Eshelman School Postdoc Wins Lush Prize for Artificial Intelligence Chemical Toxicity Research

January 22, 2019

Vinicius Alves

Vinicius Alves, a postdoctoral research associate at the UNC Eshelman School of Pharmacy Catalyst for Rare Diseases, is a recipient of the 2018 Lush Prize Young Researcher award.

The Lush Prize rewards international initiatives across science and campaigning that work to end or replace animal testing, particularly in the area of toxicology research, and is accompanied by a £10,000 grant.

Alves is developing an artificial intelligence-based web platform to assess the toxicity of mixtures present in major classes of industrial chemicals. He is one of four Young Researcher award winners from the United States and 13 worldwide winners and was honored at the Lush Prize Conference in Berlin last November.

“It is very exciting to see computational approaches being recognized by the scientific community as a practical solution for smarter decision-making,” Alves said. “We have been applying modern machine learning and data science techniques to accelerate the drug discovery and chemical safety assessment process, making it faster and more relevant to humans — and all without the use of animal testing.”

Alves earned his M.Sc. and Ph.D. in Pharmaceutical Sciences from the Federal University of Goias in Brazil. He studied at UNC-Chapel Hill as an undergraduate research fellow in 2012 and as a visiting Ph.D. student from 2015 to 2016 in Alexander Tropsha’s lab, before joining UNC Catalyst as a postdoctoral researcher in 2018.

UNC Catalyst is a research group focused on understanding and counteracting rare diseases. It creates high quality research tools to explore disease pathobiology, in order to accelerate the pace of drug discovery and help define options for therapeutic intervention. In collaboration with the Genetic Alliance and the Structural Genomics Consortium (SGC-UNC), UNC Catalyst employs open science principles in order to share knowledge freely and without restriction to other research communities.