Meet Alexandre Goyon

Alexandre develops analytical methods to characterize therapeutic modalities spanning small molecules, oligonucleotides, peptides, mRNAs, and conjugates. By using multidimensional LC-MS systems, he aims to streamline online sample preparation, accelerate method development, and close characterization gaps affecting the safety, stability, and quality of new medicines.

“What excites me most is solving complex analytical gaps for novel modalities, such as resolving elusive oligonucleotide diastereomers to provide actionable clarity,” he says. “This moment is critical because the rapid expansion of complex therapeutics requires unprecedented characterization rigor to ensure only the safest, most effective candidates advance to patients.”

“It is easy to measure speed, but much harder to quantify critical thought,” says Alexandre. As hardware matures, he sees AI-driven automation and high-throughput data generation becoming central to analytical science, with models predicting optimal parameters and molecular properties. But those models, he stresses, will only be as dependable as the data behind them. “As AI and automation accelerate our workflows, there is a real risk of moving rapidly in the wrong direction. Paradoxically, the rise of autonomous tools will make individual human oversight more critical than ever.”

Choosing an internship at Queen’s University in Canada instead of a more convenient option in Spain transformed Alexandre’s career, opening opportunities in food science, biopharmaceutical characterization, and ultimately Genentech. Outside the laboratory, he enjoys summer hiking and backcountry skiing. “Navigating unmapped terrain requires risk assessment, adaptability, and resilience, which is the exact mindset needed when stepping into the lab to tackle uncharted scientific problems,” he says. “Plus, being off the grid is where my best breakthroughs happen!”