A poster titled “Using Machine Learning and Real-World Data to Identify Patients with Schizophrenia for whom Aripiprazole Monohydrate LAIs are Likely to be a Favorable Treatment Option” was presented at the American Society of Clinical Psychopharmacology Annual Meeting. Authors: Christoph U. Correll, Jason Jones, Bharath Ravichandran, Karimah S. Bell Lynum, Norman Atkins Jr., Soma S. Nag, Kristine Harrsen, Anne M. Hutson Walker, Tiffany Yu, Bartek Augustyniak, Isaac Kirk-Koffi, Vincent Marino, Rachel Linker, and Mauricio Tohen.
The authors are affiliated with the Donald and Barbara Zucker School of Medicine, Charité Universitätsmedizin Berlin, Zucker Hillside Hospital, the German Center for Mental Health, Einstein Center for Population Diversity, Atropos Health, Guidehouse Inc., Otsuka Pharmaceutical Development & Commercialization Inc., H. Lundbeck A/S, Lundbeck LLC, and the University of New Mexico School of Medicine.
Short Summary:
This study leveraged machine learning and real-world patient data to identify schizophrenia patients who are most likely to benefit from Aripiprazole Monohydrate long-acting injectable (LAI) medications, aiming to better guide treatment selection at the individual patient level.
Key Conclusion:
- Findings suggest that broader adoption of LAIs in early-stage schizophrenia may lead to improved outcomes compared to current real-world treatment patterns