-Operation Failure Modes

*1. 4xN -> "Ultrarapid Metabolizer"

• Trigger: Pipeline reports CYP2D6 *4xN as UM.
• Mechanism: *4 has activity 0; *4 x N = still 0. Only functional alleles (*1, *2, *35) become UM when amplified.
• Symptom: Patient labeled as needing dose reduction when they should be PM/IM.
• Fix: Look up per-allele activity BEFORE multiplying by N; *4xN = 0; AS depends entirely on the other allele.

2. Calling CYP2D6 from short-read without SV-aware tool

• Trigger: Use GATK + PharmCAT only on CYP2D6.
• Mechanism: 97%+ CYP2D6/CYP2D7 identity; SVs (deletion, duplications, hybrids) silently miscalled.
• Symptom: ~10-18% of samples miscalled (Twesigomwe 2020); concentrated in samples with SVs.
• Fix: Add Cyrius (or StellarPGx) for CYP2D6; pass outside calls to PharmCAT.

3. Pre-2020 *10 activity value

• Trigger: Use activity = 0.5 for CYP2D6 *10.
• Mechanism: Caudle 2020 reset *10 from 0.5 to 0.25 based on metabolic-ratio evidence.
• Symptom: East-Asian samples mis-classified as NM (when should be IM).
• Fix: Use Caudle 2020 activity table; *10 = 0.25.

4. EUR-only DPYD panel

• Trigger: Pre-treat fluoropyrimidine using CPIC-core 4-variant panel only.
• Mechanism: 4-variant panel captures EUR DPD-deficient carriers but misses additional DPYD variants enriched in non-European populations (Offer 2014 identified ~30 such deleterious variants).
• Symptom: African-ancestry patients suffer severe toxicity despite "negative" PGx.
• Fix: Use extended panel for AFR cohorts; supplement with phenotype testing (uracil/dihydrouracil plasma ratio).

5. TPMT testing without NUDT15

• Trigger: Pre-treat thiopurines using TPMT-only PGx in East Asian patient.
• Mechanism: NUDT15 *3 (9.8% EAS, <1% EUR) is the dominant determinant in EAS.
• Symptom: EAS patients TPMT-wildtype suffer severe myelosuppression.
• Fix: Always test NUDT15 alongside TPMT; apply Maillard 2026 compound-IM rules.

6. HLA-B*57 -> "abacavir risk" (4-field underspecified)

• Trigger: Screen reports "B*57 present" as contraindication.
• Mechanism: B57:01 (HSS risk), B57:02, B*57:03 (no HSS risk).
• Symptom: False contraindication; patient denied effective therapy.
• Fix: Report 4-field; B*57:01 specifically.

*7. CYP3A5 3 / non-expresser confusion

• Trigger: Apply "CYP3A5 normal metabolizer" to *3/*3 in tacrolimus dosing.
• Mechanism: *3/*3 are NON-EXPRESSERS (most common state in non-AFR); expressers (any *1) need 1.5-2x higher dose.
• Symptom: Tacrolimus over-dosing in expressers; under-dosing in non-expressers.
• Fix: Apply CPIC 2015 (Birdwell) tacrolimus dosing; flag expresser status.

8. Activity-based vs allele-based confusion

• Trigger: Sum activities across substrate-non-specific assumption for *17.
• Mechanism: CYP2D6 *17 shows substrate-dependent activity (reduced for some substrates, near-normal for others).
• Symptom: Substrate-specific dose recommendations applied generically.
• Fix: Use substrate-specific guidance where available; flag *17 in AFR cohorts.

Reconciliation: When Tools Disagree

Pattern	Likely cause	Action
Cyrius vs Aldy CYP2D6 disagree	SV-rich sample; Aldy less accurate	Trust Cyrius
PharmCAT vs CPIC website disagree on phenotype	PharmCAT version lag or *10 activity value drift	Update PharmCAT to current release
CPIC vs DPWG dosing differ	Independent guideline bodies	Cite both; use jurisdiction-appropriate one
Patient phenotype doesn't match genotype	Drug-drug interaction; clearance physiology; non-pharmacogenetic factor	Consider phenoconversion; clinical reassessment
TPMT-only test vs IM phenotype	Missed NUDT15 in EAS	Re-test with NUDT15
*4xN reported as UM	Tool bug	Use SV-aware tool and Caudle 2020 activity table
HLA-B*57 reported without 4-field	Insufficient resolution	Re-type at 4-field minimum

Quantitative Thresholds and Conventions