Alto Neuroscience has pointed to the success of its antidepressant therapy in a phase 2a trial as proof that its precision psychiatry platform can identify the patients most likely to benefit from its treatment.
The therapy, dubbed ALTO-100, hit the study’s primary endpoint of demonstrating a change in depression severity compared to baseline after six weeks in patients with major depressive disorder. Specifically, the 59 patients that Alto identified as having a relevant brain biomarker saw a mean 15.5 point reduction in their severity score, while the 64 patients without the biomarker saw a more modest 10.6 point decrease.
When it came to achieving clinical response—defined as a 50% reduction in symptoms of depression—the split was seen again, with 61% of biomarker-defined patients hitting this mark compared to 33% of patients without the biomarker.
The biotech used its AI-based Precision Psychiatry Platform to identify the study participants most likely to respond well to the drug “based on an understanding of biological heterogeneity in depression and ALTO-100’s novel mechanism,” the company said in a release Jan. 10.
The data support moving into a large phase 2b trial focused solely on patients with this biomarker later this month, Alto added. The current phase 2a trial also involves ALTO-100 being given to 95 patients with post-traumatic stress disorder, with analyses “ongoing for the population with PTSD to inform potential future studies in that indication.”
“The strength of these results demonstrates, for the first time, that we can prospectively identify likely responders to our novel drugs and apply data-driven measurement to the treatment of psychiatric and other central nervous system disorders,” said CEO Amit Etkin, M.D., Ph.D. “As this provides a substantial level of de-risking, we are eager to move ALTO-100 into the phase 2b study which will begin enrollment this month.”
Alto’s plans for ALTO100 are backed by a $35 million series B funding round in October. The company’s platform evolved out of more than a decade of research from Stanford University’s Etkin Lab.
The brain biomarkers the company is focused on include behavior, electroencephalogram (EEG) activity, and sleep and activity patterns, through which it believes AI can help identify the most likely patient responders. Its ultimate vision is for many of these biomarkers to be measured by remote-deliverable tools such as computerized behavioral tests, wearable tech or even in-home EEGs.