SystemOnline
WorkflowsClopidogrel + Warfarin + Simvastatin
Reference PopulationsAFR EUR EAS SAS AMR
1000G SamplesPhase-3 (n=2504)
Decision EngineDeterministic PGx
Evidence LayerV1–V10 / R1–R12 / U1–U9
Export StackCSV PDF FHIR
Data ModeResearch Simulation
GovernanceAudit Enabled
Engineanukriti-pgx-core==0.2.1
SystemOnline
WorkflowsClopidogrel + Warfarin + Simvastatin
Reference PopulationsAFR EUR EAS SAS AMR
1000G SamplesPhase-3 (n=2504)
Decision EngineDeterministic PGx
Evidence LayerV1–V10 / R1–R12 / U1–U9
Export StackCSV PDF FHIR
Data ModeResearch Simulation
GovernanceAudit Enabled
Engineanukriti-pgx-core==0.2.1
SystemOnline
WorkflowsClopidogrel + Warfarin + Simvastatin
Reference PopulationsAFR EUR EAS SAS AMR
1000G SamplesPhase-3 (n=2504)
Decision EngineDeterministic PGx
Evidence LayerV1–V10 / R1–R12 / U1–U9
Export StackCSV PDF FHIR
Data ModeResearch Simulation
GovernanceAudit Enabled
Engineanukriti-pgx-core==0.2.1
SystemOnline
WorkflowsClopidogrel + Warfarin + Simvastatin
Reference PopulationsAFR EUR EAS SAS AMR
1000G SamplesPhase-3 (n=2504)
Decision EngineDeterministic PGx
Evidence LayerV1–V10 / R1–R12 / U1–U9
Export StackCSV PDF FHIR
Data ModeResearch Simulation
GovernanceAudit Enabled
Engineanukriti-pgx-core==0.2.1
Anukriti logo

Anukriti

emoji_eventsAWS AIdeas Winner — Top 20Live

Anukriti

Population-Aware Pharmacogenomics Intelligence

Anukriti helps biotech and research teams evaluate pharmacogenomic risk across diverse populations before expensive trial decisions. Our deterministic PGx engine is auditable by design, and AI is used for explanation, not medical decision-making.

Now live: three shipped workflows (clopidogrel, warfarin, simvastatin), real 1000 Genomes phase-3 sample mode (n=2,504 across AFR/EUR/EAS/SAS/AMR), and a multi-agent Evidence Sufficiency Layer that names every refusal with a specific rule id.

Selected as 1 of 20 AWS AIdeas winners from 10,000+ global submissions across 115 countries.

Try the Live Demoarrow_right_alt
Diagnostic Terminal — LOCALHOST:9000
settings
>

ANUKRITI PLATFORM INITIALIZED...

>

LOADING POPULATION-AWARE WORKFLOWS...

>

DETERMINISTIC PGX ENGINE READY

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Target IdentifiedAX-4022 [Synthetic Phenotype]
In SilicoC12H18N2O2
Structure ID: AX-4022Rendering Chemical Potential...
3D-MODEL LIVE
Live Analysis Buffer
Workflows Live3 shipped
1000G Samples2,504 phase-3
Call Statuses3 states
Evidence LayerV1–V10 / R1–R12
Export ContractTrial-ready rows

Reference Cohorts

AFR EUR EAS SAS AMR

Global Mix

Decision Path

Deterministic

Auditable

Reviewer Flow

< 100ms warm

End-to-end

Platform Approach

Why Anukriti, Why This Approach

We focus on deterministic pharmacogenomic interpretation first, then layer AI explanations for accessibility. This architecture enables auditable decision pathways while helping teams explore population-level risk differences before costly trial-stage changes.

Validation Snapshot
IWPC warfarin cohort · n=5,700
low → 45.80 → standard → 33.66 → high → 21.58 mg/wk

Engine-predicted risk tier vs. actual prescribed dose. Monotonic gradient, ~24 mg/wk delta. Of 467 patients flagged for dose-down but prescribed ≥ cohort median, 99 (21%) had INR outside 2.0–3.0 target — empirical confirmation the dose was wrong.

