Mahidol University powers drug discovery research with NVIDIA platform

Thailand’s new AI Center at Mahidol University (MU) is powering drug discovery research with the NVIDIA DGX A100 systems and the NVIDIA Clara platform.

Housed at the university’s Salaya campus, the centre will initially support projects from the Cluster of Excellence in AI-Based Medical Diagnosis, the Integrative Computational BioScience Center and the Artificial Intelligence-Integrated Drug Discovery Platform, from the Faculty of Information and Communication Technology, Faculty of Medicine Siriraj Hospital and Faculty of Pharmacy, respectively.

“We are targeting to have the platform support the end-to-end drug discovery process, using NVIDIA Clara Discovery for drug development, NVIDIA Clara Parabrickes for genomic analysis and Clara Imaging with ePAD and MONAI for radiology and pathology to innovate and accelerate our AI model creation and deployment,” said Dr Pattanasak Mongkolwat, Dean of the Faculty of ICT at Mahidol University.

The Mahidol University AI Center provides a conducive environment for researchers to collaborate and initiative new ideas and projects, and where MU students and researchers across disciplines can be trained on AI. It will bring researchers in Thailand’s university community together to work on disciplines such as computer science, engineering, life science, medicine, music for health, and social science and humanities.

Building on the university’s strengths in medicine and health sciences, it will further scientific knowledge and breakthroughs to support the United Nations’ sustainable development goals to make the world a better place.

As part of the Thailand AI University Consortium, the centre will collaborate on developing an automated framework for AI assisted annotation and AI federated learning in medical imaging solutions. This will allow an image annotation workstation to be integrated into clinical workflows to reduce disruption during annotation for deep learning purposes, while maintaining data integrity, data security and data anonymity.

The federated learning platform can be expanded and linked to partner institutions. AI models and training results can be shared without being hindered by institutional data sharing policies. Anonymisation mechanisms will be in place to automatically remove patient identifiable information and collect annotation data as structured data. Image data, along with corresponding annotation data, can be fed to a deep learning model for training and classifying.

“With the systems powering Mahidol University AI Center, researchers in the university and across Thailand will be able to accelerate research breakthroughs that benefit Thailand and the world,” said Dennis Ang, Director of Enterprise Business for SEA and ANZ at NVIDIA.