Professor School of Innovation and Entrepreneurship
Dr. David (Dongliang) Ge is Professor at Southern University of Science and Technology (SUSTech). He is also Chairman of SUSTech-Apostle joint venture, as well as Chairman, CEO and co-Founder of Apostle Inc (http://apostlebio.com), a Silicon-Valley-based biotechnology company focusing on liquid biopsy technologies.
- Named by Phacilitate as one of the "Top 50 Most Influential People in Big Data" in 2015
- Named by the Genome Technology magazine as the “Rising Stars” in 2009
- 20 years of experience in bioinformatics, genomics, and biomarker
- Published 5 articles in Nature and 1 in Science; work in total receiving over 18,000 citations.
- Contributed to the bioinformatics and biomarker section of the U.S. FDA Guidelines for Industry: Enrichment Strategies; Chronic HCV infection
- Patent inventor of genomic biomarker products: Quest AccuType® IL28B，LabCorp 480630
- Contributed to the clinical development of Sofosbuvir, a world-leading drug
- Member of U.S. NIH NHGRI Special Emphasis Panel
- CEO and co-founder of Apostle Inc, a Silicon-Valley-based biotechnology company developing liquid biopsy technologies.
- A BioSpace top 20 Biotech Startups 2018
- A Stanford University StartX company 2018
- President, BioSciKin/Simcere Diagnostics Co., Ltd.; led a 200-people company; oversee the investment in 3 of the "50 Smartest Companies 2016 - MIT Technology Review", and 2 of the 3 European Biotech Unicorns in 2016, with a focus on bioinformatics, genomics, and precision medicine
- Former Director of Bioinformatics, Gilead Sciences, Inc.; Head of Bioinformatics Department
- Former Assistant Professor of Medicine, Biostatistics and Bioinformatics, Duke University School of Medicine
- Author of a series of software tools for next-generation sequencing studies; Experienced JAVA and R programmer
Educational and Training Background
- Duke University, USA: Postdoctoral fellow 2006- 2008
- Bioinformatics and Biostatistics
- Next generation sequencing studies; Genome-wide association studies
- Precision Medicine; Pharmacogenomics
- Clinical trial
- Medical College of Georgia, USA: Postdoctoral fellow 2005- 2006
- Structural Equation Modeling
- Genomics; Pharmacogenomics
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. 2004.
- PhD. Biostatistics and Genetic Epidemiology/Bioinformatics.
- National recommendation
- Shanghai Medical University (currently Fudan University School of Medicine), Shanghai, China. 1999.
- First Prize, the National People Scholarship
The research direction of Professor Ge's team is to develop and apply revolutionary new genomic detection technology and computer analysis technology, so as to fundamentally solve some key challenges in the clinical application of genomic detection, so as to improve the global human health. The future development plan of scientific research can be divided into three levels:
(1) a number of new chemical and biochemical materials and methods are used to achieve the high-efficiency enrichment, preservation, extraction and targeted operation of trace genetic substances in human body fluids such as plasma, serum, saliva, urine and cerebrospinal fluid. As a platform technology, it can be applied in a wide range of genetic material analysis fields.
(2) the cancer big data platform and artificial intelligence machine learning technology ensure that the deep machine learning from high-quality cancer genome big data is accurate and efficient, and effectively solve the problem of high heterogeneity of tumor genome. Based on artificial intelligence technology, we can accurately identify circulating tumor DNA in the samples, and then realize the diagnosis of early cancer.
(3) organic integration of the above chemical and biochemical materials and methods with artificial intelligence machine learning technology The purpose is to achieve the accurate and efficient enrichment of tumor DNA fragments in the samples, and analyze these DNA fragments accurately for the diagnosis of early cancer. After fusion, compared with the traditional plasma free DNA enrichment technology, this technology can specifically enrich tumor DNA, remove the background noise of DNA fragments from normal tissues, improve the accuracy of tumor DNA analysis, reduce the sequencing depth and cost, and make the early diagnosis of cancer with high accuracy and low cost possible.