Tempus Labs. has filed a patent for a system that offers personalized depression disorder treatment. The system uses patient data and empirical outcomes to determine personalized treatment options. A method for generating treatment information for mental health disorders is also outlined, involving molecular data analysis and clinical information. GlobalData’s report on Tempus Labs gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Tempus Labs, Personalized treatment planning was a key innovation area identified from patents. Tempus Labs's grant share as of January 2024 was 22%. Grant share is based on the ratio of number of grants to total number of patents.
Personalized depression disorder treatment based on molecular data
A patent application (Publication Number: US20230386643A1) describes a method for generating treatment information for patients diagnosed with mental health disorders. The method involves obtaining molecular data from a sample, providing clinical data and cohort data, generating a report from a therapy engine based on the molecular data and clinical information, and presenting the report to a user. The report includes nucleic acid sequences associated with the diagnosed disorder, a list of effective drugs based on the data, and additional information such as drug classifications and potential side effects. The therapy engine is continuously updated with new clinical data to improve treatment recommendations over time.
Furthermore, the patent application details a system and a computer-readable medium for implementing the method. The system includes memory and a processor to execute instructions for obtaining molecular data, providing clinical and cohort data, generating reports, and presenting them to users. The computer-readable medium stores program code instructions for the processor to carry out the method steps. The system and medium also support obtaining and updating clinical data, identifying drug resistance, recommending dosages, and excluding previous medications from recommendations. The method aims to provide personalized treatment recommendations for patients with mental health disorders based on molecular data, clinical history, and cohort data, ultimately improving treatment outcomes and patient care.
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