We are a clinical-stage biopharmaceutical company with a mission to redefine psychiatry by leveraging neurobiology to develop personalized and highly effective treatment options. Building on more than a decade of research by our founder, Dr. Amit Etkin, we aim to deeply understand brain function and match patients to the right medication more efficiently through the use of treatments that, if approved, are tailored to specific patient populations. As a result, we believe we can help patients avoid the often lengthy process of trying multiple ineffective treatments before finding one to which they respond, potentially helping patients get better faster. Through insights derived from our scalable and proprietary Precision Psychiatry Platform, or our Platform, which applies rigorous data science and robust analytics to data gathered by neurocognitive assessments, electroencephalography, and wearable devices, we aim to discover brain-based biomarkers to better identify which patients are more likely to respond to our novel product candidates. Our approach is designed to improve patient outcomes and increase the likelihood of clinical success and commercial impact of our product candidates by using neurobiological profiles to identify more homogeneous patient groups. We build upon and leverage vast data sets of longitudinal clinical and biomarker data from thousands of patients across central nervous system, or CNS, disorders, which we believe serves as a foundation for applying our approach across numerous patient populations. Ultimately, if we are successful, we believe our approach can substantially improve upon the traditional, all-comer approach to CNS drug development. Our current pipeline consists of five clinical-stage assets initially targeting major depressive disorder, or MDD, and schizophrenia populations characterized by independent brain-based biomarkers. Each of our clinical-stage product candidates has been evaluated through at least initial Phase 1 clinical trials and observed to be well tolerated. Our most advanced programs, including our two product candidates being evaluated in ongoing late-stage (Phase 2b or later) trials, are supported by prospectively replicated evidence of clinical activity in biomarker-characterized populations. We have successfully completed Phase 2a trials for our two most advanced product candidates, ALTO-100 and ALTO-300, in more than 200 patients each. In each of these trials, we identified patient populations more likely to respond based on objectively defined biomarker profiles, and then prospectively replicated these biomarker findings in independent datasets from within the same trial. We leveraged these biomarker findings to initiate a placebo-controlled, double-blind, randomized Phase 2b trial for each candidate in patients with MDD characterized by an objective biomarker. Specifically, in the ALTO-100 Phase 2b trial we are enrolling 266 patients with MDD characterized by a cognitive biomarker, and we expect to report topline data from this trial in the second half of 2024; and in the ALTO-300 Phase 2b trial we are enrolling 200 patients with MDD characterized by an electroencephalography, or EEG, biomarker, and we expect to report topline data from this trial in the first half of 2025. We estimate one or both of these two independent biomarkers are present in approximately three-quarters of the overall MDD population. In addition to our two most advanced programs, we expect to initiate Phase 2 proof-of-concept, or POC, trials evaluating ALTO-101 and ALTO-203 in the first half of 2024. ALTO-101 is being developed for patients with cognitive impairment associated with schizophrenia, or CIAS, and ALTO-203 is being developed for patients with MDD and higher levels of anhedonia, or the lack of motivation or pleasure. We expect to report topline data from these trials in 2025 and the first half of 2025, respectively. We also plan to develop ALTO-202, our novel, oral N-methyl-D-aspartate, or NMDA, receptor antagonist, for the treatment of patients with MDD. Our Platform and differentiated approach aim to disrupt the trial-and-error method that is currently standard practice in CNS drug development and clinical care. The data we leverage in connection with the development and application of our Platform comes from multiple sources, including proprietary research, commercial licenses, and publicly available databases. Data we have generated through our own clinical trials, combined with various data sets acquired through licenses or research collaborations, amount to approximately 250 terabytes of clinical and biomarker data, which have been used to develop and enhance our methodologies aimed at discovering predictive biomarkers. Our Platform and approach employ modern tools for measuring human neurobiology together with rigorous data science analytics to discover, and prospectively replicate, biomarker signatures. We use these signatures to identify drug responders, or patients that may demonstrate better clinical response to our novel product candidates. We believe this approach has the potential to increase the probability of clinical success by magnifying the impact of each