Insilico Medicine CEO Alex Zhavoronkov is running what amounts to three experiments at once: whether a drug discovered by AI can actually survive a Phase 3 clinical trial, whether AI drug discovery can be profitable, and whether China, not the U.S. or Europe, becomes biotech's next center of gravity, according to Fortune's Nicholas Gordon, who interviewed Zhavoronkov in Hong Kong. The company's lead candidate, rentosertib, a treatment for the fatal lung-scarring disease idiopathic pulmonary fibrosis, entered Phase 3 trials in China this month, with the first patient dosed on Sept. 10. Insilico says it's the first AI-discovered drug of its kind to reach large-scale trials.
The results so far have generated more attention than the trial launch alone would have. A Sept. 7 study in Nature Biotechnology reported that blood samples from 42 rentosertib patients showed signs of reversed biological age, an effect Insilico executives describe as small and possibly not durable, but still among the first clinical hints that an AI-designed drug might influence aging itself. Co-CEO Feng Ren connected the mechanism directly to fibrosis: "We believe aging is related to fibrosis... If we can stop the fibrosis, then we might have a chance to stop biological aging." Insilico followed that with LongevityBench, a new benchmark for testing how well AI models understand aging biology, where the company says its own smaller, aging-trained models outperformed larger frontier systems.
Much of the AI-drug-discovery field that emerged alongside Insilico in the mid-2010s hasn't held up. "Our cohort is now a graveyard," Zhavoronkov said, admitting he made his own overreaching claims early on, including that AI would replace medicinal chemists outright. Rentosertib's path to the clinic began almost as a fluke: after Insilico's algorithms designed and validated a new molecule in mice within 46 days back in 2019, Zhavoronkov said the team rated its odds of success so low, under 1 percent, that they started filming a documentary expecting to document a failure. "We never expected it to succeed," he said. Insilico now has a second drug in Phase 2 trials for ulcerative colitis and eight more in Phase 1, mostly for various cancers.
Zhavoronkov credits China's regulators, not just its scientists, for the pace of progress. China expanded its drug-review corps tenfold after 2015 to clear a lengthy application backlog, cutting average review times from roughly 900 days to about 300 by 2019. Zhavoronkov said Chinese reviewers came into Insilico's process unusually well prepared: "They brought in a lot of experts, and it felt as though they knew my drug better than I did... They knew not only my drug, but all the other drugs." He described Chinese regulators as more focused on measurable survival benefits than on eliminating every uncertainty around safety, giving the company what he called a clear roadmap rather than an open-ended review.
The company has also become profitable, reporting $35.5 million in net profit for the first half of 2026, helped by a run of licensing deals: $2.75 billion with Eli Lilly, $2.5 billion with South Korea's SK Biopharmaceuticals, $600 million with Takeda, and smaller China-specific deals like a $120 million agreement with Qilu Pharmaceutical that Zhavoronkov argues get overlooked. He predicts Chinese demand for novel drugs will keep expanding as the country gets wealthier, "China is going to be 10 Japans," and points to Chinese out-licensing deals with foreign companies, which totaled a record $136 billion last year, as evidence the shift is already underway. Insilico is now pursuing what Zhavoronkov calls a "China-for-China" strategy, licensing its novel drug candidates cheaply to formerly low-innovation Chinese manufacturers, "companies that used to be vitamin C vendors," who can scale them faster and more cheaply than Insilico could alone.
Zhavoronkov is candid about the tradeoffs of operating in China versus elsewhere, both regulatory and cultural. "It's a month in negotiations, not nine months," he said of dealmaking there, adding of his Chinese counterparts and their work habits: "They do not have work-life balance. They have life-life balance." He's also begun shifting Insilico's own focus from developing drugs to selling the AI tools behind them, launching the MMAI Gym in January to fine-tune models like GPT, Claude, and Alibaba's Qwen specifically on medicinal chemistry and clinical development. "We decided to become a coach instead of a player," he said. "We did too much work on drugs. Now it's time for us to release the AI."
On the ethical question hanging over longevity research generally, whether extended healthy lifespans become another luxury reserved for the wealthy, Zhavoronkov pushed back, arguing inequality in longevity already exists and that scale manufacturing tends to erase it over time. He pointed to GLP-1 weight-loss drugs that launched near $2,000 a month and now cost roughly $80 just across the border in Shenzhen as the pattern he expects longevity treatments to follow: "I actually think longevity therapeutics are going to fix inequality."