Tianhua Wang
About Tianhua Wang
Tianhua Wang is an Associate Director of Statistics at Nektar Therapeutics, with a strong background in statistical programming and expertise in biomarker assay development. He has held various positions in the pharmaceutical industry and academia, including roles at Celgene, FDA, and Bristol-Myers Squibb.
Current Role at Nektar Therapeutics
Tianhua Wang serves as the Associate Director of Statistics at Nektar Therapeutics, a position he has held since 2021. In this role, he is responsible for overseeing statistical methodologies and analyses that support the company's research and development efforts. His expertise contributes to the advancement of clinical trials and the evaluation of therapeutic efficacy.
Previous Experience at Celgene
Prior to his current role, Tianhua Wang worked at Celgene as a Principal Statistician from 2019 to 2021. During his tenure, he contributed to statistical analysis and design for clinical trials, enhancing the company's capabilities in oncology research. His work involved collaboration with cross-functional teams to ensure data integrity and compliance with regulatory standards.
Educational Background in Statistics
Tianhua Wang earned his Doctor of Philosophy (Ph.D.) in Statistics from the University of Missouri-Columbia, where he studied from 2008 to 2013. His academic training provided a solid foundation in statistical theory and applications, which he has applied throughout his professional career. He also holds a Bachelor of Arts in Mathematics and Statistics from the University of Science and Technology of China, completed in 2008.
Expertise in Statistical Programming
Tianhua Wang is proficient in statistical programming languages such as R/Splus and holds a certification in SAS/Base. His programming skills enable him to conduct complex data analyses and develop statistical models. He also has experience with Bioconductor, which supports the analysis of high-throughput genomic data, further enhancing his analytical capabilities.
Specialization in Clinical Statistics
Tianhua Wang specializes in Bayesian Analysis and Machine Learning, both of which are critical for advanced data analysis in clinical trials. His expertise extends to developing and validating biomarker assays, which play a significant role in personalized medicine approaches in oncology. Additionally, he has a strong background in statistical quality control and optimal experimental designs, ensuring the reliability and efficiency of clinical research.