Recent research published in Proceedings of the National Academy of Sciences A new drug developed using artificial intelligence suggests that it can significantly reduce fentanyl consumption in animal models. This experimental drug targets specific serotonin receptors in the brain, restoring neural pathways altered by addiction. These findings provide evidence that this new compound may ultimately provide a non-addictive treatment option for people experiencing opioid use disorder.
Opioid use disorder currently affects millions of people, and synthetic opioids like fentanyl are creating a serious public health crisis. In search of alternative treatments, scientists have focused on developing treatments that address the neurological changes caused by addiction without relying on opioid-based medications.
“New treatments for opioid use disorder are desperately needed,” said study author Christy D. Fowler, a Chancellor’s Fellow and professor in the Department of Neurobiology and Behavior at the University of California, Irvine. “Almost everyone is affected by the opioid epidemic: people’s mothers, fathers, sisters, brothers, sons and daughters.”
Fowler, who is also co-director of the Center for Addiction Neuroscience at the University of California, Irvine, noted that opioid use disorder does not discriminate based on age or socioeconomic boundaries. “Therefore, I believe that if we can help those who still owe so much to society and their families, it is our ethical responsibility to do so,” she explained.
Historically, the pharmaceutical industry has been reluctant to invest heavily in this area. “For too long, pharmaceutical companies have distanced themselves from the field of addiction treatment based on the stigma of ‘addicts’ and the misconception that the people who buy their drugs cannot afford them,” Fowler said. “This is simply not true. Just as we cannot give up hope for people with other illnesses such as cancer or diabetes, we cannot give up hope for people with opioid use disorder.”
Current treatment options, such as methadone and buprenorphine, tend to be limited by safety concerns, inconsistent long-term efficacy, and difficulties with patient adherence. These drugs are also opioid-based, creating additional challenges for long-term recovery.
To find another pathway, researchers analyzed how fentanyl interacts with the serotonin system, a network of chemical messengers involved in mood, reward, and learning. Long-term use of opioids alters these serotonin pathways, altering the physical structure of brain cell connections. The authors aimed to discover drugs that could target these specific serotonin-related changes rather than opioid receptors.
“We hope that the development of this new drug will lead to more treatment options for people who are trying to stop or reduce their use of opioids,” Fowler said. “Furthermore, because this targeting approach does not include the receptors that opioids act on directly in the brain, this new drug has the potential to produce more beneficial and lasting changes in the brain to overcome the harm caused by previous opioid exposure.”
Researchers used an artificial intelligence platform to analyze large amounts of genetic and chemical data obtained from postmortem brain tissue of human patients who were dependent on opioids. The system identified two specific types of serotonin receptors as likely targets for new treatments.
“These studies used an AI platform developed by GATC Health. Therefore, these studies also provide evidence supporting the use of AI technology to reduce the time required for drug development efforts,” Fowler said. Based on these predictions, the artificial intelligence system generated dozens of potential compounds, and the researchers selected two top candidates, named GATC-021 and GATC-1021.
The researchers first performed clinical tests on the cells to confirm that the two new drugs targeted exactly the intended serotonin receptors. They found that while GATC-021 activated the desired receptors, it also caused unwanted side effects. In a test in which 14 rats explored an open enclosure, the highest dose of GATC-021 significantly reduced the rats’ normal movement and exploration.
In contrast, GATC-1021 showed high accuracy. Laboratory cell tests have shown that it selectively activates targeted serotonin receptors without binding to unrelated pathways. When tested in groups of eight rats, GATC-1021 had no negative effects on general movement or behavior across a range of doses.
Based on these initial safety profiles, scientists evaluated how the drug affected fentanyl uptake. They surgically implanted intravenous catheters into adult male and female Wistar rats. The animal is placed in a special room and presses a lever to administer a small amount of fentanyl. This is a procedure known as intravenous self-administration.
After the rats learned the behavior and established a stable pattern of fentanyl intake over a 10-day period, the researchers injected the rats with the experimental drug or a placebo. These studies included groups of 12 to 13 rats for each specific dose and drug combination. Initially, both drugs reduced fentanyl consumption, but GATC-021 lost its effect during the five-day study period.
On the other hand, GATC-1021 remained effective and showed no signs of resistance. GATC-1021 consistently reduced the number of lever presses for fentanyl in rats across doses ranging from 25 to 70 milligrams per kilogram of body weight. When scientists analyzed the data, accounting for individual differences, they found that GATC-1021 reduced fentanyl intake by more than 60 percent.
Because GATC-1021 targets the same serotonin receptors that are typically activated by hallucinogens, the researchers tested whether it causes hallucinations. In rodents, hallucinogenic effects are measured by observing involuntary rapid twitches of the head. Although known hallucinogens caused significant head convulsions, GATC-1021 did not cause such reactions.
The scientists then looked at how the drug affected the physical structure of brain cells, which transmit information through tiny branch-like projections called dendritic spines. The shape and density of these vertebrae changes as the brain learns and adapts. This is a process known as neuroplasticity. Animals that self-administered fentanyl and received GATC-1021 had a higher proportion of thin, adaptable dendrites compared to rats that received fentanyl alone.
To understand the genetic mechanisms behind these physical changes, the authors analyzed gene expression in three brain regions associated with reward and addiction. They found that while fentanyl intake alone caused widespread changes in gene activity, treatment with GATC-1021 altered these patterns in beneficial ways. The drug significantly increased the activity of certain genes associated with neuroplasticity and brain cell survival in the prefrontal cortex, the brain region responsible for decision-making.
While the integration of artificial intelligence accelerates the discovery process, physical experiments reveal nuances that computer models miss. For example, an artificial intelligence system predicted that combining an experimental drug with sulbutiamine, a synthetic form of vitamin B1, would increase its absorption into the brain. However, animal studies showed that GATC-1021 was actually more effective at entering the brain without the addition of sulbutiamine.
“While AI platforms were essential for the early development of drugs, preclinical testing in animal models was equally essential to determining how drugs would work in complex biological systems,” Fowler said. “These studies found that although the AI predictions were correct overall, some aspects of the predictions were not validated when tested in rodent models. Therefore, preclinical testing remains important to prevent the occurrence of off-target effects in humans.”
Predictions about how this drug will work in humans remain speculative until clinical trials are conducted. “We are still in the early stages of developing this drug, so it will likely take several years before all FDA regulatory pipeline requirements are met,” Fowler explained.
Future studies should investigate how drugs are absorbed and processed in different regions of the brain under different dosing schedules. Scientists also need to investigate the long-term effects of drugs.
“We want to see if this drug is also effective for other disorders that are common in people experiencing opioid use disorder, such as anxiety and depression,” Fowler added.
The study, “AI-derived therapeutic development of serotonin receptor-targeted drugs for the treatment of opioid use disorder,” was authored by Valeria Lallai, Samuel Kho, AC Martin, James P. Fowler, Madison L. Roach, Kevin Wang, Kendyl N. Laumann, Tyler G. Morrison, Mina Palaniappan, Malia Bautista, Allison S. Mogul, and Jinjutha E. Cheaprusak, Vijay Shrestha, Danaji M. Reid, Julia E. Lagomarsino, Vaishnavi Narayan, Jason Ufens, Waldemar Learnhardt, Saman Mirzai, Ian Jenkins, Arturo R. Zavala, Jonathan R.T. Lakey, Robert Tinder, and Christy D. Fowler.
