NAIROBI, Kenya- In the high-tech lab of Terray Therapeutics in Monrovia, California, robots hum and scientists in blue coats monitor a symphony of miniaturized automation.
Here, the future of drug discovery is unfolding at a nanoscale level.
Terray’s lab functions as a data factory for AI-assisted drug discovery, generating an astonishing 50 terabytes of raw data daily—equivalent to over 12,000 movies.
Proteins in solution interact with chemical molecules in minuscule wells on custom silicon chips, and every interaction is meticulously recorded.
Jacob Berlin, co-founder and CEO of Terray, sums it up: “Once you have the right kind of data, the A.I. can work and get really, really good.”
AI is transforming drug discovery from a painstaking artisanal craft to a precise, automated process.
The technology, which learns from vast amounts of specialized data—molecular information, protein structures, and biochemical interactions—can suggest potential drug candidates with remarkable accuracy.
According to McKinsey & Company, AI represents a “once-in-a-century opportunity” for the pharmaceutical industry.
Terray’s high-tech lab is not just about automation; it’s about accelerating the drug development process.
Generative AI can design a drug molecule digitally, which is then translated into a physical molecule and tested against target proteins.
This continuous feedback loop between AI and lab experiments accelerates the process, making drug discovery more efficient.
While some AI-developed drugs are already in clinical trials, the journey is just beginning. David Baker, a biochemist and director of the Institute for Protein Design at the University of Washington, notes, “Generative A.I. is transforming the field, but the drug-development process is messy and very human.”
Traditionally, drug development has been an expensive, time-consuming endeavor. Designing a drug and navigating clinical trials to approval can cost around $1 billion and take 10 to 15 years.
Additionally, nearly 90pc of candidate drugs fail in human trials due to inefficacy or unforeseen side effects. However, AI-driven precision and speed promise to improve these odds and reduce costs.
Terray and other AI-driven drug developers are often funded by pharmaceutical giants, which view these partnerships as a low-cost path to innovation.
As Gerardo Ubaghs Carrión, a former biotech investment banker, puts it, “For them, it’s like taking an Uber to get you somewhere instead of having to buy a car.”
These partnerships involve milestone payments that can reach hundreds of millions of dollars, with the potential for royalty income if a drug is commercially successful.
Companies like Terray, Recursion Pharmaceuticals, Schrödinger, and Isomorphic Labs are at the forefront of this AI-driven revolution.
Isomorphic, a spinout from Google DeepMind, focuses on computational approaches, betting on the strength of its software.
Their latest AI model, AlphaFold 3, can predict how molecules and proteins will interact—a significant step in drug design.
Terray is developing new drugs for inflammatory diseases such as lupus, psoriasis, and rheumatoid arthritis, with plans to enter clinical trials by early 2026.
The ultimate test, as Dr. Berlin puts it, will be whether in 10 years we can look back and see a significant increase in the clinical success rate and better drugs for human health.
