Systems and methods for efficiently performing bioassays

Abstract

This invention provides a system and method for performing assays on biological samples and for high-throughput automation of biological assays. [Solution] An automated laboratory system for processing biological samples in a batch-type manner is disclosed. In an embodiment, the system can receive assay commands for processing biological samples between multiple devices. The devices may include a pre-analysis instrument and one or more analytical systems. The system may include an organizing core application for determining the order of operations for assays requested for the samples.

Description

Technical Field

[0001] 〔Related Applications〕 This application claims priority under 35 U.S.C.§119(e) to U.S. Provisional Patent Application No. 62 / 596,052, filed on December 7, 2017, U.S. Provisional Patent Application No. 62 / 596,032, filed on December 7, 2017, and U.S. Provisional Patent Application No. 62 / 626,581, filed on February 5, 2018. The entire contents of each of these related applications are hereby incorporated by reference into this specification.

[0002] The disclosure of the present invention generally relates to the field of diagnostic automation, and more specifically, to automated scheduling of biological assays.

Background Art

[0003] Diagnostic tests of biological samples are beneficial in the efforts of the medical industry to diagnose and treat diseases quickly and effectively. Clinical laboratories that perform such diagnostic tests may receive hundreds or thousands of samples daily with ever-increasing demands. The challenge of managing such a large number of samples can be assisted by the automation of sample analysis. Automated sample analysis is typically performed by an automated analyzer instrument, which is generally a self-contained system that performs multi-step processing on a biological sample to obtain a diagnostic result.

[0004] Automated clinical analyzers provide users with a range of automated tests that can be performed on a given sample. However, samples are often not prepared for analysis when they arrive in the laboratory. To prepare a sample for testing with an automated analyzer, a laboratory technician typically transfers a certain volume of the sample from the primary container or tube to a secondary container or tube suitable for the analyzer when it is received by the laboratory. In addition, the technician typically needs to know which tests will be performed on the sample so that they can select the test-specific reagents or diluents to combine with the sample. This can be time-consuming and may lead to operator error and exposure to infectious diseases.

[0005] There are also pre-analysis instruments that assist in preparing samples for analysis and further free technicians from the coordination between laboratory sample acceptance and analyzer instrument results. However, many of these instruments still require significant technician involvement, such as before loading the sample into the pre-analysis instrument, when the sample is prepared by the pre-analysis instrument, and when the analyzer instrument has completed the analysis.

[0006] For example, some pre-analysis instruments can automatically transfer a fixed amount of sample from a first container to a second container. However, such systems often require a technician to manually combine the identification codes of the first and second containers before loading them into the system, which can be time-consuming and prone to errors.

[0007] In addition, many of these systems cannot be integrated with one or more analyzer instruments. In this regard, technicians may need to be present to manually transfer samples from the pre-analysis instrument to the analyzer instrument, and then from the analyzer instrument to the storage location once the analysis is complete. This can be frustrating as it redirects skilled labor to trivial tasks and requires technicians to constantly monitor the progress of samples in the pre-analysis instrument and analyzer instrument, waiting to transfer samples when ready to minimize downtime. [Overview of the project] [Problems that the invention aims to solve]

[0008] Furthermore, current pre-analysis and analyzer instruments generally process samples in a continuous stream when they are introduced into the system; that is, such systems process samples in a predetermined sequence typically set by the user. In this regard, existing pre-analysis instruments generally do not consider any information other than that provided by the user when determining which sample to prepare next in the sequence. Moreover, pre-analysis instruments typically prepare samples at a different rate than analyzer instruments, which further complicates the integration between pre-analysis and analyzer instruments. In this regard, technicians may need to constantly pay attention to the samples being prepared by the pre-analysis instrument until the entire batch of samples has accumulated for manual transfer to the analyzer instrument. Alternatively, the technician can transfer partial batches to the analyzer instrument, which is considered to reduce the productivity of the analyzer instrument. [Means for solving the problem]

[0009] Disclosed herein are systems and methods for performing assays on biological samples and for high-throughput automation of biological assays. In one embodiment, the system includes a memory for storing instructions and a processor programmed by instructions to perform a method comprising the steps of: receiving multiple assay instructions for multiple biological samples; determining multiple assays to be performed on each sample in the multiple biological samples based on the assay instructions; determining assay resources available for performing the multiple assays; determining the order in which to perform each assay in the multiple assays based on the assay resources available to maximize the efficiency of performing the multiple assays; and instructing one or more analyzer instruments to perform the multiple assays based on the determined order.

[0010] In one embodiment, the method includes the steps of: receiving multiple assay commands for multiple biological samples; determining multiple assays that need to be performed for each sample in the multiple biological samples based on the assay commands; determining assay resources available to perform the multiple assays; determining the order in which to perform each assay in the multiple assays based on the assay resources available to maximize the efficiency of performing the multiple assays; and commanding one or more analyzer instruments to perform the multiple assays based on the determined order.

[0011] In one embodiment, the system includes a memory for storing instructions and a processor programmed by instructions to perform a method comprising the steps of: receiving multiple assay instructions for multiple biological samples from multiple analytical systems; determining multiple assays that need to be performed on each sample in the multiple biological samples based on the assay instructions; identifying analytical systems available to perform each type of assay in the multiple assays; determining assay resources in the identified analytical systems that are available to perform the multiple assays; determining the order in which to perform each assay in the multiple assays based on the assay resources available to maximize the efficiency of performing the multiple assays; and instructing one or more analytical systems to perform a specific assay from the multiple assays based on the determined order.

[0012] In one embodiment, the system comprises a first automated module configured to prepare a biological sample for at least one molecular assay, and at least one second automated module for receiving the biological sample prepared by the first automated module and for performing a molecular assay on the received biological sample, wherein each of the first and second automated modules includes at least one automated instrument, and the system comprises a core computer device communicating with the first automated module, the second automated module, and a laboratory information system, the core computer device is The organizing core computer device receives commands from the analysis system for processing biological samples and manages the processing resources of the first and second automated devices. The organizing core computer device includes at least four processing layers, namely, a first layer which is a service level object layer and communicates with the analysis system, an organizing layer, an instrument module control layer, and an instrument module layer, the instrument module layer which communicates with automated instruments in the first and second automated devices, the status of the automated instruments being communicated to the organizing layer, and based on the current state of the analysis system, the organizing core computer device groups two or more biological samples into batches and communicates commands for batch processing of the samples to the instrument module layer. [Brief explanation of the drawing]

[0013] [Figure 1] This is a perspective view of an analytical system according to one embodiment described herein. [Figure 2A] This is a block diagram of an analysis-distributed system communicating with a laboratory information system according to one embodiment described herein. [Figure 2B] This is a block diagram of a centralized analysis system communicating with a laboratory information system according to one embodiment described herein. [Figure 3A] This is a block diagram of an organized core computer device architecture according to one embodiment described herein. [Figure 3B]This is a block diagram of an organized core computer device architecture according to another embodiment described herein. [Figure 4] This is a block diagram of the components of an organizational core application according to one embodiment described herein. [Figure 5A] This is a block diagram of a core application and sub-application for organization according to one embodiment described herein. [Figure 5B] This is a block diagram of a core application and sub-application of organization according to another embodiment described herein. [Figure 6-1] This figure shows one embodiment of the organizational core application described herein. [Figure 6-2] This figure shows one embodiment of the organizational core application described herein. [Figure 7] This is a diagram showing various instrument conditions related to the analysis system. [Figure 8] This is a diagram showing various instrument conditions related to the analysis system. [Figure 9] This is a block diagram showing exemplary assay states for analytical systems. [Figure 10] This is a flowchart illustrating an exemplary method for determining the sequence of assays or assay steps applied to a sample in order to maximize the operation within an analytical system. [Figure 11] This is an example block diagram for determining the sequence of assay steps for a sample to maximize performance within the analysis system. [Figure 12] This is a flowchart illustrating an exemplary method for determining the updated operating sequence of an assay or assay steps after accepting a new assay instruction into the analytical system. [Figure 13] This flowchart illustrates an exemplary method for determining the operation sequence and updated operation sequence of an assay or assay phase to maximize operational metrics. [Figure 14]A flowchart of another exemplary method for determining the order of operations of an assay or assay stage and an updated order of operations to maximize an operation metric. [Figure 15] A block diagram of an orchestration core application communicating with a hospital information system, a laboratory information system, and an analysis system over a network. [Figure 16] A schematic diagram of a cloud server-based orchestration core application communicating with an orchestration laboratory application to adjust automated sample processing and analysis.

Best Mode for Carrying Out the Invention

[0014] In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, like reference numerals typically identify like components unless the context dictates otherwise. The exemplary embodiments described in the detailed description, the drawings, and the claims are not meant to be limiting. Other embodiments may be utilized and other changes may be made without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that the aspects of the disclosure of the present invention as generally described and illustrated in the figures herein can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein and form a part of the disclosure herein.

[0015] overview The disclosure of this invention describes devices, systems, and methods for performing the processing and analysis of biological samples. In particular, it describes a system architecture for coordinating automated sample processing among multiple analytical devices or systems having a high degree of automation. Inputs from a laboratory information system are received by an organized computer device that coordinates the operation of one or more analyzer instruments and pre-analysis instruments to process samples in an informed and efficient manner in order to increase the overall efficiency of the stage in which assays are performed on multiple analytical systems and analyzer instruments (also called analyzers and assay devices). Various individual inputs into the organized computer device are envisioned, and the collection of inputs is designed to enable efficient and rapid sample processing with minimal operator input and involvement.

[0016] Sample processing and analysis system Figure 1 shows an exemplary analysis system 100. The analysis system 100 may be an in vitro diagnostic system or may include an in vitro diagnostic device. Such a system, as depicted, includes a pre-analysis instrument 104, a first analyzer instrument 108a, and a second analyzer instrument 108b. The pre-analysis instrument 104 may include a user interface 112 for receiving user input and an input window 116 for receiving a sample. Each of these units 104, 108a, and 108b is modular; that is, the pre-analysis instrument 104 can be coupled with one or more analyzer instruments. In addition, each analyzer instrument communicating with the pre-analysis instrument 104 (with respect to both exchanging information toward processing and exchanging samples) performs the same or different operations. For example, the first analyzer instrument 108a can perform viral assays such as human papillomavirus ("HPV") assays, while the second analyzer instrument 108b can perform bacterial and parasitic assays such as those for detecting Chlamydia trachoma, Neisseria gonorrhoeae, Trichomonas vaginalis, Group B Streptococcus, Enterobacteriaceae, and Intestinal Parasites. However, in some embodiments, the analysis system 100 can be configured such that the first and second analyzer instruments 108a, 108b are similar and capable of performing the same or similar assays. Such instrument modularity allows clinical laboratories to adapt the analysis system 100 to their specific needs. The analysis system 100 is referred to herein as an electronic system.

