Fresenius Medical Care Holdings, Inc.

Fresenius Medical Care Deutschland Gmbh

Doris Helene Fuertinger

Peter Kotanko

Stephan Thijssen

Franz Kappel

Alice Topping

Aurelio A De Los Reyes, V

Anna Meyring-Wosten

Nathan W Levin

Sabrina Casper

David Joerg

Gudrun Schappacher-Tilp

Ulrike Kotanko

Aurelio A De Los Reyes V

Techniques and apparatus for generating, performing, and evaluating virtual clinical trials that include clinic modules to represent real-world operational aspects of trial entities are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to generate a plurality of avatars configured to model a health condition associated with a population of patients, and to perform a virtual clinical trial to simulate a course of treatment for the plurality of avatars, the virtual clinical trial to include at least one clinic module associated with at least one event and a probability for the at least one event, the at least one event to model an operational aspect of an entity of the virtual clinical trial. Other embodiments are described.

Techniques for conducting virtual clinical trials

A computing system for determining a systematic training strategy for the user is provided. The computing system includes a user device that uses one or more sensors to obtain partial pressure of oxygen (PO2) levels of a user over a period of time. The user device provides previous PO2 levels to a personalized erythropoiesis model generation computing platform. The computing platform obtains individualized user data for the user indicating or more previous hematocrit and/or hemoglobin measurements for the user. The computing platform determines an individualized erythropoiesis model for the user based on the one or more previous hematocrit and/or hemoglobin measurements and the previous PO2 information, and employs the individualized erythropoiesis model to determine predicted hematocrit and/or hemoglobin measurements. The computing platform performs one or more actions based on the one or more predicted hematocrit and/or hemoglobin measurements.

System and method for attaining desired oxygen dosing based on erythropoiesis modeling

A method includes: receiving measurements of a blood-related parameter corresponding to a patient undergoing hemodialysis; estimating a value of one or more hemodialysis treatment-related parameters by applying a vascular refill model based on the received measurements of the blood-related parameter, wherein the one or more hemodialysis treatment-related parameters are indicative of an effect of vascular refill on the patient caused by the hemodialysis; determining, based on the one or more estimated values of the one or more hemodialysis treatment-related parameters, a hemodialysis treatment-related operation; and facilitating performance of the treatment-related operation. The vascular refill model is a two-compartment model based on a first compartment corresponding to blood plasma in the patient's body, a second compartment based on interstitial fluid in the patient's body, and a semi-permeable membrane separating the first compartment and the second compartment.

System for analyzing vascular refill during short-pulse ultrafiltration in hemodialysis

A method of adjusting a patient's undesired hematocrit and/or hemoglobin concentration to a value within a desired range at a predetermined time with an erythropoiesis stimulating agent (ESA) regimen includes obtaining patient parameters required for input into a model for predicting the patient's hematocrit and/or hemoglobin concentration at a predetermined time with a selected ESA administration regimen, the model including iron homeostasis, and employing the patient parameters and an initially selected ESA administration regimen in the model to predict the patient's hematocrit and/or hemoglobin concentration at the predetermined time with the initially selected ESA administration regimen. The method then includes administering ESA to the patient with an ESA administration regimen predicted to adjust the patient's hematocrit and/or hemoglobin concentration to the desired range at the predetermined time. The method can be implemented in a hemodialysis system.

System and method of modeling erythropoiesis including iron homeostasis

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Long Island City, NY, United States of America

Doris Helene Fuertinger