Dr. Xiang-Qun (Sean) Xie is a tenured full Professor of Pharmaceutical Sciences and the Principal Investigator of an integrated AI Data Science Computing and Experimental Medicinal ChemBio Lab at the Univ of Pittsburgh School of Pharmacy/Drug Discovery Institute since 2006. Dr Xie is also an Executive Committee Member/CoP of the UPitt AI Data Science Initiative (RDS@Pitt). His passion for innovation and excellence has propelled him to spearhead transformative initiatives. During his tenure as Associate Dean for Research Innovation and later Associate Dean for PharmacoAnalytics, Dr. Xie served as Director and PD/PI, leading the establishment of the NIH-funded P30 Center of Excellence for CDAR (www.cdarcenter.org/about-us/contact-us/) in 2014, a collaborative Big Data and AI computing initiative of PITT with Carnegie Mellon University (CMU). CDAR has fostered groundbreaking AI-driven data science research, advancing interdisciplinary collaboration and innovation across Pittsburgh and beyond. Subsequently, Dr Sean Xie, as a Founding Director, launched the nation’s Pharmacometrics & Systems Pharmacology (PSP) PharmacoAnalytics AI data science program in 2017, equipping students with cutting-edge skills and knowledge in AI data science and drug discovery for future innovation. Nationally, Dr. Xie's expertise and leadership have earned him the esteemed role of Charter Member of the US FDA Science Board. He is a dedicated member of the Editorial Board of the AAPS Journal. He serves on the Editorial Review Board of the NIH Directors’ New Innovator Award Program and the NIH major center grants BTOD and NIH P Series - Artificial Intelligence and Technology Collaboratory. In recognition of his scientific impact, Dr. Xie was recently named Editor-in-Chief of AAPS Adv Book Series | Springer Nature. Internationally, Dr Xie’s insight and expertise have been sought after as an expert reviewer for numerous international research foundations, including the UK MRC Foundation, the Wellcome Trust, the Netherlands Organization for Scientific Research Council, the Austrian Science Fund (FWF), and the CNSF. Dr. Xie is also an Associated Partner of the European Research Executive Agency (REA): Targeting Circadian Clock Dysfunction in Alzheimer’s Disease (TClock4AD), Marie Skłodowska-Curie Doctoral Networks. Dr. Xie has previously held honorary professorships at prestigious institutions, including a Scholar Honorary Professor of the Chinese Academy of Medical Sciences & Peking Union Medical College, further underscoring his global influence. His laboratory excels in developing disease-specific chemical genomics knowledgebases, Alzplatform, Deep-MGM, and drug TargetHunter®, which attract over 1.9 million online users. His groundbreaking research integrates GPU ML/DL Generative AI computing to revolutionize cryo-EM structure-based pharmaceutical science drug design and discovery, as exemplified by his over 250 publications and numerous patents in high-impact journals, such as Cell, Nature Comm, PNAS, Leukemia, Scientific Reports, AAPS J, JMC, Kidney International and Cells, etc). Among his most impactful translational research accomplishments is the discovery of pioneering, first-in-class drug technologies. He successfully advance his novel oncology drug platform, and recently received FDA IND approval - “Study May Proceed” human clinical trials. His broad scientific contributions have been recognized with the prestigious AAPS Award for Outstanding Research Achievement. ([email protected], 832-755-1268). SELECTED PUBLICATIONS: 1) Bian Y and Xie X-Q*. AI Deep Learning Molecular Generative Modeling of Scaffold-Focused Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries. Cells, 2022 PMID: 35269537 2) Hou, T., Bian, Y., McGuire, T., Xie, X.-Q.* “Integrated multi-class classification and prediction of GPCRs allosteric modulators by machine learning intelligence.” Biomolecules 2021, PMID:34208096 3) Jing Y, Hu Z, Fan P, Xue Y, Tarter RE, Kirisci L, Wang J, Vanyukov M, Ralph ET and Xie X-Q*. Analysis of Substance Use and Its Outcomes by Machine Learning I. Childhood Evaluation of Liability to Substance Use Disorder. Drug and Alcohol Dependence. PMID: 31839402. Analysis of Substance Use and Its Outcomes by Machine Learning: II. Derivation and Prediction of the Trajectory of Substance Use Severity. Drug and Alcohol Dependence. 2020, 31615693. 4) Xing C, Zhuang Y, Xu T, Feng Z, Xu E, Zhang C and Xie XQ* Cryo-EM Structure of Human Cannabinoid Receptor CB2-Gi Signaling Complex. Cell 2020,180(4):645-654, PMID:32004460. 5) Gao Y, Yang P, Shen HM, Yu H, Xie ZJ, … Cheng T* and Xie XQ* “Small-molecule inhibitors targeting INK4 protein p18INK4C enhance ex vivo expansion of hematopoietic stem cells”, Nature Communications, 2015, 6:6328. PMID: 25692908; 6) "Targeted inhibition of the type 2 cannabinoid receptor is a novel approach to reduce renal fibrosis." Kidney Int. 2018, PMID: 30093080