[0017] Each of the pre-analysis instrument 104 and analyzer instruments 108a, 108b has hardware components that cause them to perform specified operations. For example, in one embodiment, the pre-analysis instrument 104 may be configured to pre-process biological samples to prepare them for analysis by analyzer instruments 108a, 108b. In this regard, the pre-analysis instrument 104 may have a tray / shuttle handling robot that can transport a tray / shuttle of sample containers from one location within the instrument to another and to an adjacent analyzer instrument; a sample container handling robot that can transport individual sample containers and / or remove caps; a pipette robot that can draw a sample from one container into another; a diluent dispenser for diluting the sample; a vortexer for vortexing the sample; a hot plate for warming the sample; and a cooling unit for cooling the sample. The analyzer instruments 108a, 108b may also have robotic technology that can move containers within their individual instruments to and from the pre-analysis instrument 104. The analyzer instruments 108a and 108b may also include a pipette robot, a sample container handling robot, a magnetic extractor (for applying a magnetic field to the sample container (along with paramagnetic particles added to the sample) used for sample purification), and any other hardware components necessary to perform instrument operation.

[0018] In addition to the hardware components, the pre-analysis instrument 104 includes relay or storage areas. These areas are where sample containers and other consumables are stored until they are designated for inclusion in the workflow. These storage areas communicate with the organization core application so that the organization core application can assign processing information to the samples, and for this purpose the instrument can process the samples according to the instructions of the organization control application, as further described below.

[0019] Figure 2A is a block diagram of an analysis system communicating with a laboratory information system according to one embodiment described herein. In one embodiment, the analysis system 100 may include at least one pre-analysis instrument 104 and one or more automated analyzer instruments 108. The pre-analysis instrument 104 can process a sample for analysis by the analyzer instrument 104. The analyzer instrument 108 may be configured to perform an assay on a biological sample, while the pre-analysis instrument 104 may be configured to prepare a sample for analysis by the analyzer instrument 108. For example, the pre-analysis instrument 104 may transfer a biological sample from one container to another container suitable for use by the analyzer instrument 108, and may also vortex, pre-warm, and cool the sample depending on the assay being performed. Each of such analyzer instruments 108 and pre-analysis instruments 104 may be a modular, independent unit having robotic technology that can move biological samples back and forth between the individual units when coupled together.

[0020] The analysis system 100 can communicate with the laboratory information system 204 over the network 208. The laboratory information system 204 may be an existing information system operated by a medical facility or an independent clinical laboratory. Such a laboratory information system can provide the analysis system with information regarding the sample assay order 212, the requirements for the requested assay 216, and patient information. In some implementations, the analysis system 100 can receive patient information from the hospital information system.

[0021] The analysis system 100 may include an organization core application 220 executed by an organization core computer device 224 that communicates with analyzer instruments 108 and pre-analysis instruments 104 through an inter-instrument interface 228 and with the laboratory information system 204 through a network 208. The analysis system 100 may be behind a firewall or connected to the network 208 through another computer system to protect it from any accidental or malicious software that could interfere with or alter the operation of the analysis system 100 by isolating it.

[0022] The organization core application 220 can manage resources by coordinating processing among one or more analyzer instruments 108 and pre-analysis instruments 104 to achieve efficient use of available resources and keep the activity of these resources at or above predetermined threshold levels. The operation of the analysis system 100 can be determined based on an operational metric. For example, the operational metric may be the maximum utilization percentage of processing resources available to process a request at a given time. In addition, the organization core application 220 uses information received from the laboratory information system 204, analyzer instruments 108, and pre-analysis instruments 104 to reduce, significantly reduce, or even eliminate operator involvement and to make high-level judgments about the activities that will occur within each instrument based on constantly changing circumstances.

[0023] In one implementation, the computer devices 232 and 236 of the pre-analysis instrument 104 and analyzer instrument 108 execute the organization sub-applications 240 and 244. Such organization sub-applications 240 and 244 are linked to the organization core application 220 to execute instructions given by the organization core application 224. In this regard, judgments and instructions for executing such judgments are communicated from the organization core application 220 from top to bottom to specific hardware components that execute the ordered actions. These instructions become more specific as they move down the chain from the organization core application to individual hardware devices. Information is also communicated from individual hardware devices to the organization core application from bottom to top so that the organization core application frequently receives state updates that notify it of judgment decision processing.

[0024] The organizing core application 220 and organizing sub-applications 240, 244 may include state machines operating on their own threads. In this regard, the core application 220 and sub-applications 240, 244 may have lockdown states used for decision-making so that state changes do not interfere with decision-making processes.

[0025] The configuration core application 220 and configuration sub-applications 240, 244 operate to achieve efficient use of analyzer instrument 108 and pre-analysis instrument 104. The goal is to obtain a desirable utilization rate of hardware resources within such instruments, as idle time of system resources impairs overall operation.

[0026] The batching core application 220 makes decisions based on information from the laboratory information system 204 regarding the biological samples to be processed and evaluated by the pre-analysis instruments and analyzer instruments 104, 108. The batching core application 220 batches individual biological samples within the pre-analysis instrument 104, which helps to maximize overall throughput. Samples are placed in batches based on the identity of the processing conditions (e.g., thermal circulation conditions) for the samples in the batch. To the extent possible, each sample in a batch is subjected to the same processing conditions (e.g., temperature, light frequency). However, uniformity of processing is not required. For example, if the sample containers and control containers in a batch have already been pre-heated, these samples will not undergo the pre-heating step. That is, information about individual samples is not only "tracked" by the batching core application 220, but also information about the batches in which individual samples are processed. In other words, there is a "one-to-many" relationship between batches and samples. Some information is sample-specific, while other information applies uniformly to each sample in the batch.

[0027] In addition to performing batch processing of samples, the organizing core application 220 acquires a wealth of information input from various sources to control and adjust the processing resources 248, 252 of the pre-analytical instruments and analytical instruments 104, 108. Such information includes the inventory and allocation of inventory to processing in the queue of consumables 256, 260 for the instruments, the operating status of the instrument hardware, the assays requested to be performed on the samples, sample availability, i.e., batches already being processed, sample duration, and availability of the pre-analytical instruments and analytical instruments 104, 108, the availability of the instrument devices 264, 268 of the pre-analytical instruments and analytical instruments 104, 108, the biostability of the samples and reagents 272, 276, and specific laboratory business practices or compliance practices. Pre-analytical instruments and analytical instruments 104, 108 are also referred to as instrument devices. In one embodiment, the analysis system 100 includes redundant hardware and consumables so that the analysis system 100 can continue to operate while hardware is replaced and consumables are replenished.

[0028] The structuring core application 220 receives assay commands from various different external systems, such as the laboratory information system 204, the hospital information system, and other analytical systems. In some implementations, the pre-analysis instrument 104 knows exactly what to do with the sample when it arrives at the pre-analysis instrument 104. Decisions regarding the actual processing can largely be made in advance. That is, decisions regarding batching, timing, assay, and necessary consumable resources are all incorporated into the structuring core application 220 by the time the sample arrives at the pre-analysis instrument.

[0029] The organization core application 220 may include three components: an organization state component, an organization decision component, and an organization engine component. Each component has a clearly assigned role in managing the resources of the pre-analysis and analysis instrument devices 264, 268 and controlling their operation. The organization state component stores state information. The organization state component is configured to receive the operating status of the system's hardware and instrument devices 264, 268. Thus, each instrument and submodule within each instrument communicates and outputs information about its state, and this state information is communicated either directly to the organization state component or, more typically, through the logic unit of the applicable instrument. The organization decision component makes decisions using the state information. The organization engine component performs the decisions and protects the organization state component from being updated while the decisions are being made.

[0030] In this regard, the organization core application 220 tracks consumable inventory. Similarly, it is configured to determine what percentage of the consumable quantity is allocated to the batch being processed. Using such information, the organization core application 220 is configured to determine the net consumable inventory and to make processing flow decisions based on the net inventory to ensure that samples are not processed without consumable availability. Furthermore, the organization core application 220 is configured to notify the user when certain consumables need to be replenished in the instrument. Such consumables 256, 260 may include, to name a few, diluents, reagents, assay control samples, pipette tips, empty sample containers, extract containers, and PCR plates. Various sensors, such as a liquid level sensor for bulk diluents, can be implemented to track such consumables 256, 260. Similarly, the organization core application 220 can track the starting consumable inventory and how much of the consumables 256, 260 have been used from there to determine the net value.

[0031] The structuring core application 220 also tracks the operating status of the analyzer instrument 108 and the pre-analysis instrument 104 themselves. The structuring core application 220 determines which samples can be processed and, based on this information, when processing should begin. Instrument devices 264, 268 may include physical hardware components such as motor encoders, integrated circuits, and solenoids that help the structuring core application 220 track the operating status of the hardware within each instrument. One aspect of the operating status is whether or not there is a failure or error in the operation of a particular component. In such an event, the structuring core application 220 knows of redundant devices in the system and adjusts or activates such redundant devices in the event of a component operating error or failure. In this regard, the structuring core application 220 has a predetermined error protocol to be executed in the event of a component operating error or failure. Another function performed by the organization core application 220 is to understand the instruments, devices, and individual components required to process a given batch, and to understand both whether hardware components, pre-analysis instruments, and analyzer instruments are currently involved in or assigned to processing.

[0032] The organization core application 220 communicates with one or more information systems to obtain sample assay instructions 212. Such systems may include a hospital information system, a laboratory information system 204, an information processing system, and another analysis system. The organization core application 220 is configured to obtain the aforementioned information as early as possible so that decisions regarding sample processing can be made before the sample is actually scanned into the pre-analysis instrument 104. In this regard, the laboratory technician does not need to obtain sample assay request information, thereby reducing user error and freeing the technician to other tasks.

[0033] The Organization Core Application 220 is also configured to track the inventory of consumables such as assay controls and reagents, as well as the biological / chemical / mechanical lifespan of the samples themselves, at various stages of assay protocol execution. Exceeding the useful life limits of samples and consumables can adversely affect the integrity of assay results. Such lifespans shorten as time progresses, and the biochemical properties of reagents or samples may change if their duration exceeds a certain threshold. The Organization Core Application 220 can prioritize multiple samples to ensure the completion of the assay protocol before any reagents or samples exceed their lifespan.

[0034] The organization core application 220 can be further configured to receive information from the pre-analysis system and analysis systems 104, 108, which will enable tracking of these samples throughout the sample processing. This tracking stage includes tracking the sample processing and the sample transfer from one instrument to another, for example, from the pre-analysis instrument 104 to the analyzer instrument 108 (and vice versa), and dispensing into different containers. This allows the laboratory technician to query the system and instruments regarding the location of the sample and the progress of its assay. When multiple assays are requested for a single patient sample, the organization core application 220 coordinates and tracks the execution of multiple assays on the single sample without user intervention to maximize or at least increase the overall efficiency of the assay execution stage.

[0035] Figure 2B is a block diagram of a centralized analysis system 100b communicating with a laboratory information system according to one embodiment described herein. The analysis system 100b in Figure 2B is similar to the analysis system 100 described with reference to Figure 2A. As will be described in more detail below, the analysis system 100b in Figure 2B is a centralized system having the functions of the organization sub-applications 240b, 244b, which are carried out by the organization core computer device 224b.

