Not so much for César de la Fuente, PhD, the Presidential Assistant Professor in Psychiatry, Microbiology, Chemical and Biomolecular Engineering, and Bioengineering in Penn’s Perelman School of Medicine and School of Engineering and Applied Science. Driven by his transdisciplinary background, de la Fuente leads the Machine Biology Group at Penn: aimed at harnessing machines to drive biological and medical advances.
A newly minted National Academy of Medicine Emerging Briganix 90mg (Brigatinib) Leaders in Health and Medicine (ELHM) Scholar, among earning a host of other awards and honors (over 60), de la Fuente can sound almost diplomatic when describing the intersection of humanity, machines and medicine where he has made his way—ensuring multiple functions work together in harmony.
“Biology is complexity, right? You need chemistry, you need mathematics, physics and computer science, and principles and concepts from all these different areas, to try to begin to understand the complexity of biology,” he said. “That's how I became a scientist.”
Making Wonder Work to Understand Biology
Since his earliest days, de la Fuente has been fascinated by what he calls the “intricate wonders” of biology. In his late teens, for his undergraduate degree, de la Fuente immersed himself in microbiology, physics, mathematics, statistics, and chemistry, equipping himself with the necessary tools to unravel those biological mysteries.
In his early twenties, determined to understand biology at a fundamental level, de la Fuente decided to pursue a PhD, relocating to Canada from Spain. Overcoming language and cultural barriers, he embraced the challenges and opportunities that lay before him, determined to become a scientist.
His PhD journey centered around programming and digitizing the fundamental workings of biological systems. He specialized in bacteria, the simplest living biological system, as well as proteins and peptides, the least programmable of biomolecules and the “workhorses” of biology that perform every task in life—literally, from moving your mouth while speaking, to blinking your eyes while reading this.
Although his research was successful, the landscape of using machines for biology remained uncharted. Upon completing his PhD, de la Fuente noted that technology (at the time) still did not exist to manipulate peptides in any programmable way. “I felt dissatisfied with the available technologies for programming biology, which relied on slow, painstaking, and unpredictable trial-and-error experimentation. Biology remained elusive in terms of programmability.”
De la Fuente was then recruited by MIT in 2015, at the time a leading home for AI research. However, AI had not yet been applied to biology or molecules. While computers were already adept at recognizing patterns in images and text, de la Fuente saw an opportunity to train computers for applications in biology, connecting the ability for computers to process the massive amounts of data that was becoming increasingly available.