product candidate, thereby yielding a differentiated drug profile. However, our approach to the discovery and development of product candidates based on our Platform is novel and has not been used for the approval of other CNS products. We currently anticipate that the modalities we use to define brain-based biomarkers, for some of our product candidates, may require us to develop and obtain FDA approval of a companion diagnostic for the accompanying product candidate. We expect to initiate discussions with the FDA concerning the development of companion diagnostics at our end of Phase 2 meetings with respect to ALTO-100 and ALTO-300. The modalities we use to define brain-based biomarkers include: • Computerized Neurocognitive Battery: Neurocognitive tasks have been used over many decades of neuropsychological assessment to help researchers understand cognitive functioning across core domains such as memory, processing speed, attention, and executive functioning. We have implemented digital versions of well-validated neurocognitive tasks in our proprietary battery, Spectra, which we use to test and characterize patients across cognitive domains. • Electroencephalogram (EEG): An EEG is a non-invasive test measuring electrical activity in the brain. While more commonly used to assess seizures, EEG has a long track record of sensitivity to clinically relevant brain wave patterns across neuropsychiatric disorders and treatments. We leverage machine learning to identify potentially useful features from EEG signals. • Wearable Devices: We use wearable devices to analyze patient sleep and activity patterns. Through correlating these patterns with drug intervention outcomes, we aim to derive biomarker signatures that may predict therapeutic responses. --- In addition to identifying likely drug responders, we deploy our Platform in early-stage clinical development aimed to robustly characterize drug effects on the human brain using these biomarker modalities, thereby informing dose and indication selection for later-stage clinical development in a patient population characterized by the applicable biomarker. Together with our process for identifying likely drug responders, our approach is meaningfully differentiated from traditional, all-comer CNS drug development, wherein often little is known about the effects of a drug on the human brain. The traditional approach has resulted in high rates of failure in CNS drug development across all phases of clinical development, with a 7.3% and 6.2% likelihood of approval from Phase 1 in psychiatry and neurology, respectively. With our differentiated approach, we aim to improve upon the high failure rates in late-stage clinical development in CNS through better characterizing our product candidates, and the populations we are targeting with them, early in development. Our Platform is unproven and clinical evidence to support our approach is preliminary and limited at this time, and, as such, there can be no guarantee that our approach will result in an increased rate of approval for our therapeutic candidates. Mental health conditions are a leading cause of disability globally. Current estimates suggest that over 50% of the U.S. population will be diagnosed with a psychiatric disorder during their lifetime, with an estimated $280 billion spent on mental health services in the United States in 2020. We believe limitations of currently available treatments, which are often ineffective in a large portion of patients, are a key driver of these rising costs. We believe better outcomes can be achieved through precision medications tailored specifically to address heterogenous alterations in brain functioning seen across individual patients within any psychiatric diagnosis. While personalized medicine has made significant advances in fields like oncology, neuropsychiatry drug development and patient treatment remain largely untargeted. The magnitude of the populations and clinical need within our two lead indications, MDD and schizophrenia, are significant. MDD is one of the most prevalent and incapacitating medical conditions, with an estimated 21 million, or 8.3% of, adults in the United States experiencing at least one major depressive episode in 2021. Despite the availability of approved medications, a significant majority of patients do not achieve adequate response after standard treatment protocols. Moreover, most antidepressants work through similar mechanisms, with little true innovation to address patients who do not respond to medications that primarily target monoamine neurotransmitters, such as serotonin and dopamine. Schizophrenia is a life-long, highly debilitating mental health disorder affecting approximately 2.8 million adults in the United States as of 2020. Currently available medications generally target positive symptoms of schizophrenia, and there are no approved medications for the cognitive and negative symptoms despite their prevalence and often strong correlation with functional impairment. Alto Neuroscience, Inc. was incorporated under the laws of the State of Delaware in March 2019. Our principal executive office is located at 369 South San Antonio Road, Los Altos, CA.