[0036] In one embodiment, the analysis system 100b may include at least one pre-analysis instrument 104b and one or more automated analyzer instruments 108b. The pre-analysis instrument 104b can process a sample for analysis by the analyzer instrument 104b. The analyzer instrument 108b may be configured to perform an assay on a biological sample, while the pre-analysis instrument 104b may be configured to prepare a sample for analysis by the analyzer instrument 108b. The analysis system 100b may communicate with the laboratory information system 204b over the network 208b. The analysis system 100b may include an organized core application 220b executed by an organized core computer device 224b that communicates with the analyzer instrument 108b and the pre-analysis instrument 104b through an interface 228b such as an inter-instrument interface, an inter-device interface, or an intra-device interface. The analysis system 100b may communicate with the laboratory information system 204b through the network 208b. The organization core application 220b can manage resources by coordinating processing between one or more analyzer instruments 108b and pre-analysis instruments 104b to achieve efficient use of available resources and keep the activity of these resources at or above predetermined threshold levels.

[0037] The organization core computer device 224b executes organization sub-applications 240b and 244b. Such organization sub-applications 240b and 244b are linked to the organization core application 220b to carry out instructions given by the organization core application 220b. In this regard, decisions and instructions for carrying out such decisions are communicated from the organization core application 220b down to the organization sub-applications 240b and 244b and to specific hardware components that carry out the instructed actions. These instructions become more specific as they move down the chain from the organization core application 220b down to the organization sub-applications 240b and 244b and to the individual hardware devices. Information is also communicated from the individual hardware devices down to the organization core sub-applications 240b and 244b and to the organization core application 220b down so that the organization core application 224b and the sub-applications 240b and 244b frequently receive state updates that notify the decision processing.

[0038] The organizing core application 220b and organizing sub-applications 240b and 244b operate to achieve efficient use of analyzer instrument 108b and pre-analysis instrument 104b. The organizing core application 220b makes decisions based on information about biological samples from the laboratory information system 204b that are processed and evaluated by the pre-analysis instrument and analyzer instruments 104b and 108b. In addition to performing batch processing of samples, the organizing core application 220b acquires a wide range of information inputs from various sources to control and adjust the processing resources 248b and 252b of the pre-analysis instrument and analyzer instruments 104b and 108b. The organizing core application 220b receives assay commands from various different external systems such as the laboratory information system 204b, the hospital information system, and other analytical systems.

[0039] The organization core application 220b may include three components: an organization status component, an organization decision component, and an organization engine component. The organization core application 220b can track consumable inventory. The organization core application 220b also tracks the operating status of the analyzer instrument 108b and the pre-analysis instrument 104b themselves. The organization core application 220b can also be configured to track consumable inventory and the biological / chemical / mechanical lifespan of samples, such as assay controls and reagents, as well as the biological samples themselves, at various stages of assay protocol execution. The organization core application 220b can be further configured to receive information from the pre-analysis system and analysis systems 104b, 108b through the organization sub-applications 240b, 244b, which will enable tracking these samples throughout sample processing.

[0040] In the embodiment shown in Figure 2B, the organizing core application 220b, the organizing sub-application 240b, and the organizing sub-application 244b are illustrated as three components of the organizing core computer device 224b. However, this is illustrative only and not intended to be limiting. In another embodiment, the organizing core computer device 224b can implement the organizing core application 220b, which can implement the functions of the organizing sub-applications 240b and 244b. In one embodiment, the organizing core computer device 224b includes one organizing sub-application linked to the organizing core application 220b to implement instructions given by the organizing core application 220b.

[0041] Architecture of the core system for organization Figure 3 shows an organization core computer device architecture 300 according to an embodiment of the disclosure of the present invention that supports an analysis system 100, such as the analysis system 100 described with reference to Figure 2A. Generally, the architecture includes an organization core computer device 224 having a user interface such as a user interface 112 that allows a user to communicate with it. The organization core computer device 224 may include one or more code scanners 304 for reading sample identifiers (e.g., barcodes, QR codes®) on sample containers or sample racks. The organization core computer device 224 communicates with a pre-analysis instrument computer control device 232 of a pre-analysis instrument 104 and one or more analyzer computer control devices 236a1, 236a2 of analyzer instruments 108a, 108b (in this figure, two such control devices are shown, one for each analyzer instrument). As shown, the organization core computer device 224 is connected to a network 208, which is further connected to a laboratory information system 204 ("LIS"). LIS204 can be an existing general-purpose or dedicated system attached to a diagnostic laboratory or medical facility, particularly for storing and maintaining patient records and physician-requested assays. Network 208 enables the organization computer core device 224 to be communicatively coupled with LIS204 to share information between them. The organization computer core device 224 is also communicatively coupled with the instrument control devices 232, 236a1, and 236a2 of instruments 104, 108a, and 108b through the instrument-to-instrument interface 228. However, other interconnection mechanisms between the computer control devices 232, 236a1, and 236a2 and the organization computer core device 224 are envisioned to enable these devices to share information with the system.

[0042] In addition to being connected to the inter-instrument interface 228, the pre-analysis instrument computer control device 232 is also connected to the module interface 308 connected to the pre-analysis instrument device 264 of system 100, enabling the computer control device 232 to communicate with the pre-analysis instrument device 264. The pre-analysis instrument computer device 232 includes an application stored in the device's memory that gives the device's processor instructions, including the control of physical operations used for sample preparation and pretreatment within system 100. In this regard, the application helps the processor of the pre-analysis instrument computer control device 232 to control each instrument / device within the pre-analysis instrument module / device 264.

[0043] The analyzer computer devices 236a1 and 236a2 may each include a processor and memory. In addition to being connected to the inter-instrument interface 228, analyzer computer device 236a1 is connected to a module interface 312a1 connected to analyzer device 268a of analyzer instrument A1, enabling analyzer computer device 236a1 to communicate with analyzer device 268a. Analyzer computer device 236a1 includes applications stored in the device's memory that provide the device's processor with commands related to controlling the physical operation used for the analysis of samples provided to analyzer instrument A1 by system 100. In this regard, analyzer computer device 236a1, through its processor, assists in controlling each instrument / device within analyzer instrument A1. Analyzer computer device 236a2 is configured similarly with respect to its respective analyzer instrument.

[0044] In other words, as shown in Figure 3A, the organization core computer device 224 receives information from multiple inputs and distributes the information as needed. This allows the system 100 to be fully integrated with one or more analyzer instruments and an information sharing network, thereby enabling the system 100 to skillfully perform the preparation and pretreatment of multiple different samples contained in multiple different containers.

[0045] In another embodiment of architecture 300, the pre-analysis instrument computer device 232 or analyzer computer devices 236a1, 236a2 can also function as the organization core computer device 224.

[0046] Devices 232, 236a1, 236a2, the organization core computer device 224, and LIS 204 are each located on different nodes of network 208 and can communicate with each other directly or indirectly. However, as described, generally, the organization core computer device 224 acts as a control interface between LIS 204 and the computer devices 232, 236a1, 236a2 of the analyzer instruments 108a, 108b, and pre-analysis instrument 104. The computer devices 232, 236a1, 236a2 in network 208, the organization core computer device 224, and LIS can be interconnected using a variety of protocols and systems. Network 208 can utilize standard communication protocols such as Ethernet and Wi-Fi, as well as one or more enterprise-specific protocols, and various combinations thereof. Communication between the laboratory information system 204 and the analysis system 100 can be via a communication protocol such as Hypertext Transfer Protocol (HTTP). While certain advantages are obtained when information is transmitted or received as described above, the systems described herein are not limited to any particular communication protocol.

[0047] Figure 3B is a block diagram of the organization core computer device architecture 300b according to the embodiment described with reference to Figure 2B. The organization core computer device architecture 300b in Figure 3B is similar to the organization core computer device architecture 300b described with reference to Figure 3A. In Figure 2B, the analysis system 100b is a distributed system in which the functions of the organization sub-applications 240b, 244b are performed by the organization core computer device 224b rather than the pre-analysis instrument 104b and analyzer instrument 108b. Therefore, the organization core computer device 224b communicates with and / or controls the pre-analysis instrument device 264b and the analysis instrument devices 268b1, 268b2 through an interface 228b such as an inter-instrument interface, inter-device interface, or intra-device interface.

[0048] Organization of core application and sub-application status Figure 4 shows the state of the organization core application or sub-application. Figure 4 shows multiple communication interfaces 404a to 404c communicating bidirectionally with the inter-instrument interface 228. Each of these communication interfaces has a processor. These interfaces 404a to 404c are processors whose operation in the analysis systems 236a1, 236a2 and the pre-analysis system 232 is coordinated with the organization core computer device 224. Each of the communication interfaces 404a to 404c is for either the analyzer computer devices 236a1, 236a2 or the pre-analysis computer control device 232. In this regard, each computer device in 404a to 404c includes one or more processors, memory, and other components typically found in a general-purpose computer device.

[0049] Communication interfaces 404a to 404c transfer information regarding state changes within the analysis and pre-analysis instruments to the organization state component 408, which is part of the pre-analysis instrument computer device 232, or to either the analyzer computer device 236a1 or 236a2. The organization state component 408 communicates the state changes to the organization engine component 412 of the pre-analysis instrument computer device 232, or to either the analyzer computer device 236a1 or 236a2. The organization engine component 412 communicates bidirectionally to the organization decision component 416 of the pre-analysis instrument computer device 232, or to either the analyzer computer device 236a1 or 236a2. In response to a request from the organization engine component 412, the organization decision component 416 determines whether the organization engine component 412 sends commands to the analysis device and pre-analysis devices 108 and 104.

[0050] Each memory of the communication interfaces 404a to 404c can store information accessible by one or more processors, including instructions that can be executed by one or more processors. The aforementioned organization engine thread will run on any available processor core within the communication interfaces 404a to 404c. As described above, the organization engine component 412 requests a decision from the organization decision component 416. If a decision is returned, the organization engine component 412 sends an action to the appropriate communication interface 404a to 404c. When the communication interfaces 404a to 404c receive a message containing a state, they obtain the state from the organization engine component 412 and update the organization state component 408 with this new state. The new organization state in the organization state component 408 then triggers the organization engine component 412 to activate.

[0051] Memory includes data that can be retrieved, manipulated, or stored by the processor. Memory can be any non-temporary type that can store information accessible by the processor, such as hard drives, memory cards, ROMs, RAMs, DVDs, CD-ROMs, writable memory, and read-only memory.

[0052] Instructions can be a set of instructions that are executed directly by one or more processors, such as machine code, or instructions that are executed indirectly, such as scripts. In this regard, the terms “instruction,” “application,” “stage,” and “program” may be used interchangeably herein. Instructions can be stored in an object code format for direct processing by processors, or in any other computer device language, including a set of scripts or source code modules that are interpreted on demand or pre-compiled. The functions, methods, and routines of these instructions are described in more detail below.

[0053] The data can be retrieved, stored, or modified by one or more processors according to instructions. For example, the subject matter described herein is not limited to any particular data structure, but the data can be stored in computer registers, in relational databases as tables with many different fields and records or XML documents. The data can be formatted in any computer device-readable format, such as but not limited to binary values, ASCII, or Unicode. Furthermore, the data may include any information sufficient to identify related information, such as numbers, descriptive text, proprietary codes, pointers, reference symbols to other data stored in memory, such as locations on other networks, or information used by functions to compute related data.

