BRIEF DESCRIPTION OF THE DRAWINGS
The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:
FIG. 1 is one embodiment showing multiple components of the present system.
FIG. 2 shows different layers of an exemplary fluidic device prior to assembly.
FIG. 3 and 4 illustrate the fluidic network within an exemplary fluidic device.
FIG. 4A illustrates an exemplary sample collection unit of the present invention.
FIG. 4B illustrates an exemplary sample collection well in fluidic communication with a metering channel, and a metering element.
FIG. 4C shows an exemplary fluidic network between a metering channel, a mixing chamber and a filter.
FIG. 5 shows a top, side, and bottom view of exemplary reagent chambers of the present invention.
FIG. 6 illustrates an exemplary side view of a reagent chamber in fluidic communication with a fluidic device.
FIG. 7 illustrates exemplary reagent chambers being filled with reagents.
FIGS. 8 and 9 illustrate a side view of an exemplary fluidic device is combination with actuating elements of the reader assembly.
FIG. 9A illustrates an exemplary fluidic device including pump valves and vent modules
FIGS. 9B-9I illustrates exemplary actuatable valve assemblies of the present invention.
FIG. 10 compares a two-step assay with a competitive binding assay.
FIG. 11 shows an exemplary two-step chemiluminescence enzyme immunoassay.
FIG. 12 shows the increased sensitivity of the two-step chemiluminescence enzyme immunoassay.
FIG. 13 shows the ability of TOSCA to assay less than ideal samples and maintain desired sensitivity.
FIGS. 14A-C illustrate exemplary fluidic channels between reaction sites.
FIGS. 15A and 15B illustrate reactions sites to reduce the signal from unbound conjugates remaining in reaction sites.
FIG. 16A shows an exemplary bubble trapper or remover to prevent bubbles from entering the reaction sites.
FIG. 16B illustrates exemplary fluidic communication between a duckbill valve and a waste chamber.
FIGS. 16C-16E show an exemplary duckbill valve
FIG. 16F illustrates reaction sites that are adapted for smooth flow of the reagents and for minimal boundary layer effects.
FIG. 16G shows a perspective view of various layers of an exemplary fluidic device of the present invention.
FIG. 17 shows the sensitivity enhancement achieved using TOSCA as compared with competitive binding.
FIG. 18 shows two analytes, prostacyclin metabolite and thromboxane metabolite, which have been identified and quantified and their concentrations are different by more than 3 orders of magnitude.
FIG. 19 shows an exemplary flow chart of a business method of monitoring a clinical trial of a therapeutic agent.
FIG. 20 shows simultaneous sharing of the information detected with a fluidic device with various interested parties.
FIG. 21 shows a typical assay dose-response data for a two-step assay for T×B2.
FIG. 22 shows dose responses computed with and without errors in calibration parameters.
FIG. 23 shows computed concentration errors produced by 1% mis-estimation of A and D calibration values.
FIG. 24 illustrates calibration using a “differential” approach.
FIG. 25 shows the verification of calibration using the “1-point spike” method (log scale).
FIG. 26 shows the verification of calibration using the “1-point spike” method (linear scale).
FIG. 27 shows dose-response of assays calibrated against a plasma sample with a very low T×B2 concentration.
FIG. 28 shows use of spike recovery to eliminate calibration errors of the “C” parameter.
FIG. 29 illustrates calculating differences in concentration between two samples.
FIG. 30 illustrates an assay of plasma samples.
FIG. 31 shows the time course of assay signal generation.
FIG. 32 shows the impact of change in calibration parameter “A” on assay calibration.
FIG. 33 shows how a reference therapeutic index would be computed.
FIG. 34 illustrates computing the therapeutic index.
FIG. 35 shows multiple regression analysis of the computed therapeutic index.
FIG. 36 is an illustration of the relationship between measured drug, analyte and biomarker concentration and therapeutic index.
FIG. 37 is an illustration of the application of this invention to minimize adverse drug reactions.
FIG. 38 shows exemplary patient input values.
FIG. 39 shows use of a therapeutic index to follow treatment progression in an autism patient.
Patent Application
20070224084
