Unlearn Introduces Digital Twin Generators for Psychiatric Disorders
By Frank Fuller, Judy Viduya, Satish Casie Chetty, and Susanna Qiao
In our continuous effort to advance AI in medicine, Unlearn has just expanded our Digital Twin Generators (DTGs) into the realm of psychiatric disorders with the release of two groundbreaking models: one for schizophrenia and one for major depressive disorder (MDD). This marks a significant step forward in addressing the pressing need for accelerating clinical research in these complex indications.
Schizophrenia and MDD are two of the most debilitating psychiatric conditions affecting millions worldwide. Schizophrenia, characterized by distortions in thinking, perception, emotions, language, and behavior, can lead to significant social and occupational dysfunction. MDD, marked by persistent sadness, loss of interest or pleasure, and various physical and cognitive symptoms, is a leading cause of disability globally. The complexity and heterogeneity of these disorders pose substantial challenges in treatment, necessitating personalized and precise therapeutic approaches.
Schizophrenia DTG (SCZ DTG 1.0)
Our Schizophrenia DTG is designed for use in acute trials targeting Positive and Negative Syndrome Scale (PANSS) Total Score or Clinical Global Impression (CGI) Severity endpoints from one to three months post-randomization or post-treatment initiation. The model supports standard of care involving first or second-generation antipsychotics that can be used to support adjunctive therapy trials or in active comparison against other antipsychotics. The model was trained on data from a couple thousand patients. Evaluation of the model on held-out data indicates the largest expected variance reduction is realized within 6 weeks of an acute event.
Major Depressive Disorder DTG (MDD DTG 1.0)
Our MDD DTG targets the Hamilton Depression Total Score (HAM-D) Total Score as the primary endpoint in acute trials from one to three months after treatment initiation. Participants are on standard of care involving first-line antidepressants like selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs). Our training set includes five trials with over five thousand patients. Evaluation of the model on held-out data indicates the model can dramatically improve variance reduction for all common MDD trial durations.
Looking Forward
The release of these DTGs for schizophrenia and MDD represents a pivotal advancement in our quest to harness AI for precision medicine. Given the common challenges in recruiting patients for psychiatric disorders trials, our DTGs offer an alternative and more comprehensive understanding of individual patient responses to support more efficient clinical trials. These DTGs have the potential to transform the treatment landscape for psychiatric disorders.
We encourage you to download our DTG specification sheets to gain a comprehensive understanding of our DTGs, including their capabilities and underlying data.