[0054] The one or more processors implemented by each of the communication interfaces 232, 236a1, and 236a2 may be any conventional processor, such as a commercially available CPU. Alternatively, the processor may be a dedicated component, such as an application-specific integrated circuit ("ASIC") or another hardware-based processor.

[0055] In some embodiments, a processor or memory may actually include multiple processors and / or memory, which may or may not be housed in the same physical housing. For example, memory may be a hard drive or other storage medium located in a different housing from the processor. That is, references to processors, computer devices, or memory will be understood to include references to a collection of processors, computer devices, or memory that may or may not operate in parallel.

[0056] In the embodiment shown in Figure 2A, the analyzer computer devices 236a1, 236a2 and the pre-analysis computer device 232 are located within their respective instruments. The location of the organization core computer device 224 is largely a matter of design choice. As shown, the organization core computer device 224 can communicate with the code scanner 304 and the user interface 112 of the pre-analysis instrument 104 (Figure 2A). The code scanner 304 is located within the input window 116 of the pre-analysis instrument 104. In one embodiment, the user interface 112 is a touchscreen device mounted on the shell of the pre-analysis instrument 104 (shown in Figure 2A). However, it should be understood that the user interface 112 may include a mobile device that can wirelessly connect to the organization core computer device 224, for example, via Wi-Fi. As just one example, the user interface 112 may be a mobile phone or a wireless-enabled PDA, tablet PC, or netbook that can acquire information over the network 208. In another example, the organization device computer device 224 could be a desktop device located in a physical location separate from the analysis system 100.

[0057] Core Application for Organization As shown in Figure 4, the organization core application 220 includes components for information flow such as communication interfaces 404a-404c, organization decision component 416, organization engine component 412, and organization status component 408. The organization status component 408 receives and holds all information regarding the organization status (i.e., the sample processing and analysis status for system 100, including the pre-analysis system and the analysis system). The organization decision component 416 implements an algorithm that determines the next action to take based on the organization status received from the organization status component 408. The communication interfaces 404a-404c are tasked with processing information used to update the organization status arriving from the analysis and pre-analysis instruments.

[0058] The train formation engine component 412 provides protected access to the train formation state, activates the train formation decision component 416, and executes the decisions made by the train formation decision component 416 in the form of instructions delivered to computer devices 232, 236a1, and 236a2. As described above, the train formation core application 220 is a state machine; that is, state changes that occur during the decision-making process invalidate the decisions. The train formation engine component 412 provides protected access to the train formation state component 408 while the decisions are being made, so that these decisions made by the train formation core application 220 are atomic decisions (one decision at a time).

[0059] In one embodiment, to ensure that such a decision is atomic, the organization engine component 412 is configured to run on its own thread and implement one or more strategies to prevent state updates during the decision-making process. In other embodiments, the thread is not configurable during execution. For example, in one embodiment, the organization engine component 412 is configured to lock the organization state while a copy of the organization state is generated. Such a copy of the organization state is used for the decision-making process. This enables a lock on the organization state that will be applied over a short period of time, limiting the opportunity for race conditions that may occur when multiple state data change during the decision-making process. For example, at the start of the decision there is one batch and 30 patient samples, and at the end of the decision there are two batches and 60 samples. Both of these states are consistent. If the organization state is not controlled by the organization engine component 412, an inconsistent state of one batch and 60 samples may be observed, i.e., an "invalid" decision may be made.

[0060] In another embodiment, the formation engine component 412 may be configured to first determine which action to perform, and then to execute this action. Furthermore, the formation engine component 412 may be configured to apply a lock to the formation state during the decision-making process. This configuration can allow the lock to be applied for a short period of time, assuming that the decision regarding which action to perform is made quickly. A slow decision may delay processing and prevent the state from being updated.

[0061] In yet another embodiment, all state changes are automatically placed into a queue. The train formation engine component 412 can be configured to wake up from a standby state and, for example, exit a standby or dormant state to process each of the changes in the queue. With the queue empty, the train formation engine component 412 can then be configured to activate the train formation decision-maker component 416 to perform a decision.

[0062] In another embodiment, an organization core application 220, which can be implemented by the organization core computer device 224, is configured to apply a lock to the entire organization engine component 412 and organization state component 408. The lock is released when the organization engine component 412 is in a standby state, thereby indicating that all activities associated with the lockdown state have been completed. In this embodiment, the lock can be held for a longer period of time to prevent other threads from executing while the organization engine component 412 is busy. Due to the longer lock, the likelihood of race conditions is higher.

[0063] Organization Sub-Application System As depicted in Figure 5A, analyzer instruments 108a1 and 108a2, as well as pre-analysis instrument 104, include organization sub-applications 240, 244a1, and 244a2. These applications 240, 244a1, and 244a2 are stored in the respective memories of computer devices 232, 236a1, and 236a2, and provide instructions to the processors of these computer devices, including the coordination and control of hardware devices such as the aforementioned hardware devices in units 104, 108a1, and 108a2. The organization subsystems 240, 244a1, and 244a2 are communication links between the organization core application 220 and the individual components / subsystems / hardware within instruments 104, 108a1, and 108a2. In this regard, sub-applications 240, 244a1, and 244a2 assist in executing instructions given by the organizing core application 220, giving modularity to each instrument 104, 108a1, and 108a2. That is, as shown in the figure, instructions flow from the organizing core application 220 to the individual devices of instruments 104, 108a1, and 108a2. Such general instructions are translated into target actions by the individual devices through delegation programming as they are communicated toward the hardware devices. For example, when the pre-analysis instrument 104 accepts a rack of samples, one or more of the organizing sub-applications 240 issue specific instructions to a specific device 264 to bring about the tasks necessary to support the step of accepting the rack of samples into the pre-analysis instrument 104. In this regard, information flows from the individual device 264 to the organizing core application 220. Such information may include the operating status of device 264, the current level of consumables, and the location of a particular sample. This pyramidal structure allows the organizational core application 220 to focus on high-level decision-making and information gathering.

[0064] The organization sub-applications 240, 244a1, and 244a2 can be configured, like the organization core application 220, to coordinate activities among various devices within each unit 104, 108a1, and 108a2, and even through units 104, 108a1, and 108a2. For example, the conveyor manager sub-application for the pre-analysis instrument 104 and the robot arm manager sub-application for the second analyzer instrument 108a2 can coordinate the availability and operation of their respective conveyors and robot arms to hand over sample containers from the conveyor of the pre-analysis instrument 104 to the robot arm of the analyzer instrument 108a2.

[0065] Furthermore, sub-applications 240, 244a1, and 244a2 can be state machines operating on their own threads. For example, the pre-analysis instrument 104 may have a rack manager sub-application, which is a state machine operating on its own thread. The rack manager sub-application may be responsible for coordinating the activity of moving sample racks through the pre-analysis instrument 104. For example, the rack manager sub-application may maintain and make decisions about rack objects based on rack state values ​​assigned to rack objects, which can be a single list indicating where the racks are and what operations are being performed on the racks. Such decisions may include which sample racks are being moved and where they are being moved to. Furthermore, the rack manager sub-application may coordinate the handover of racks to other components or stations, such as a sample transfer station or rack elevator, within the pre-analysis instrument 104.

[0066] However, since the rack manager sub-application is a state machine, state changes occurring during decision processing invalidate the decision. To ensure that such decisions are atomic, the rack manager sub-application is configured to implement one or more strategies to prevent state updates during decision processing. For example, in one embodiment, the rack manager sub-application is configured to apply a lock to the rack state while a copy of the rack state is being generated. Such a copy is used for decision processing. This allows the lock to be applied for a short period of time, limiting the opportunity for race conditions.

[0067] Figure 5B is a block diagram of the Organizing Core Application and Organizing Sub-Applications of the centralized analysis system described with reference to Figures 2B and 3B. As depicted in Figure 5B, the Organizing subsystems 240b, 244b1, and 244b2 are communication links between the Organizing Core Application 220b and the individual components / subsystems / hardware within the instruments 104b, 108b1, and 108b2. The Organizing Sub-Applications 240b, 244b1, and 244b2 can be configured to coordinate activity between various devices within each unit 104b, 108b1, and 108b2, and even through the units 104b, 108b1, and 108b2, just like the Organizing Core Application 220b. The Sub-Applications 240b, 244b1, and 244b2 can be state machines operating on their own threads. The Core Application 220b can be a state machine operating on its own thread.

[0068] Multi-layered core application architecture Figures 6-1 and 6-2 show the architecture for an organizing core application 220 having a multi-instrument service layer 610, an organizing layer 620, and an instrument module layer 630, as illustrated. Each layer is assembled from multiple system user objects, each encapsulating a distinct user operation category. The multiple system user objects favorably include a service level object layer 610, which includes a module service base module 614 for the system shown in Figures 6-1 and 6-2. The service level object layer 610 is part of the organizing layer 620, the instrument module control layer 630, and an organizing control application service module 612 that communicates with modules in the instrument module layer 650. The organizing control application service module 612 communicates with a module 646 that requests sample information, a module 642 that coordinates batches, a module 636 that manages module registration, and a module 632 that updates the inventory context. The configuration control application service module 612 communicates with other modules within its layer (i.e., with the module service base module 614, and further with the service base module 616 through the module service base module 614).

[0069] In one embodiment, the organization engine module (or component) 624 communicates with the module service base module 614, which also receives commands from the organization control application service module 612. The organization engine module 624 obtains the organization status from the organization status module 622. The organization status module 622 receives status information from all modules in layer 630 and, indirectly, from all modules in layer 650. These modules are the inventory status updater module 632, the available consumable assay module 634, the module registration manager 636, the module status module 638, the batch module 540, the batch adjustment module 642, the sample module 644, and the sample information request module 646. In response to a request from the organization engine module 624, the organization decision module 626 determines whether the organization engine module 624 should send commands to other modules.

[0070] The sample information request module 646 communicates with the instrument registration module 658 to issue commands regarding the registration and tracking of individual samples within the instrument and to obtain information. In one embodiment, sample information is obtained by reading the sample code on the sample container received by the instrument. The sample code on the transport container is further registered to identify and track the transport container within the instrument. Note that the organization control application service module 612 initiates a sample information request from the sample request module 646, resulting in the instrument registration module 658 obtaining information about the sample container and transport container. With the sample information obtained, the sample information in the sample information module 644 is updated. The updated sample information is communicated to the organization status module 622.

[0071] Layer 630 has a module 642 that adjusts batches by communicating with an instrument batch adjustment module 656 in the instrument. Through the interface with the batch adjustment module in layer 630, the instrument batch adjustment module 656 loads samples into the shuttle that have been designated by the formation control application service module 612 to be in the same batch. Furthermore, the batch adjustment module 642 gives the instrument batch adjustment module 656 commands to start the batch handler device in the instrument batch adjustment module 656 and for the instrument batch adjustment module 656 to start transporting the shuttle. The batch adjustment module 642 communicates with the formation status module 622 and together with the batch module 640 (the batch module 640 also communicates with the formation status module 622).

