Laboratory of Data Discovery for Health (D²4H)

About Laboratory of Data Discovery for Health (D²4H)

As innovation continues to flourish in the area of healthcare technology, there is a vacant niche for the careful and proper curation of data resources in order to bridge the gap in developing novel, deep analytics that can stand up to scientific scrutiny. The nascent Laboratory of Data Discovery for Health (D²4H) is set to fill this gap. It aims to gather and curate massive, unique data resources and to develop new, deep, frontier analytics in protecting global public health and improving individual healthcare through precision medicine. 


Professor Ian WONG leads one of the research programmes of D24H, which focus on AI and Pharmaceuticals in Non-Communicable Diseases (NCDs).

The programme will be led by world-leading experts with proven track-record in application of big data in pharmaceutical development and research. Our programme advocates “improving health and improving wealth” in HK. We will use the unique healthcare big databases to support pharmaceutical research and development and more importantly improve health of our citizens in HK and beyond. In order to deliver such ambitious programme, our unique research team have world-leading expertise and track record in using big data analytics, artificial intelligence (AI) and repurposing pharmaceutical products, which has led to changes in clinical practice and licenced medicines in Europe.

Research team
Lead Scientist:

Professor Ian WONG

Head & Professor

Ian Wong
Research team core members:

Dr. Esther W. Y. CHAN

Associate Professor

Esther Chan


Associate Professor


Dr. Shirley X. LI

Assistant Professor

Shirley Li

Dr. Eric Y. F. WAN

Assistant Professor

Dr. Eric Y.F. WAN

Dr. Celine S. L. CHUI

Assistant Professor

Chui Sze Ling Celine_2017

Dr. Francisco T. T. LAI

Research Assistant Professor

Dr. Francisco T.T. Lai

Vision and Mission of the research programme “AI and pharmaceuticals in non-communicable diseases (NCDs)”

In an era of global emergent healthcare big databases, real-world evidence is playing an increasingly important role in clinical and pharmaceutical research, complementary to classic trials. The 2018 Chief Executive Policy Address confirmed the government’s commitment to improving the access and use of big data held in trust by government and statutory agencies. The electronic healthcare record system managed by the Hospital Authority (HA) is such a powerful database for clinical research. Currently, it contains data from 11 million unique patients. The characteristics of the database include wide-coverage, de-identification for privacy protection, high coding accuracy and centralised information. Its value is widely recognised, given innovative efforts by the present programme team, which opens up the immense potential for this to be developed into a world-class, Asia-leading research database.


This programme aims to use unique healthcare big databases and cutting-edge big data analytics – artificial intelligence (AI) to improve the health and wealth of HK. In this programme we will further mine and fully utilise the HA database by conducting four inter-linked and AI-technology driven projects in pharmaceuticals in NCDs: 1) evaluating medication effectiveness in real-life settings, 2) enhancing medication safety surveillance.

Research Areas and Focus

The research programme comprised of two main projects: 

Project 1: Evaluation of post-marketing treatment outcomes for the major non-communicable diseases (NCDs)

Aim:  To evaluate post-marketing treatment outcomes for the major NCDs

Research team:

PI: ICK Wong (HKU); Co-PI: EWY Chan (HKU), CL Cheung (HKU), G Rees (UCL), L Wei (UCL), L Smeeth (LSHTM), I Douglas (LSHTM) , WCY Lau (UCL), AYS Wong (LSHTM), M Jit (LSHTM), CSL Chui (HKU), X Li (HKU)
Project 2: AI-enabled pharmacovigilance (PV) at the population level

Aim: To undertake AI-enabled PV at the population level

Research team:

PI: ICK Wong (HKU); Co-PI: EWY Chan (HKU), CL Cheung (HKU), G Rees (UCL), L Wei (UCL), L Smeeth (LSHTM), I Douglas (LSHTM), WCY Lau (UCL), AYS Wong (LSHTM), M Jit (LSHTM), CSL Chui (HKU), X Li (HKU)

D²4H Home Page

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