logo
PROVIDERS
LABS
CROs
PAYORS
PATIENTS
ABOUT US
Schedule a Demo
Contact Us
scope image
Overview

PGxAI CancerRisk

AI-powered genetic insights for hereditary cancer risk and clinical decision support
Schedule a Demo Contact us
Overview
PGxAI CancerRisk is a clinical-grade genetic test that identifies pathogenic and likely pathogenic variants associated with hereditary cancer syndromes. Based on ACMG and ClinGen guidelines, it provides clinicians with actionable insights for surveillance, early intervention, and family planning.
•
Detects clinically significant monogenic variants (ACMG Tier 1–3 genes)
•
Covers over 30 cancer-associated genes including BRCA1/2, TP53, MLH1, MSH2, and others
•
AI-powered report with interpretation, recommendations, and variant classification
Report Preview
Concise, One-Page Summary of Key Cancer Risk Markers
report example
Genes Covered
TP53
Associated with Li-Fraumeni syndrome; linked to early-onset multiple cancers including breast, brain, and sarcomas
BRCA1 / BRCA2
Major genes involved in hereditary breast and ovarian cancer syndromes
CMSH2, MLH1, MSH6, PMS2
Core mismatch repair genes implicated in Lynch syndrome and elevated colorectal, endometrial, and other cancer risks
APC
Associated with familial adenomatous polyposis and early-onset colorectal cancer
Use & Evidence
Who It’s For
•
Clinical geneticists and oncologists
•
Preventive medicine and women’s health practices
•
Reproductive health and fertility specialists
•
At-risk individuals with family history of cancer
•
Cancer survivors and their relatives
Scientific Basis
Genetic testing plays a critical role in identifying individuals with inherited cancer risk. Modern genomic tools now allow precise detection of pathogenic variants across key susceptibility genes, enabling early surveillance, personalized risk reduction strategies, and informed decision-making for patients and providers. PGxAI CancerRisk follows ACMG/AMP guidelines for variant classification and includes genes with strong evidence for clinical actionability. Pathogenicity is determined using ClinVar, gnomAD, functional studies, and peer-reviewed literature.