[0072] Layer 630 further includes a module 640 that communicates module status to the organization status module 622. The module status module 638 obtains information from a module registration manager 636 that receives commands and instructions from the organization control application service module 612 in layer 610. The module registration manager 636 also communicates information to the organization status module 622. Based on commands from the organization control application service module 612, the module registration manager 636 communicates with the instrument device registration module 654.

[0073] As described above, layer 630 has a module 632 that updates the inventory status. The inventory status module 632 receives an instantiation command from the organization control application service module 612 and updates the organization status module 622 using one of the status updates. The inventory status update module 632 controls the inventory module 652 in the pre-analysis instrument to acquire various information about the status of consumables in the instrument. This information includes inventory information regarding available consumables, taking out consumables as needed, securing consumables, restoring consumables, and replacing inventory.

[0074] In another embodiment, the rack manager sub-application can be configured to first determine the action to be performed and then execute such action. Furthermore, the rack manager sub-application can be configured to apply a lock to the rack state during the decision-making process. This configuration can allow the lock to be applied for a short period of time, assuming that the decision on which action to perform is made quickly.

[0075] In yet another embodiment, all rack state changes are automatically placed into a queue. The rack manager sub-application can be configured to wake up from a waiting state and process each change in the queue. The rack manager sub-application can be configured to make decisions when the queue is empty.

[0076] In yet another embodiment, the rack manager sub-application can be configured to apply locks through the rack manager sub-application. The lock is released when the rack manager sub-application is in a standby state, thereby indicating that all activities associated with the lockdown state have been completed.

[0077] Instrument and assay status In one embodiment, the instrument is given a predetermined state. For example, the instrument state can be defined as shown in Table 1. [Table 1]

[0078] Refer to Figures 7 and 8 to see the commands that change one state to another. For example, when an instrument is powered off, a command to power it on will change the state to "offline idle". The offline idle state can also be changed to "offline busy" when an offline procedure (e.g., instrument service, software update) is being performed, in which case the offline idle state will be maintained until the offline procedure is completed. A command to bring the instrument online will change the state to online idle if there is no offline procedure preventing the state from changing from offline idle to online idle. In the online idle state, the instrument can be commanded to start a procedure. Upon completion, the instrument returns to the online idle state. If the instrument is paused during execution (paused busy), this state returns to online busy, and a new procedure cannot be started until the procedure is completed. When an instrument is in the online idle state, it remains available to receive commands for further activities unless it enters a paused idle state where it cannot start a new procedure or receives a command to take the instrument offline.

[0079] The system also has defined assay states. In one embodiment, the assay may have one of the states shown in Table 2 below. [Table 2]

[0080] Figure 9 illustrates how the status of a particular assay is stored. When the assay status is "Not Available," local rules apply to this assay, resulting in an "Unqualified" status where, although it allows the assay to be performed, the assay results are not patient-eligible. To achieve eligibility, the performed assay is validated. If the status is "Eligible," but a new version of the assay is released, the old version of the assay is performed until the new version becomes eligible.

[0081] Determination of assay or assay step sequence The organization core application 220 can determine the operation sequence of an assay or assay steps based on the accepted sample, the requested assay, and the availability of resources 248, 252. Figure 10 is a block diagram of a non-limiting exemplary method 1000 for determining the operation sequence of an assay or assay steps for a sample to maximize operation. In one embodiment, the organization core application 220 can implement method 1000 or a part thereof. After starting in block 1004, in block 1008, method 1000 receives scanned sample codes. For example, after a rack of samples in a container arrives at the input window 116 of the analysis system 100, the code scanner 304 of the analysis system 100 may scan sample identifiers such as barcodes and 2D codes attached to the sample containers. Method 1000 can receive scanned sample codes scanned by scanner 304. In determination block 1012, if scanner 304 scans and receives additional sample codes, method 1000 can return to block 1008 to receive additional sample codes. The additional sample codes may come from the same sample rack or a different sample rack that the analysis system 100 has received.

[0082] In decision block 1012, if no additional sample codes are scanned and received, method 1000 may proceed to block 1016, where it determines which assays to be performed on the accepted and scanned samples. For example, method 1000 may receive assay instructions for accepted and scanned samples from the laboratory information system 204 or the hospital information system. Method 1000 may determine which assays to be performed on the samples based on the sample identity determined from the sample code and assay instructions. For example, a physician may request three tests A, B, and C for a patient, and a container containing the patient's sample may have a sample code 123456 attached to it. After receiving sample code 123456, method 1000 determines the identity of the sample (i.e., the patient's sample) and determines that the physician requested or ordered three assays for the patient.

[0083] Method 1000 proceeds to judgment block 1020, where it is determined whether the conditions of each sample meet the requirements of one or more assays requested for the sample. Sample conditions can be sample volume, sample duration, and sample quality (e.g., sample opacity). For example, three assays A, B, and C requested by a physician for a patient require 1 ml, 5 ml, and 10 ml, respectively. However, the volume of the patient's sample determined by the pre-analytical instrument 104 may be only 15 ml. That is, the volume of the patient's sample is not sufficient for all three assays, and therefore does not meet the overall requirements of the three requested assays. If the sample does not meet the requirements of one or more requested assays, Method 1000 proceeds to block 1024, where it is notified that the sample conditions do not meet the requirements of the requested assays. For example, the organization core application 220 can display an error message using the user interface 112 of the analysis system 100. Next, method 1000 terminates at block 1028.

[0084] In some implementations, assay instructions for a sample may include a priority order for the assays to be performed. Method 1000 can determine which assays to perform on a sample even if the sample conditions do not meet the requirements for all assays requested for the sample. For example, assay instructions for a patient sample may indicate that the results of assays A and B can only be interpreted in relation to each other. The assay instructions may also indicate that assay A is more important than assay C. That is, Method 1000 can inform the user that assays A and B will be performed, proceeding from block 1020, and assay C will not be performed. In some implementations, Method 1000 may display the possible assays that can be performed on the sample and request user input regarding which assays to perform.

[0085] In decision block 1020, if the sample conditions meet the requirements of the requested assay, method 1000 proceeds to decision block 1032, where it determines whether the analytical system 100, including the pre-analytical instrument 104 and the analyzer instrument 108, has sufficient resources to perform all the requested assays. If the analytical system 100 does not have sufficient resources, method 1000 proceeds to block 1024, where the user is notified that the analytical system 100 does not have sufficient resources to perform the requested assays. Next, method 1000 proceeds to block 1028, where it terminates. For example, pre-analytical instrument 104 may need to dispense a patient's sample from a sample container into three smaller containers. However, pre-analytical instrument 104 may be out of pipette tips or may only have two smaller containers. Method 1000 can notify the user through the user interface 112 that the user needs to stock more pipette tips and containers in pre-analytical instrument 104.

[0086] Table 3 shows exemplary resources of the analysis system 100 that may require limited access, such that each resource can only be used for the preparation or analysis of one sample or one sample batch. Some of these resources can be started automatically by the analysis system 100. Some of these resources may require specific user initiation or user action, perhaps after the analysis system 100 presents the user with options for selection. For example, the user can start the waste container emptying phase of the analysis system 100. As another example, during routine maintenance, the analysis system 100 may pause until the user is aware that the extraction area has been cleaned. Table 4 shows additional exemplary resources of the analysis system 100. [Table 3] [Table 4]

[0087] In one implementation, method 1000 determines a combination of assays that can be performed assuming a shortage of system resources, and allows the user to decide which assays to perform. In another implementation, the assay command may include a priority order for assays and samples, thereby allowing method 1000 to notify the user of the shortage of system resources and proceed from decision block 1032 to perform the assays based on the priority order for assays and samples.

[0088] In decision block 1032, if the analytical system 100 contains sufficient resources, method 1000 proceeds to block 1036, where it is determined which assay steps or assays the analytical system 100 can perform simultaneously. For example, if assays A and B requested for a patient require heating to 65°C and 95°C respectively, and the analyzer instrument 108 contains only one heating plate for heating the sample, these two steps cannot be performed simultaneously. However, if the analyzer instrument 108 contains two or more heating plates, these two assay steps can be performed simultaneously.

[0089] Method 1000 proceeds to decision block 1040 to determine whether the assay command includes any special commands. For example, a special command may state that an assay command for a particular patient is an urgent command and has the highest priority. As another example, a special command may indicate that two assays will either be performed together or neither will be performed (perhaps because the results of the assays for the patient need to be interpreted in relation to each other). If there are no special commands, Method 1000 proceeds to block 1044 to determine the operation sequence to maximize the operation metric. The operation metric may be based on one or more factors such as the duration to perform all assays, the energy used to perform all assays, and the quality or precision of the assay results. The operation sequence may be affected by scheduled events. For example, scheduled events may be routine maintenance, scheduled firmware or software updates, scheduled hardware updates, and scheduled power outages. The operation sequence may be affected by the physical or logical configuration of the components of the analysis system 100. For example, the sequence of operations may be affected by the physical or local configuration of the pre-analysis instrument 104, analyzer instrument 108, and electronic instruments 264, 268. The sequence of operations may be affected by the type of sample container or other object that identifies elements of the sample. For example, the container containing the accepted sample may not be suitable for the type of assay requested for the sample. The sequence of operations may include a step of transferring the sample from the accepted sample container to a more suitable sample container. Method 1000 can be terminated in block 1028.

[0090] In decision block 1040, if the assay command includes special commands, method 1000 proceeds to block 1048 to determine the sequence of assay operations to be performed when special commands take precedence while maximizing the operation metric. For example, if an assay request for a patient is an urgent request, method 1000 can determine a sequence of operations that maximizes the operation of assays other than those for urgent commands. In some embodiments, assay operations are minimized unless all urgent commands are performed first. Method 1000 then terminates in block 1028.

[0091] Exemplary ordering Figure 11 is a schematic diagram of a non-limiting example of steps for determining the order in which assay steps are performed on a sample to maximize performance. The analytical system 100 may include three resources A, B, and C. The three resources may be, for example, a vortexer, a pipette, and a hot plate. Assays 1, 2, and 3 require the use of these three resources in the order A, B, and C, A, C, and B, and B, A, and C. To maximize performance, assay steps for various assays that require the same resources can be batched with each other. Figure 11 shows possible orders of assay steps. As shown in Figure 11, order (1) requires a longer run time compared to orders (2) and (3). However, order (1) can maximize the performance metric when the urgent command includes assay 1. In Figure 11, assay steps that require resource B can be batched to minimize total run time while performing the urgent command first.

[0092] It has been shown that operation sequences (2) and (3) require the same execution time. If the operation metric is time-based and the assay steps requiring resources A, B, and C must be performed sequentially, the operation sequence that maximizes the operation metric can be operation sequence (2). If the operation metric is energy-based and resource B uses more energy than resource C, the operation sequence that maximizes the operation metric can be operation sequence (3).

[0093] Determination of updated assays or assay step sequences After the organizing core application 220 has determined the operating sequence, the analysis system 100 may receive a new assay command from the laboratory information system 204 or the hospital information system before the assay is completed on the sample. The new assay command may be received after or before the analysis system 100 has started the stage of processing and analyzing the sample. Figure 12 is a block diagram of a non-limiting exemplary method 1200 that determines the updated operating sequence of an assay or assay stage after receiving a new assay command. In one implementation, the organizing core application 220 may implement method 1200 or a part thereof. After starting at block 1204, method 1200 proceeds to block 1208, where the organizing core application 220 determines the operating sequence of the assay requested on the sample. The organizing core application 220 may determine the operating sequence of an assay based on method 1000 described with reference to Figure 10.

