Method and Apparatus for Detecting Conditions from Physiology Data

1 . A method for monitoring a patient for effects of a pharmacological therapy comprising the steps of:

collecting physiology data from at least one wearable sensor worn by the patient during a pre-treatment interval;

creating an individualized estimator model based on the patient's pre-treatment collected physiology data, the model capable of estimating physiological variables responsive to receiving new physiology data from the at least one wearable sensor worn by the patient;

collecting additional physiology data from the at least one wearable sensor worn by the patient during a post-treatment interval;

generating estimates of the post-treatment physiology data using the individualized estimator model;

comparing post-treatment physiology data to the estimates thereof and determining when a pre-defined effect pattern is present based at least in part on the comparison; and

when the predefined effect pattern is present, determining and performing an action, the action being one or more of:

triggering an electronic questionnaire to be prompted to the patient;

providing instructions to the patient to take a measurement;

providing instructions to the patient to contact the patient's clinician;

triggering a ticket in a call center system to queue a call to the patient;

creating a prompt in an app on the patient's phone to contact a clinician;

providing instructions to the patient related to triaging the effects;

transmitting a control signal to control medical equipment associated with treating the patient;

transmitting instructions to a vaccine manufacture to alter a composition and/or dosage of a vaccine.

2 . The method of claim 1 , wherein the effects are adverse side effects.

3 . The method of claim 1 , wherein the effects are signs of efficacy of a vaccine.

4 . The method of claim 1 , wherein the physiology data comprises heart rate data, respiration rate data, core temperature data, skin temperature data, and activity data.

5 . The method of claim 1 , wherein the individualized estimator model is trained using data collected from the patient while in a free-living physiological state where an inflammatory status of the patient is stable and not expected to be changing.

6 . The method of claim 1 , wherein comparing comprises determining residuals between the estimates and the physiology data.

7 . The method of claim 6 , wherein the residuals are synthesized into a singular score, the score being a scalar index.

8 . The method of claim 1 , wherein the individualized estimator model comprises a neural network.

9 . A system for monitoring a patient for effects of a pharmacological therapy, the system comprising:

at least one wearable sensor worn by a patient during a pre-treatment interval, the at least one wearable sensor configured to collect physiology data from the patient;

a control circuit coupled to the at least one wearable sensor, the control circuit configured to:

create an individualized estimator model based on the patient's pre-treatment collected physiology data, the model capable of estimating physiological variables responsive to receiving new physiology data from the at least one wearable sensor worn by the patient;

wherein the at least one wearable sensor collects additional physiology data from the at least one wearable sensor worn by the patient during a post-treatment interval;

wherein the control circuit is further configured to:

generate estimates of the post-treatment physiology data using the individualized estimator model;

compare post-treatment physiology data to the estimates thereof and determine when a pre-defined effect pattern is present based at least in part on the comparison; and

when the predefined effect pattern is present, determine and perform an action, the action being one or more of:

provide instructions to the patient related to triaging the effects;

transmit a control signal to control medical equipment associated with treating the patient;

transmit instructions to a vaccine manufacture to alter a composition and/or dosage of a vaccine.

10 . The system of claim 9 , wherein the effects are adverse side effects.

11 . The system of claim 9 , wherein the effects are signs of efficacy of a vaccine.

12 . The system of claim 9 , wherein the physiology data comprises heart rate data, respiration rate data, core temperature data, skin temperature data, and activity data.

13 . The system of claim 9 , wherein the control circuit trains the individualized estimator model using data collected from the patient while in a free-living physiological state where an inflammatory status of the patient is stable and not expected to be changing.

14 . The system of claim 9 , wherein the control circuit is configured to compare by determining residuals between the estimates and the physiology data.

15 . The system of claim 14 , wherein the control circuit is configured to synthesize the residuals into a singular score, the score being a scalar index.

16 . The system of claim 9 , wherein the individual estimator model comprises a neural network.