PGX
anukriti-pgx-core 0.2.1 vs IWPC
Klein et al. NEJM 2009 · CPIC 2017
Deep dive
Powered by Industry Standard Architecture
🧬1000 Genomes
🧪ChEMBL
⚙️RDKit
📚CPIC / PharmVar
☁️Bedrock / Nova
Recognition & Community Validation

AWS AIdeas Winner (Top 20)

Anukriti was selected as 1 of 20 winners from 10,000+ ideas submitted across 115 countries and featured on AWS Builder Center for its population-aware pharmacogenomics simulation approach.

Read AnnouncementWatch Demo
shield_check

Research Simulation Guardrails

Anukriti is a research and education platform, not a clinical diagnostic system. Deterministic outputs remain auditable, AI-generated text is explanatory, and users should not treat simulation output as medical advice.

Now Live

What's shipped today

science
3 workflows

Clopidogrel/CYP2C19, Warfarin/CYP2C9+VKORC1, Simvastatin/SLCO1B1 — all CPIC level A, all auditable.

diversity_3
2,504 real samples

1000 Genomes phase-3 cohort across 5 superpopulations. Pre-resolved genotypes from AWS Open Data.

rule
Named-rule refusals

Evidence Sufficiency Layer: 12 R-rules, 10 V-rules, 9 U-rules. Every refused recommendation cites the rule id.

fact_check
IWPC validated · n=5,700

Engine produces monotonic dose gradients (low 45.8 → high 21.6 mg/wk) on the IWPC warfarin cohort. 99 of 467 high-risk patients confirmed by INR data. Companion CPIC table audit ships with open findings disclosed — VKORC1 100%, CYP2C9 has v0.2.1 bugs scheduled for v0.3.0 fix.

Validation deep dive

Case Studies & Evidence

Why Population-Aware PGx Matters

Anukriti is built on publicly available pharmacogenomics evidence and real-world case studies that show how genotype frequency differences can materially affect drug safety and efficacy outcomes.

Clopidogrel

CYP2C19

biotech

Poor metabolizer prevalence varies sharply across populations, which can change antiplatelet response and event risk.

PM prevalence: ~2% in many European cohorts vs much higher in parts of East Asia/Oceania.

Source: NCBI Medical Genetics Summaryopen_in_new

Warfarin

CYP2C9 + VKORC1

biotech

Dose requirements are strongly affected by PGx variation and can differ significantly across ancestry groups.

Multi-ethnic cohorts report meaningful dose separation linked to CYP2C9 and VKORC1 variants.

Source: NIH/PMC population dosing studyopen_in_new

Carbamazepine

HLA-B*15:02

biotech

Severe hypersensitivity risk clusters in specific populations, illustrating why representation matters in early safety planning.

Strong association of HLA-B*15:02 with SJS/TEN in several Asian cohorts.

Source: FDA recommendation backgroundopen_in_new

Codeine

CYP2D6

biotech

Ultra-rapid and poor metabolizer phenotypes can both create safety or efficacy failures depending on genotype distribution.

Marked global variability in CYP2D6 phenotype frequencies.

Source: NCBI Medical Genetics Summaryopen_in_new

Evidence Links

Research simulation only. Not intended for diagnosis, treatment, or prescribing decisions.

Technical Roadmap

From research prototype to trusted trial intelligence platform

Phase 1Completed

Deterministic Trial Wedge

Three shipped workflows — clopidogrel (CYP2C19), warfarin (CYP2C9 + VKORC1 + CYP4F2), and simvastatin (SLCO1B1) — with auditable call statuses (called / cannot_call / insufficient_data) and CPIC + PharmVar provenance.

Live
Phase 2Completed

Reviewer Trust Layer

Benchmarks, confidence calibration, reproducibility packs, evidence mapping, reviewer reports. Evidence Sufficiency Layer with named refusals: 12 R-rules (decision), 10 V-rules (verdict), 9 U-rules (uncertainty), and 3 bias-detection kinds — every refusal cites a specific rule id.

Live
Phase 3In Progress

Pilot Operations

Production API on Azure Container Apps + MongoDB Atlas. Public simulation surface (zero-auth demo). Real 1000 Genomes phase-3 sample mode — pre-resolved genotypes from the AWS Open Data bucket. Per-cohort outcome distributions and shareable run permalinks.

Live
Phase 4In Progress

Clinical-Grade Validation

PharmCAT concordance benchmark, BCHE / Vysya founder-community wedge (Kerdoncuff 2025), CYP2D6 CNV calling via Cyrius, full AFR-specific evidence pack. Scientific partnership outreach (PharmVar, LASI-DAD, GenomeIndia) underway.

Next