Mendelspod Podcast

For decades, drug developers have struggled with so-called "undruggable" proteins—those regions of the proteome that evade traditional small molecules and antibodies. But Aikium, led by Eswar Iyer, could be changing the game. In today’s show, Iyer, a prolific scientist with over 100 patents and a background in George Church’s lab, shares how his company is tackling one of the toughest challenges in therapeutics.

At the heart of Aikium’s approach is Yotta-ML2, an AI-powered wet lab platform that searches the vast combinatorial space of proteins to create precise, bespoke binders for disease targets that have long been out of reach. “The combinatorial space for how many proteins can bind a region is very large,” Iyer explains. “Experiments are limited to 10⁹ to 10¹² possibilities, but the theoretical space exceeds 10¹⁵. We’re using AI to intelligently navigate this massive search problem and find what actually works in the body.”

Iyer is clear-eyed about the biggest challenges ahead: “AI is just hype if it can’t deliver better therapies, faster,” he says. “The biggest barrier isn’t just designing binders—it’s making sure they work in human biology, avoiding immunogenicity, and accelerating the slow feedback cycle of drug development.”

Looking to the future, Iyer envisions a major shift in the industry: “We’re living in an age of exponential technologies. Just as AI has transformed other fields, it’s going to compress the timeline and risk of therapeutic development. In five or six years, we’ll see a wave of AI-designed molecules entering the clinic.”