Reciprocal Labs Corporation

Ki Hong Han

John David Van Sickle

Christopher Hogg

Gregory F Tracy

Leah J Morrell

Mike Lohmeier

Dmitry Stupakov

John Kalmi

Charles Clayton Donaldson

Mark William Sehmer

Meredith Ann Barrett

Robert Austin Lee

Michael Lohmeier

Lucas Karl Dailey

Ian Daniel Alderman

Systems and methods for monitoring accurate, real-time medicament device events, performing analytics on that data, and providing notifications are described. In various embodiments, an application server receives controller medication events, analyzes the events, associated event times, and controller medication dosage plans to characterize event times and send notifications for future doses. The controller medication dosage plan may specify a dose time for a planned dose, a narrow time window comprising the dose time, and an expanded time window comprising the narrow time window and longer in duration than the narrow time window, and the events may be characterized based on their time relative to the dose time, the time windows, and other events.

Real time adaptive controller medication dosing

This description provides trigger identification notifications to patients suffering from respiratory diseases based on large amounts of patient data in order to help effect behavior changes in a patient to prevent inhaler rescue usage events from occurring. Rescue medication events, environmental conditions, and other contextually relevant patient information are detected by sensors associated with the patient's medicament devices and are collected from other sources, respectively to provide a basis to determine identify various triggers of rescue inhaler usage events for a patient. Each trigger is analyzed to determine the severity of the patient's reaction to the trigger and is used to send notifications accordingly.

Identification of asthma triggering conditions based on medicament device monitoring for a patient

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Dublin, CA, United States of America

Ki Hong Han