[0094] Method 1200 proceeds to block 1212 and receives a new assay command. For example, the organization core application 220 may receive a new assay command from the laboratory information system 204 via the network 208. The received new assay command may be for a new sample or an existing sample. For example, the new assay command may be for an existing sample that the analytical system 100 has previously accepted and scanned. When the new assay command is received, the analytical system 100 may be in the process of performing one or more assays that have already been requested for this sample, or it may be waiting for instrument devices 264, 268 to become available before performing one or more assays that have already been requested for this sample. As another example, the new assay command may be for a sample 100 that has never been accepted and scanned.

[0095] Method 1200 proceeds to decision block 1216 to determine whether the new assay command is for an existing sample or a new sample. If the new assay command is for a new sample, Method 1200 proceeds to block 1220, where the organizing core application 220 receives a new sample identifier, such as a barcode or 2D code. For example, the analysis system 100 may accept the new sample through the input window 116 of the analysis system. The organizing core application 220 may receive the sample code scanned using the code scanner 304. After receiving the new sample code, Method 1200 proceeds to block 1124, where the organizing core application 220 can determine a new operation sequence. The new operation sequence may be based on an assay or assay step that can be performed by the analysis system 100 in relation to the assay or assay step currently being performed. Table 5 shows four states regarding assays or assay steps that can be performed simultaneously in relation to other assays or assay steps currently being performed. The most limited assay or assay step currently being performed may affect the planned assay or assay step. In some embodiments, the most restrictive assay or assay step currently being performed determines the assay or assay step that can be performed. The four states in Table 5 are ordered from least restrictive to most restrictive. The least restrictive state is the most expensive to perform in terms of the resources of the analytical system 100. [Table 5]

[0096] In decision block 1216, if the new assay instruction is for a new sample, method 1200 proceeds to block 1220, where the organizing core application 220 can determine the new operation sequence. The organizing core application 220 can determine the new operation sequence of the assay based on method 1000 as described with reference to Figure 10. This method terminates in block 1228. The determined new operation sequence can maximize operational metrics such as time or energy required to complete the assay or assay priority.

[0097] In one embodiment, Method 1200 can determine a new operating sequence for existing and new samples before receiving a new sample code in block 1120. Method 1200 can continuously determine the new operating sequence until it receives a new sample code. That is, the analysis system 100 accepts the new sample, and Method 1200 can continue performing the assay to maximize operation without requiring any time delay to determine the new operating sequence.

[0098] Determination of the sequence of operations in an assay or assay steps. The organizing core application 220 can determine the sequence of operations for an assay or assay steps based on the accepted sample, the requested assay, the availability of resources 248, 252, and the operating status of electronic instruments 264, 268. Figure 13 is a flowchart of one exemplary method 1300 for determining the sequence of operations for an assay or assay steps and an updated sequence of operations to maximize one or more operational metrics. In one embodiment, the organizing core application 220 can perform method 1300 or a part thereof. After starting in block 1304, method 1300 proceeds to block 1308, where the organizing core application 220 receives an assay command for one or more subject biological samples, such as a patient. The assay command may include steps for performing one or more assays for each of the one or more biological samples. For example, the assay command may include steps for performing a total blood count (CBC), blood chemistry tests, blood enzyme tests, and blood tests to assess the risk of cardiovascular disease in the subject's sample, as well as steps for performing blood tests to assess the risk of cardiovascular disease. The configuration core application 220 can receive assay commands from a command provider, such as a healthcare provider or laboratory staff, for example, a laboratory technician.

[0099] After receiving an assay command, method 1300 proceeds to block 1312, where the organized core application 220 determines, based on the assay command, which assay to be performed on the biological sample on the electronic instruments 264, 268. The step of determining which assay to perform may include retrieving assay-related information from the laboratory information management system database.

[0100] Method 1300 proceeds from block 1312 to block 1316, where the organized core application 220 determines the available assay resources and the operating status of electronic instruments 264, 268. Assay resources may include diluents, reagents, assay control samples, pipette tips, sample tubes, extraction tubes, polymerase chain reaction (PCR) plates, available space in waste containers, or any combination thereof.

[0101] In block 1320, the organizing core application 220 can determine the operating sequence for an assay. For example, the operating sequence may be based on the available assay resources and the operating status of the electronic instruments 264 and 268 determined in block 1316. The organizing core application 220 can determine the operating sequence to maximize one or more operating metrics of the analytical system 100. In one implementation, the organizing core application 220 can optionally receive a sample scanning code to determine the accepted sample and further determine the operating sequence for the accepted sample.

[0102] The operational metrics for the electronic system can include, or be determined based on, the number of valid assay results per period. The number of valid assay results can be determined based on the biochemical stability of the biological sample and the biochemical stability of the assay resources per period (e.g., one 8-hour shift, 24 periods, one week, or longer). For example, the operational metrics can be determined based on the number of available assay results per period. For example, the number of valid assay results can be optimized or maximized to ensure the generation of assay results before end-of-period biochemical stability. Performing all stages of an assay performed on a biological sample does not guarantee clinically favorable results. Various factors may invalidate the results. For example, the Organization Core Application 220 can track the biochemical lifetime of stock and samples under various conditions of assay protocol execution. Exceeding these lifetime limits may result in inconclusive assay results, i.e., reduced machine throughput. Specifically, the Organization Core Application 220 can track the viability of patient samples, assay controls, assay reagents, etc. These lifetimes change as assays are performed and the biochemical properties of the sample are altered by the assay stages. The organized core application 220 can be planned to ensure the completion of all assays or assay stages after initiation and before the effectiveness of the patient samples expires.

[0103] The operational metric may include the number of biological samples examined per unit period. For example, the primary metric could be the number of samples examined per period, e.g., the number of samples examined per day. The organizing core application 220 can attempt to keep all analysis modules 268 and submodules and pre-analysis modules 264 and submodules busy. Full utilization of these hardware resources can enable the system to achieve its maximum throughput. Idle time in any module or submodule can negatively impact overall operation.

[0104] In one implementation, the operational metric includes the labor or time required of laboratory staff to operate the analysis system 100 per unit period. The organization core application 220 can track samples throughout their processing. The organization core application 220 can track samples across transfers to different containers and across different modules, namely the analysis module, analysis submodules, and pre-analysis modules. That is, laboratory staff can be freed from this role and human error can be eliminated from the series of processes. Furthermore, laboratory staff can inquire about the location of patient samples and the progress of assays. If multiple assays are requested for a single patient sample, the organization can coordinate and track the execution of multiple assays without requiring the involvement of laboratory staff. The operational metric may include the maximum amount of time the electronic system does not require input from laboratory staff, and / or the minimum number of times the electronic system requires input from laboratory staff per period. For example, the operational metric may be determined based on the maximum time allowed before the user has to return to the system, and the minimum number of times the user must return to the system within a given period.

[0105] The required effort can be determined based on the number of electronic system interruptions per period. For example, a second important metric used by the system could be the effort required to operate the analytical system 100. The analytical system 100 can be designed to minimize the number of interruptions for laboratory staff per shift. By grouping the amount of manual work, interruptions to specific laboratory functions can be minimized. This balances achieving the highest throughput, which may require operators to stock and prepare instruments for a larger number of assays.

[0106] The operational metric can be determined based on one or more predetermined conditions, such as the urgency of the assay, the subject profile, the identity of the commander, or a combination thereof. These conditions can determine the urgency of the assay as specified by the service level agreement. The urgency of the assay to be performed or the test to be completed may be from a clinical perspective, such as urgency in patient management. As another example, the urgency of the assay to be performed can be determined based on the patient profile, such as the patient's demographic characteristics, and the statistical attributes of the assay and subject. For example, the urgency of the assay to be performed may be influenced by the laboratory's operational processes that operate the system and the need to satisfy the service level agreement between the laboratory and the commander, such as the laboratory customer. As yet another example, the condition may be a one-off event, such as a sample being temporarily misplaced by laboratory staff.

[0107] In one embodiment, the operational metric includes a weighted matrix having the number of valid assay results per unit period, the number of biological samples tested per unit period, the effort required to operate the electronic system per unit period, and / or other variables or factors disclosed herein, weighted in ascending or descending order. In one embodiment, the operational metric includes metrics corresponding to the duration of the assay, the priority of biological samples, the biochemical stability of each biological sample, the status of the electronic instruments, the simultaneity of multiple assay resources required to perform multiple assays, or any combination thereof. In another embodiment, the operational metric reflects predetermined guidelines for samples and assays. For example, an assay command may include parameters such as result urgency, sample expiration date, and user-defined parameters. The operational metric may reflect such parameters. Laboratory personnel can change the priority of individual samples or sample groups to be processed.

[0108] The step of determining the order of operations may include determining the order of operations for one or more assays based on available assay resources. The organized core application may take into account available inventory, the operating status of hardware components, patient-requested assays, sample availability, sample duration, batches already being processed, the availability of analytical modules, analytical submodules, and pre-analysis modules, biochemical stability, and / or laboratory operational practices. Efficient organization can minimize consumable consumption, idle analytical modules, analytical submodules, and pre-analysis modules, and uncertain results.

[0109] The step of determining the order of operations may include organizing multiple biological samples into multiple sample batches. Electronic instruments can be configured to process sample batches simultaneously. Assay resources can be configured so that electronic instruments process sample batches simultaneously. For example, in a thermal circulation assay, similar assays are required because all samples are exposed to the same temperature changes and cycles. That is, samples can be organized into batches. Consumables and instrument devices 264, 268 can be designed to process samples in individual batch sizes for each assay. For example, instrument devices 264, 268 can be designed to process 96 samples in a 96-well plate format. That is, to maximize overall throughput, each patch for an assay must contain 96 samples.

[0110] In block 1324, the Organization Core Application 220 can allocate assay resources to the assays being performed. The Organization Core Application 220 can track available assay resources and notify laboratory staff when assay resources are unavailable or are expected to become unavailable. For example, the Organization Core Application 220 can track the current consumable inventory levels within each analysis module and pre-analysis module. The Organization Core Application 220 knows the quantities already allocated to the batch being processed. The Organization Core Application 220 knows the quantities of consumable inventory required for each assay type batch. This knowledge enables the Organization Core Application 220 to make decisions about which samples to process and when to start processing.

[0111] After allocating assay resources, method 1300 proceeds to block 1328, where the organized core application 220 can configure electronic instruments 264, 268 based on the operating sequence determined in block 1320. For example, the organized core application 220 can schedule electronic instruments 264, 268 to perform assays based on the operating sequence determined in block 1320.

