Personalized Solriamfetol Therapy System for Impaired Renal Function

A next-generation solriamfetol therapy system that leverages machine learning, wearable devices, and cloud-based analytics to provide personalized dosing regimens, real-time efficacy monitoring, and collaborative care management for subjects with impaired renal function.

The original patent disclosed methods for decreasing adverse effects associated with solriamfetol therapy in subjects with impaired renal function. However, these methods rely on static dosing regimens and do not account for individualized kidney function metrics, medical history, or real-time therapy efficacy monitoring. The new inventive concept addresses these limitations by introducing a personalized solriamfetol therapy system that adapts to the subject's unique needs and renal function in real-time.

The system comprises a machine learning module that predicts optimal dosing regimens based on individualized kidney function metrics and medical history. Wearable devices and artificial intelligence-powered analytics enable real-time monitoring of solriamfetol therapy efficacy. A novel solriamfetol formulation with a targeted release mechanism adapts to the subject's renal function in real-time, ensuring optimal drug delivery and minimizing adverse effects. A cloud-based platform facilitates collaborative care management, enabling seamless communication between healthcare providers and real-time data analysis. A wearable device tracks solriamfetol therapy adherence and detects potential adverse effects, providing personalized alerts and recommendations to healthcare providers.

The new claims introduce a paradigm shift in solriamfetol therapy by integrating machine learning, wearable devices, and cloud-based analytics to provide personalized and adaptive dosing regimens. This is a significant departure from the original patent's static dosing regimens, demonstrating a novel and non-obvious approach to solriamfetol therapy.

Alternative embodiments of the inventive concept could include the use of other machine learning algorithms, different wearable device form factors, or integration with electronic health records. Variations of the system could be designed for specific patient populations, such as pediatric or geriatric subjects.

The personalized solriamfetol therapy system has significant commercial potential in the pharmaceutical and healthcare industries, particularly in the areas of sleep disorders, nephrology, and personalized medicine. The system's ability to provide real-time efficacy monitoring and adaptive dosing regimens could lead to improved patient outcomes, reduced healthcare costs, and increased market share for solriamfetol therapy providers.