THERAPEUTICS EXHIBIT

Fragle: Affordable AI-Powered Cancer Monitoring


01 Fragle

Detecting cancer relapse months earlier and at a fraction of the cost 

Current cancer monitoring methods are limited and they typically detect relapses only after tumours have grown large enough to be visible. They may also cost thousands of dollars per test, making them impractical for frequent use. 

Fragle, developed by A*STAR Genome Institute of Singapore, offers a practical alternative. Fragle uses deep learning to analyse DNA fragmentlength patterns in plasma (fragmentomics) to quantify the fraction of circulating tumour DNA (ctDNA). It works with ultra-low-pass whole-genome sequencing or with targeted panels already used in hospitals, returning results in under a minute.   

Validated by a study featured in Nature Biomedical Engineering (March 2025), Fragle can  measure ctDNA fractions as low as 1%.  The National Cancer Centre Singapore has an ongoing study as part of this validation, where a cohort of over 100 lung cancer patients are monitored every two months during therapy to quantify ctDNA dynamics and detect relapse earlier than routine imaging. 

By lowering costs and simplifying workflows, Fragle makes ctDNA analysis practical for routine care, enabling earlier detection of relapse, timelier treatment adjustments, and more equitable access to personalised oncology.   

Holistic Wound Care: Multiplexed Sensor × Product Ten (PTEN) Hydrogel

02 PTEN

Smarter monitoring and advanced treatment for chronic wound management

Chronic wounds affect millions worldwide and cost healthcare systems billions each year. They remain difficult to manage, often due to slow diagnosis and poor healing responses. Two Singapore-developed innovations are paving the way for better care.   

The Multiplexed Wound Sensor Patch, developed by A*STAR Institute of Materials Research and Engineering in partnership with National University of Singapore (NUS), is a low-cost disposable patch that tracks multiple infection and inflammation biomarkers at the wound site. Using a colorimetric sensing design with mobile imaging and NUS-developed algorithms, it provides a reliable bedside readout in under 15 minutes. This rapid, quantitative tool enables clinicians to monitor wounds in real time and intervene earlier.   

The Product Ten (PTEN) Hydrogel, codeveloped by A*STAR Skin Research Labs and Nanyang Technological University, is a proprietary formulation enriched with antioxidants to improve the wound environment. By promoting vascularisation, reducing inflammation and supporting tissue repair, it addresses the biological barriers that prevent healing. Spun off under Argonaute Lifesciences Pte Ltd, PTEN demonstrates how deep-tech research can be translated into innovative healthcare solutions.

Restoring the Skin Barrier: A Novel Biogenic Amine Technology


Targeting the root causes of skin fragility   

With age and environmental exposure, the skin gradually loses its ability to regenerate the barrier and retain moisture. This leads to thinning and fragility, which can result in serious health issues and worsens quality of life in the elderly. Existing treatments provide only short-term relief by creating a temporary replacement barrier.   

Scientists at A*STAR Skin Research Labs and the National Skin Centre have developed a breakthrough biogenic amine rebalancing technology that addresses this issue at the molecular level. Biogenic amines are critical to skin health, and their imbalance is linked to weakened barrier and poor repair. By restoring this balance, the technology stimulates barrier regeneration and strengthens skin from within.   

Laboratory studies on skin models show multiple benefits, including a thicker and stronger barrier, improved tissue repair and reduced pigmentation. Combined with moisturising actives, these formulations offer both hydration and regeneration in one. Developed using plant-based actives, this technology is being prepared for commercialisation.

SNPdrug3D: Mapping Genetic Variants to Drug Response in 3D


04 SNP Drug 3D

Turning genetic data into actionable insights for patient care   

SNPdrug3D is an AI-powered platform developed by A*STAR Bioinformatics Institute (A*STAR BII) in partnership with Temus, an industry software solutions company, under the joint A*STAR BII–Temus Lab initiative. It addresses a critical challenge in precision medicine: understanding how small DNA changes, known as genetic variants, influence a patient’s response to drugs.   

These genetic variants play a key role in treatment outcomes, yet robust tools to assess drug–variant interactions at scale have been lacking. SNPdrug3D fills this gap by using three-dimensional structural models to show how variants affect drug binding in proteins.   

The platform is the largest of its kind. It analyses 70 million protein-altering variants across more than 200,000 protein structures (both experimental and AI-predicted) and nearly 1,800 drugs, generating over 4 million variant–drug mappings. This breadth enables clinicians and researchers to uncover interactions that might otherwise remain hidden. Experimental validation with drug binding assays has confirmed SNPdrug3D’s accuracy, showing that variants located near binding sites are significantly more destabilising.   

SNPdrug3D is already in clinical use in Singapore. Oncologists and specialists are applying it to interpret sequencing data from patients with cancer, eye disorders, and autoimmune diseases. Beyond individual cases, it also incorporates population-level data from Singapore, supporting patient stratification and providing deeper insights into drug responses at a national scale.   

In addition to browsing variant–drug mapping data, SNPdrug3D can perform pharmacogenetic assessments of personal genomes using genetic files as input. This allows clinicians to pinpoint drug-response variants that may disrupt binding sites and influence treatment decisions at the individual level.

By enabling drug-response insights at both the patient and population level, SNPdrug3D supports more data-driven and personalised treatment strategies, advancing the vision of precision medicine. The platform is also crosscompatible across different environments (for example, as a Python package in Jupyter Lab) and has been deployed on Illumina’s commercial cloud platform for genomic data analysis.

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