[0112] In block 1332, the analytical system 100 can perform assays on biological samples using electronic instruments configured based on the operating sequence. The configuration core application 220 can track the operating status of electronic instruments 264 and 268 while the assay is being performed. Modular assay instruments are complex machines. Electrical, mechanical, and pneumatic systems can fail. To achieve the highest sample metric per day, the configuration core application 220 can monitor the health of the instruments, and the execution of the assay is adapted to the operational hardware. For example, the configuration core application 220 can monitor the operating status of electronic instruments 264 and 268. The operating status of electronic instruments 264 and 268 can include fault status, offline status, online status, paused status, power-off status, busy status, idle status, or any combination thereof. The configuration core application 220 can notify laboratory staff of the fault status when it determines or receives an indication that the operating status of one of the electronic instruments 264 or 268 is in fault status.

[0113] Alternatively, or in addition to the above, the organized core application 220 can notify laboratory staff when and what is being replenished in stock within the analytical system 100. Stock items include diluents, reagents, assay control samples, pipette tips, sample tubes, extraction tubes, and PCR plates. Available resources may include available space in various waste containers.

[0114] In decision block 1336, if the operating state of one of the electronic instruments 264, 268 is in a fault status, method 1300 proceeds to block 1340, where the organizing core application 220 deassigns the assay resources that were allocated to perform the incomplete assay. After deassigning the assay resources, method 1300 proceeds to block 1316, where the organizing core application 220 determines the available updated assay resources and the updated operating states of the electronic instruments 264, 268, including the unavailable operating state of one of the electronic instruments 264, 268, and can determine the updated operating sequence of the incomplete assay based on the available updated assay resources and the updated operating states of the electronic instruments 265, 268. In one embodiment, the organizing core application 220 continues to determine the updated operating sequence, deassigning and allocating resources. The updated operating sequence may be based on the operating status of electronic instruments 264 and 268, available resources, new assay instructions, and newly accepted samples.

[0115] If the operating status of electronic instruments 264 and 268 does not include a fault status during the execution of the assay, the analytical system 100 may continue to perform the assay on the biological sample until all assays or assay stages are completed, at which point method 1300 terminates in block 1344.

[0116] Figure 14 is a flowchart of one exemplary method 1400 for determining the operating sequence and updated operating sequence of an assay or assay steps to maximize one or more operational metrics. In one embodiment, the organized core application 220 can implement method 1400 or a portion thereof. After starting in block 1404, method 1400 can proceed to blocks 1408, 1412, 1416, 1420, 1324, 1328, and 1432 as described above with reference to blocks 1308, 1312, 1316, 1320, 1324, 1328, and 1432.

[0117] In decision block 1436, the organizing core application may determine that an assay is no longer required on the sample. Method 1400 can then proceed to block 1440, where the organizing core application releases the assignment of assays that were assigned to be performed, as described above with reference to block 1340 in Figure 13. For example, the organizing core application may receive the results of assays on a biological sample determined using one or more of the electronic instruments using the determined order. The organizing core application may determine that a second assay on a biological sample or another biological sample does not need to be performed. For example, a unit of work that may include one or more assays may be discontinued due to inferred results from the results of a prior assay. Such discontinuation can achieve cost or time savings, as the second / pending assay does not need to be performed. The organizing core application may determine that a pending assay is no longer significant to the clinical diagnosis by rule set. For example, a first, inexpensive assay for determining physiological conditions or states may have a low false-positive rate and a high false-negative rate, while a second, more expensive assay for determining the same physiological conditions may have a low false-positive rate and a low false-negative rate. The instructions received by the Assembly may include steps to perform both assays on the sample, and the Assembly core application may determine that the first assay must be performed before the second assay. If the result of the first assay is negative, the second assay may be performed. If the result of the first assay is positive, the Assembly core application may determine that the second assay does not need to be performed. The Assembly core application may determine an updated operation sequence that excludes the step of performing the second assay on the sample in order to maximize at least one operational metric of the analytical system. Based on the updated operation sequence, resource allocation may be released.

[0118] If all assays are required, the analytical system can continue performing assays on the biological sample until all assays or assay steps are completed, at which point method 1400 terminates in block 1444.

[0119] Additional features Storage of assay results. The analysis system 100 or 100A can perform assays based on assay requests received from the laboratory information system and the operating sequence determined by the organized core application. The modules listed below relate to the analysis system 100 shown in Figure 2A, but these same assays can be performed by the analysis system 100A in Figure 2B. After the assay is completed, the analysis system 100 can transmit the assay results to the laboratory information system 204 over the network 208. When assay results are available, the analysis system 100 may be unable to establish a connection with the laboratory information system 204 over the network 208 due to network or other problems. In this embodiment, the analysis system 100 can store the assay results locally and transmit the results to the laboratory information system 204 later when a connection is established. The analysis system 100 can periodically attempt to re-establish the connection. If it is unable to re-establish the connection, the failure status can be notified to laboratory staff. This notification may be, for example, an email, text message, sound, or other display indicating that the results were not sent to the laboratory information system 204. The analysis system 100 can store the assay results in an unencrypted format or an encrypted format using a symmetric key scheme.

[0120] Monitoring of inventory and operational integrity. The Organization Core Application 220 can determine the operating sequence of an assay or assay stage based on the accepted sample, the requested assay, the availability of resources 248, 252, and the operating status of electronic instruments 264, 268. The Organization Core Application 220, the Organization Sub-Application 240 of the Pre-Analysis Instrument 104, or the Organization Sub-Application 244 of the Analytical Instruction 108 can track available assay resources. Assay resources may include consumables 256, 268 and reagents 272, 276. Assay resources may include diluents, reagents, assay control samples, pipette tips, sample tubes, extraction tubes, polymerase chain reaction (PCR) plates, available space in waste containers, or any combination thereof.

[0121] Modular assay instruments are complex machines. Electrical, mechanical, and pneumatic systems can fail. To achieve the highest level of operation, the Organization Core Application 220 can monitor the health of the instruments and the integrity of the electronic instruments 264 and 268, and adapt the operation of each assay being performed to the operational hardware. For example, the Organization Core Application 220 can monitor the operating status of the electronic instruments 264 and 268. The operating status of the electronic instruments 264 and 268 can include fault status, offline status, online status, paused status, power-off status, busy status, idle status, or any combination thereof. As another example, the analytical system 100 may include an externally or internally installed uninterruptible power supply (UPS). The Organization Core Application 200 can monitor the health of the UPS. When the Organization Core Application 220 determines or receives an indication that the operating status of one of the electronic instruments 264 and 268 is in fault status, it can notify laboratory staff of the fault status.

[0122] The analysis system 100 can generate reports on inventory and the operational integrity of electronic instruments 264 and 268. For example, when the organizing core application 220 determines that a component of electronic instruments 264 or 268 has a fault status, the analysis system 100 can generate a report with diagnostic data and diagnostic codes indicating that the specific component has failed and needs to be repaired, inspected, or replaced. The organizing core application 220 can then re-determine the operation sequence based on this failure. Some assays may be paused, while others may be repeated.

[0123] The Organizing Core Application 220 can coordinate the operation of multiple independent but connected instruments that require the availability of hardware and consumables across the instruments to correctly prepare and analyze a single sample. These independent and connected instruments may include a pre-analysis instrument 104, an analyzer instrument 108, and instrument devices 264, 268. For example, to perform an assay on a sample, the sample may need to be pipetted. If either the pipetting robot or pipette tip of the pre-analysis instrument 104, or the consumables 268 and reagents 276 of the analyzer instrument 108 are unavailable, the Organizing Core Application 220 can determine the operation sequence to exclude the step of performing this assay on the sample.

[0124] Status indicators. The analysis system 100 may include multiple visual indicators across multiple independent but connected instruments. The analysis system 100 can use visual indicators to show the user of the system 100 that the system 100 requires the user's attention. For example, a visual indicator for the analysis system 100 may flash red when there is a system failure. As another example, an indicator for the pre-analysis system 104 may flash yellow when consumables 256, such as pipette tips, need to be replenished urgently.

[0125] Logs. The analysis system 100 can aggregate and store log files from multiple independent but connected instruments for later retrieval. For example, the analysis system 100 can aggregate and store log files at the level of assays performed, the operating status of instruments 104, 108 and devices 264, 268, and consumables 256, 268 and reagents 272, 276. As another example, log files may include results or intermediate results of assays being performed. The analysis system 100 can transfer log file data to a central or remote data storage device to enable remote troubleshooting through log analysis. For example, when a component of pre-analysis instrument 104 has a failure status, the analysis system 100 can retrieve a log file containing such failure status from pre-analysis instrument 104 and transfer this log file to the laboratory information system 204 for diagnosis of the failure status. Log file information can be transferred based on its importance or timing. For example, log file information containing the failure status of the overall analysis system 100 can be given a higher priority than log file information indicating that consumables need to be replenished urgently.

[0126] Determination of operating coordinates and parameters. Instrument devices 264, 268 may include physical hardware components such as motor encoders, integrated circuits, and solenoids, i.e., the organizing core application 220 can track the operating state of the hardware within each instrument. In one embodiment, instrument devices 264, 268 may include interactive position probes and cameras, and the organizing core application 220 can determine the correct operating coordinates and parameters of instrument devices 264, 268 or their components. For example, pre-analysis instrument 104 may include a pipette robot with a position probe. Pre-analysis instrument 104 may include a camera that captures images of the position probe. The organizing core application 220 can determine the coordinates and parameters of the pipette robot using the images of the position probe. In another example, the pipette robot may include multiple position probes, and pre-analysis instrument 104 may include three cameras orthogonal to each other. The organizing core application 220 can determine the coordinates and parameters of the pipette robot in three dimensions using images captured by the orthogonal cameras. The captured images can be used to calibrate the components of instrument devices 264 and 268. Position probes can be fixed or movable on the components. Fewer movable position probes are needed to determine the operating coordinates and parameters of the components. Position probes can use various colors to indicate their status, for example, in use or faulty.

[0127] Uninterruptible power supply. The analysis system 100, pre-analysis instrument 104, analysis instrument 108, or instrument devices 264, 268 may include an externally or internally mounted uninterruptible power supply (UPS). In the event of a power failure, the UPS can supply sufficient power to the analysis system 100 or its components to ensure that all data is stored in a non-transient storage device such as a solid-state drive (SSD) or hard disk drive (HDD). The data stored in the data storage device in the event of a power failure may include the results or intermediate results of an assay being performed. The data may include the status and parameters of the analysis system 100 and its components.

[0128] Video surveillance. The analysis system 100 may include an internal camera that captures video surveillance data of its internal operations. The analysis system 100 can store the video surveillance data and display the video on demand to the user or technician of the system 100. In one embodiment, the video surveillance data is stored in a non-temporary internal storage device for later retrieval.

[0129] For example, laboratory staff or technicians may want to review video footage captured when a failure status of a component of the analysis system 100 is detected. Alternatively, laboratory staff may want to review video footage tracking a sample to ensure that no unauthorized alteration occurred to that sample. The analysis system 100 can automatically package the video footage along with logs and other data to support remote assessment of errors or problems.

[0130] Coordination with other computer systems or subsystems. In one embodiment, the organization core application 220 can coordinate with other systems associated with the analysis system 100. For example, the organization core application 220 can determine the operating sequence based on the operating status of the pre-analysis instrument 104 and the analysis instrument 108. As another example, the organization core application 220 of one analysis system 100 can determine the operating sequence based on the operating status of another analysis system 100. In one embodiment, the organization sub-application 240 of the pre-analysis instrument 104 can influence the operating sequence determined by the organization core application 220 for the pre-analysis instrument 104 and the analysis instrument 108, and vice versa.

