SJMC & AstraZeneca Introduce Malaysia’s First AI-Assisted Breast Cancer Diagnostic Tool

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Subang Jaya Medical Centre (SJMC), in partnership with AstraZeneca, has launched Malaysia's first computational pathology solution that uses AI imaging to review digitised tissue samples for breast cancer testing

This represents a major milestone in modernising pathology services and integrating digital health tools into everyday medical practice across the country.

The initiative addresses the critical need for accurate and consistent diagnostics amid the growing incidence of breast cancer.

Precise testing for Human Epidermal Growth Factor Receptor 2 (HER2) has become increasingly crucial for determining appropriate treatment pathways, particularly as therapies emerge for low and ultralow HER2 levels.

HER2 protein in breast cancer is a receptor on cell surfaces that normally manages cell growth, but when overproduced, it causes fast and aggressive tumor growth.

Measuring HER2 protein levels under a microscope can be challenging, as subtle visual differences often lead to scoring variations among pathologists.

By combining digital pathology with AI-driven analysis, the new tool helps pathologists evaluate HER2 protein expression on scanned glass slides using Mindpeak HER2 AI software

The solution aims to improve scoring consistency and accuracy while preserving the role of certified medical professionals, ensuring all final diagnostic decisions remain under the direct supervision of qualified pathologists.

SJMC pathologists participated in multinational observational studies to validate the AI technology before its clinical rollout. The system integrates into the hospital's existing digital pathology setup, where tissue samples are routinely scanned into high-resolution digital slides.

Scientific studies show that AI-assisted scoring of digital breast cancer samples significantly improves agreement with reference standards and reduces misclassification errors between HER2 ultralow and HER2 null cases.

Research also suggests that computational pathology helps medical teams manage growing case volumes while delivering faster, reliable results for treatment planning.

Here's how it can help patients

AI-assisted computational pathology improves patient care by making breast cancer diagnoses more precise and consistent.

By reducing the chance of subtle scoring variations, the technology ensures that patients with low or ultralow HER2 levels are accurately identified.

This precision lets oncologists tailor treatment plans with greater confidence, enabling earlier access to suitable targeted therapies.

The streamlined digital workflow also enables faster laboratory turnarounds, giving patients and their families timely answers during critical care decisions.