Renata Priscila Barros de Menezes

Pharmacist, Master, and Ph.D. in Natural and Synthetic Bioactive Products from the Federal University of Paraíba, with a specialization in Medicinal Chemistry and a postdoctoral fellowship at the same institution. She has a strong background and experience in Cheminformatics, applying computational modeling techniques for drug discovery. Her trajectory includes the development of predictive models based on machine learning, molecular docking, molecular dynamics, and ADMET studies, exploring interactions between bioactive compounds and molecular targets of pharmacological interest. During her undergraduate studies in General Pharmacy at the State University of Paraíba, she worked in toxicology care centers and participated in research projects on natural products with antimicrobial activity. In her masters and doctoral research, she specialized in computational tools for structural analysis of bioactive compounds, focusing on the optimization of drug candidates. In her postdoctoral studies, she expanded her research to advanced strategies in virtual screening, QSAR (Quantitative Structure-Activity Relationship), and molecular interaction networks, contributing to the identification of promising molecules against various diseases. Currently, she is enhancing her data analysis skills through the IBM Professional Data Analyst Certification (Coursera), developing practical expertise in Python, SQL, and data visualization, strengthening her ability to integrate artificial intelligence and data science into Cheminformatics. She has over 40 published articles in international journals and book chapters, with expertise in scientific communication and the translation of complex data into strategic insights. Passionate about innovation in Computational Medicinal Chemistry, she seeks to apply Artificial Intelligence and Cheminformatics approaches to accelerate drug discovery. (Source: Lattes Curriculum)