Robotic Microtool Control in an Intelligent Automated In Vitro Fertilization and Intracytoplasmic Sperm Injection Platform
US-2024426856-A1 · Dec 26, 2024 · US
US2016306945A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016306945-A1 |
| Application number | US-201415101756-A |
| Country | US |
| Kind code | A1 |
| Filing date | Dec 6, 2014 |
| Priority date | Dec 6, 2013 |
| Publication date | Oct 20, 2016 |
| Grant date | — |
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The present invention is directed to computer based pharmacokinetics systems, such as. web-based pharmacokinetics systems, and their use to predict a dose and a dosing interval for a patient in need of a clotting factor therapy.
Opening claim text (preview).
What is claimed is: 1 . A method of treating a bleeding episode comprising administering to a subject in need thereof a therapeutic dose of a clotting factor at a dosing interval, wherein the dose and dosing interval are calculated using a web-based application that is accessible through a web server, wherein the application is programmed to implement a clotting factor population pharmacokinetic (popPK) model and a Bayesian estimation program to calculate the dose and dosing interval. 2 . A method of treating a bleeding episode comprising (1) calculating a therapeutic dose of a clotting factor and a dosing interval of the clotting factor for a subject in need thereof using a web-based application that is accessible through a web server, wherein the application is programmed to implement a clotting factor population pharmacokinetic (popPK) model and a Bayesian estimation program to calculate the dose and dosing interval and (2) administering the clotting factor at the calculated dose and the dosing interval to the subject. 3 . The method of claim 1 or 2 , further comprising entering individual clotting factor pharmacokinetic information. 4 . The method of claim 3 , further comprising, optionally contemporaneously, updating the popPK model based on the individual clotting factor pharmacokinetic information. 5 . The method of any one of claims 1 to 4 , wherein the application continuously updates the popPK model based on newly input clotting factor pharmacokinetic information. 6 . The method of claim 1 or 2 , further comprising, before the calculating, inputting a body weight of the subject. 7 . The method of claim 1 or 2 , further comprising inputting a rise of plasma clotting factor activity level desired following the administrating (“desired rise of plasma clotting factor activity level”). 8 . The method of any one of claims 1 to 7 , wherein the clotting factor is long-acting. 9 . The method of claim 8 , wherein the long-acting clotting factor is rFVIIIFc or rFIXFc. 10 . The method of any one of claims 1 to 9 , further comprising, before the calculating, inputting the subject's age. 11 . The method of claim 9 , wherein the long-acting clotting factor is rFVIIIFc and further comprising, before the calculating, inputting the subject's Von Willebrand Factor (VWF) level. 12 . The method of any one of claims 1 to 11 , further comprising, before the calculating, measuring a clotting factor activity level in plasma at various time points after an initial dose of the clotting factor, wherein individual subject clotting factor pharmacokinetic information is, optionally contemporaneously, calculated based on the clotting factor activity level. 13 . The method of claim 12 , further comprising, before the measuring, administering an initial dose of the clotting factor. 14 . The method of claim 12 or 13 , wherein the initial dose is a fixed interval dose. 15 . The method of any one of claims 1 to 14 , wherein the clotting factor popPK model is updated, optionally contemporaneously, and is, optionally immediately, available through the web server. 16 . The method of claim 15 , wherein the clotting factor popPK model is updated, optionally immediately, after the individual subject clotting factor pharmacokinetic information is added to the application and wherein an updated clotting factor popPK model is available for a next use. 17 . A web-based method of, optionally contemporaneously, improving the predictive accuracy of clotting factor dosing information, the method comprising: (a) accessing a web-based application accessible through a web server, the application comprising a dataset comprising clotting factor population pharmacokinetic (popPK) information, (b) inputting individual subject clotting factor pharmacokinetic information into the application to create a new dataset, and (c) calculating, using the application, a clotting factor popPK model using the new dataset. 18 . The method of claim 17 , wherein the calculating is performed automatically or upon request. 19 . The method of claim 17 or 18 , wherein the popPK model is used to create a dosing regimen for clotting factor administration to a subject in need thereof. 20 . The method of claim 19 , further comprising administering to the subject a clotting factor according to the regimen. 21 . The method of any one of claims 17 to 20 , wherein the clotting factor is long-acting. 22 . The method of claim 21 , wherein the long-acting clotting factor is rFVIIIFc or rFIXFc. 23 . The method of any one of claims 1 - 23 , wherein: (a) the clotting factor is rFVIIIFc and the popPK model includes one or more parameters selected from the group consisting of the parameters in Example 9, 11, and 16 (Table 18, 24, 25, or 33), or (b) the clotting factor is rFIXFc and the popPK model includes one or more parameters selected from the group consisting of the parameters in Example 5 or 7 (Table 10, 13, or 14). 24 . A web-based method of estimating long-acting FIX dosing information individualized for a patient, the method comprising: (a) receiving, by one or more electronic devices, at least one of patient information and desired treatment outcome information, (b) transmitting, by a processing device, the at least one of patient information and desired treatment outcome information to a web-based application program accessible through a web server, wherein the application is programmed to implement a long-acting FIX population pharmacokinetic (popPK) model of Example 5 or 7 and a Bayesian estimation program, (c) receiving from the web based server and program, individualized dosing information calculated using the popPK model, the Bayesian estimation program, and the transmitted information of (b), and (d) outputting, by the one or more electronic devices, the individualized dosing information. 25 . A web-based method of estimating long-acting FVIII dosing information individualized for a patient, the method comprising: (a) receiving, by one or more electronic devices, at least one of patient information and desired treatment outcome information, (b) transmitting, by a processing device, the at least one of patient information and desired treatment outcome information to a web-based application program accessible through a web server, wherein the application is programmed to implement a long-acting FVIII popPK model of Example 9 or 11, and a Bayesian estimation program, (c) receiving from the web based server and program, individualized dosing information calculated using the popPK model, the Bayesian estimation program, and the transmitted information of (b), and (d) outputting, by the one or more electronic devices, the individualized dosing information. 26 . A web-based method of estimating long-acting FIX dosing information individualized for a patient, the method comprising: (a) receiving, by a processing device, at least one of patient information and desired treatment outcome information by a web-based application program accessible through a web server and programmed to implement a long-acting FIX population pharmacokinetic (popPK) model, and a Bayesian estimation program, wherein the received information is transmitted by one or more electronic devices, (b) calculating, by the web-based program, individualized long-acting FIX dosing information using the FIX popPK model, the Bayesia
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Factor VII (3.4.21.21); Factor IX (3.4.21.22); Factor Xa (3.4.21.6); Factor XI (3.4.21.27); Factor XII (3.4.21.38) · CPC title
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