César de la Fuente is a Presidential Associate Professor at the University of Pennsylvania, where he leads the Machine Biology Group. He completed postdoctoral research at MIT and earned a PhD from the University of British Columbia (UBC). His research goal is to use the power of machines to accelerate discoveries in biology and medicine.
Notably, he pioneered the development of the first computer-designed antibiotic with efficacy in animal models, demonstrating the application of AI for antibiotic discovery and helping launch this emerging field. His lab is at the forefront of developing computational methods to mine the world’s biological information, leading to the identification of over a million new antimicrobial compounds. These efforts began by exploring the human proteome as a source of antibiotics for the first time.
His team was also the first to find therapeutic molecules in extinct organisms, launching the field of molecular de-extinction, which has already yielded preclinical antibiotic candidates such as neanderthalin, mammuthusin, and elephasin.
De la Fuente’s lab has expanded its antibiotic discovery efforts to explore microbial dark matter, identifying nearly one million new antibiotic molecules, which have been made freely available and open access to encourage global research collaboration. This work leveraged machine learning to analyze 63,410 metagenomes and 87,920 microbial genomes.
Additionally, by exploring thousands of human microbiomes, the team discovered new antimicrobial agents, including prevotellin-2 from the gut microbe Prevotella copri. Collectively, these efforts have reduced the time to identify preclinical antibiotic candidates from years to just a few hours.
Further advances include:
Reprogramming venoms into antimicrobials
Developing autonomous nanorobots to treat infections
Creating resistance-proof antimicrobial materials
Inventing rapid, low-cost diagnostic devices for COVID-19 and other infections
Prof. de la Fuente is an NIH MIRA investigator and has received over 80 national and international awards. He is an elected Fellow of the American Institute for Medical and Biological Engineering (AIMBE), one of the youngest ever inducted.
He has been recognized by MIT Technology Review as one of the world’s top innovators for “digitizing evolution to make better antibiotics,” and has received numerous prestigious honors, including:
The Langer Prize
ACS Kavli Emerging Leader in Chemistry
ASM Distinguished Lecturer
Miklós Bodanszky Award
AIChE’s 35 Under 35 Award
Princess of Girona Prize
National Academy of Medicine Emerging Leader in Health and Medicine, among many others
He serves on the editorial boards of top journals and is Associate Editor of Drug Resistance Updates (IF = 24.3), Nature Communications Biology, Bioactive Materials, and others. He has been named a Highly Cited Researcher by Clarivate multiple times.
Prof. de la Fuente has delivered over 300 invited lectures, including Keynotes, Named Lectures, and TEDx, and is co-author of an influential book on machine learning for drug discovery, with multiple patents and over 160 peer-reviewed publications in top-tier journals such as Cell, Science, Nature Biomedical Engineering, and PNAS.
