NSCC’s supercomputer help analyse the Asian skin microbiome in order to develop products to improve skin treatments and maintain skin health.

Our skin harbours a complex microbial community that includes bacteria, fungi and viruses. Many of these organisms play critical roles in maintaining skin health and are the cause of many inflammatory skin diseases such as atopic dermatitis and psoriasis, dandruff and seborrheic dermatitis, as well as malodour and diaper rash. Therefore, it is important to understand the microbial composition to develop better skin treatments and improve skin health.

However, technological identification and product development face substantial challenges due to a lack of foundational knowledge and tools. These challenges include the definition of what constitutes healthy Asian skin microbiome; adequate knowledge of its functional role in skin inflammation/homeostasis to enable rational material identification and product design; and how the efficacy of treatments can be demonstrated to support IP disclosures and claims.

A team of researchers at the Asian Skin Microbiome Programme (ASMP) at A*STAR aims to address these critical unmet needs by delivering an integrated platform of assets and technologies which generate new functional understanding of the skin microbiome and can be flexibly employed by companies for their research and clinical needs.

The team is leveraging on NSCC’s supercomputing resources to establish the skin microbiome signatures of the Asian population and to innovate technologies
to investigate this data in order to enable rational modulation of skin microbes and provide opportunities for the development of clinical interventions.

To find out more about the NSCC’s HPC resources and how you can tap on them, please contact [email protected].

 

NSCC NewsBytes January 2021

Other Case Studies

Increasing the effectiveness of antibiotics by analysing antibiotic resistance using supercomputers

Researchers from NTU are utilising NSCC’s supercomputing resources to understand the permeation of antibiotics in order to design new novel antibiotics. Antibiotic resistance is...

Using Machine Learning to identify and improve protein-ligand binding affinity predictions

Researchers from NTU are utilising NSCC’s supercomputing resources to improve the performance of learning models in molecular data analysis. AI is expected to play an...

A quieter way to fly – Reducing jet engine noise through HPC research

Researchers from NUS are harnessing the power of supercomputing to understand the mechanism of noise generated by jet engines to reduce the impact of noise emission on the...