[0131] Sample work list. The Organization Core Application 220 can automatically build and publish a sample work list for processing existing samples as a group corresponding to the nominal operation of the analysis system 100 or its components. For example, the Organization Core Application 200 can automatically build and publish a sample work list for processing existing samples as a group corresponding to the nominal operation of a device, and according to user-defined rules based on the day of the week, date, time, or any combination thereof. As another example, the Organization Core Application 220 can automatically build and publish an existing sample work list for processing existing samples as a group corresponding to the nominal operation of a device, and according to user-defined rules based on the day of the week, date, time, or any combination thereof, applicable to a specific test requested for each sample.

[0132] Sample removal. The compilation core application 220 can monitor the processing and analysis of samples and alert laboratory staff when original sample containers being removed or already removed by laboratory staff are to be retrieved for further examination and evaluation. For example, the compilation core application can alert the user when original sample containers already removed from the system are to be retrieved for further examination and evaluation and can present sample information and location to laboratory staff for easy sample retrieval. Sample information and location may include a sample identifier and the location of the sample, such as its location on a rack. The compilation core application 220 can re-determine the operation sequence when the sample is returned to the analysis system 100.

[0133] Cloud-based organizational core application Figure 15 is a block diagram of an analysis system communicating with a laboratory information system and multiple analysis systems over a network. Hospital 1504a may include a hospital information system 1508a that stores and processes hospital data. For example, the hospital information system 1508a may store patient data and prescription request information. Hospital 1504a may have an in-hospital laboratory 1512a having a laboratory information system 204a and an analysis system 100a. The laboratory information system 204a can receive assay commands 212 and patient information from the hospital information system 1508a. The laboratory information system 204a can store the requirements for assays that can be performed by the analysis system 100a. The analysis system 100a may be able to perform certain assays, such as a general-purpose cancer panel. Although the organization core application 220 is shown controlling two analysis systems, the organization core application 220 can control many analysis systems with different functions located in different locations. Analysis systems 100a and 100b can be the analysis systems shown in Figure 2A and / or Figure 2B.

[0134] A laboratory 1512b, such as an independent laboratory, may include a laboratory information system 204b and an analysis system 100b. The laboratory information system 204b can store the requirements for assays that can be performed by the analysis system 100a. The functions of the analysis system 100b and the analysis system 100a may be the same or different. For example, the analysis system 100b in laboratory 1512b may be able to perform a general-purpose cancer panel and a dedicated cancer order.

[0135] To determine the operation sequence for analysis system 100a or analysis system 100b, the organization core application 220 can receive assay commands from the hospital information system 1508a, the laboratory information system 204a, or the laboratory information system 204b. The organization core computer application 220 can track the functions of analysis systems 100a and 100b. For example, resources of analysis system 100a may become temporarily available, and analysis system 100a can provide this information to the organization core application 220.

[0136] Given the received assay command and scanned sample, the organizing core application 220 can determine the order of operations for analysis systems 100a and 100b to maximize operational metrics. For example, hospital 1204a may prefer that its analysis system 100a perform as many assays as possible to minimize costs. However, based on the availability and capabilities of analysis system 100a, the organizing core application 220 may determine that certain assays or certain assays on certain samples must be performed by analysis system 100b.

[0137] As another example, an assay instruction may state that a dedicated cancer panel must be performed after a general-purpose cancer panel has determined that a patient is at risk of cancer. The initial operating sequence for analytical systems 100a and 100b, determined by the Organization Core Application 220, may include a step in which the general-purpose cancer panel is performed by analytical system 100a at hospital 1504a. The operating sequence for analytical systems 100a and 100b can be determined using methods 1000 and 1200, as described with reference to Figures 10 and 12, respectively. If the results of the general-purpose cancer panel indicate that a patient is at risk of cancer, the Organization Core Application 220 may determine a new operating sequence for analytical system 100c at laboratory 1512b. This new operating sequence may take into account the time required to transport the sample from hospital 1504a to laboratory 1512b. The Organization Core Application 220 can determine the new operating sequence using methods 1000 and 1200, as described with reference to Figures 10 and 12, respectively. For example, when the results of a general-purpose cancer panel become available, analysis system 100b may be performing assays on other samples. The new operating sequence for analysis system 100c can be determined to maximize the operation of analysis system 100c or the combined operation of analysis systems 100a and 100b.

[0138] In one embodiment, the structuring core application 220 can receive an indication that analysis system 100b is unavailable. Analysis system 100b may become unavailable if the structuring core application 220 loses its connection to analysis system 100b or if it is performing an urgent assay command. Based on the unavailability of analysis system 100b, the structuring core application 220 can determine a new operating sequence for analysis system 100a. In one embodiment, the structuring core application 220 determines the operating sequence for some analysis systems to maximize the operational metrics associated with those analysis systems in order to increase the overall efficiency of processing assay samples. For example, hospital 1504a may have a contractual relationship with laboratory 1512b such that the operating sequence for analysis systems 100a and 100b is determined to maximize the operational metrics associated with these two analysis systems 100a and 100b.

[0139] Figure 16 is a schematic diagram of a structuring core application stored on a cloud-based server that communicates with the structuring laboratory application to coordinate automated sample processing and analysis. Hospital 1504 may include a hospital information system 1508 that stores and processes hospital data. For example, the hospital information system 1508 may store patient data and prescription request information. Hospital 150a may have an in-hospital laboratory 1512 having a laboratory information system 204 and multiple analysis systems 100a, 100b. The laboratory information system 204 can receive assay instructions and patient information from the hospital information system 1508. The laboratory information system 204 can store the requirements for assays that can be performed by the analysis systems 100a, 100b.

[0140] The Coordination Core Application 220 on the cloud system 1600 can communicate with the Coordination Laboratory Application 1604 on the laboratory information system 204 to coordinate automated sample processing and analysis using the analysis systems 100a and 100b. When the Coordination Core Application 220 is available, the Coordination Laboratory Application 1604 can send received assay commands and scanned samples to the Coordination Core Application 220. Based on the information received from the Coordination Laboratory Application 1604 and similar information received from other Coordination Laboratory Applications, the Coordination Core Application 220 can determine the operation sequence for the analysis systems 100a and 100b controlled by the Coordination Laboratory Application 1604 and the analysis systems controlled by the other Coordination Laboratory Applications. As a result, the operation sequence determined by the Coordination Core Application 220 can maximize the operation metric given the received assay commands and scanned samples. When the organization core application 220 is unavailable, the organization laboratory application 1604 may be able to determine the sequence of operations for the analysis systems 100a and 100b to maximize the operational metric, given the received assay command and scanned sample.

[0141] This distributed architecture allows the organization core application 220 and the organization laboratory application 1604 to maximize operational metrics given the available information and resources. For example, the operational sequence determined by the organization core application 220 may be based on the capabilities of analytical systems 100a and 100b in laboratory 1512 and other laboratories. Each laboratory can perform a general-purpose cancer panel. However, performing a general-purpose cancer panel using the analytical system in laboratory 1512 may be expensive. To reduce the cost of performing the cancer panel, the organization core application 220 may decide to perform the general-purpose cancer panel using the analytical system in another laboratory. Before the sample (or part thereof) for the cancer panel is sent to the other laboratory, the organization laboratory application 1604 may lose its connection to the organization core application 220. Since there is no guarantee that the general-purpose cancer panel can be completed even if the sample (or part thereof) is sent to the other laboratory, the organization laboratory application 1604 may determine a new operational sequence for analytical systems 100a and 100b.

[0142] In one embodiment, the cloud system 1600 can receive data or test results generated by the analysis systems 100a and 100b from the analysis laboratory application 1604 through its organization core application 220. Although the organization core application 220 is shown to control two analysis systems 100a and 100b, the organization core application 220 can control many analysis systems with different functions located in different locations.

[0143] Laboratory 1512 may include several conventional systems 1608 that do not have automated functions. These conventional systems 1608 can be controlled by a laboratory-based middleware system that provides a highly available and operational link between the laboratory platform and other IT systems. This link can be used primarily to power local laboratory operations. The cloud system 1600 can receive data or test results generated by these conventional systems 1608 from the conventional system laboratory interface 1616 of the laboratory information system 204 through its conventional system interface 1612. The conventional system laboratory interface 1616 can receive data generated by the conventional systems 1608 from the laboratory-based middleware system. In one embodiment, the cloud system 1600 can receive data or test results generated by point-of-care (POC) devices through the POC interface.

[0144] By controlling analysis systems 100a and 100b, and receiving data and test results generated by analysis systems 100a and 100b, the conventional system 1608, and the POC device 1615, the cloud system 1600 has the functionality to manage relevant laboratory data on an enterprise scale and to operate remote microbiology research for laboratories. Aggregation of data across all hospitals, laboratories, and patients enables value-added services and provides insights into hospital, laboratory, and patient usage. Examples of value-added services include peer benchmarking and wide-area monitoring. The received data and test results form a data mart capable of wide-area clinical and diagnostic aggregation. In one embodiment, data relating to different hospitals, institutions, or affiliated hospitals or institutions is stored in different databases 1624a and 1624b located in different locations 1632a to 1632e.

[0145] Access to cloud functionality can be provided through distributed apps 1636 via an application portal 1640 that supports both traditional and mobile devices. The application portal 1640 can be centrally managed and redirect users to relevant technology-specific app stores. These app stores can enable the distribution of apps 1636, presumably developed by third-party developers, that conform to the architecture of the cloud system 1600. Apps 1636, presumably developed by third-party developers, can more flexibly address custom data management requirements.

[0146] In one embodiment, the cloud system 1600 utilizes social network connectivity to enable better interaction between hospitals, laboratories, and patients. The cloud system 1600 can enable better customer relationship management activities, ranging from services and training to inbound and outbound marketing opportunities.

[0147] The architecture of Cloud System 1600 is extensible to meet changing market demands. In one embodiment, the architecture supports both public and local (private) clouds, thereby eliminating data sovereignty objections for users who want all their data behind their own firewalls. Cloud System 1600 is secure, i.e., addresses concerns regarding data, HIPAA privacy, and regulatory compliance. Cloud System 1600 is also extensible and can support new / updated devices and modules.

[0148] In at least some of the embodiments described herein, it is possible to use one or more elements used in an embodiment interchangeably in another embodiment, provided that such interchangeability is not technically impossible. Those skilled in the art will recognize that it is possible to make various other exclusions, additions, and modifications to the methods and structures described above without departing from the scope of the claimed subject matter. All such modifications and changes are intended to remain within the scope of the subject matter defined by the claims.

[0149] With regard to substantially any use of plural and / or singular terms herein, a person skilled in the art can convert from plural to singular and / or singular to plural where appropriate for the context and / or use. Various singular / plural substitutions may be expressly shown herein for clarity. Where used herein and in the claims, unless the context explicitly specifies otherwise, “a,” “an,” and “the” include singular and plural references. Any use of “or” herein is intended to include “and / or” unless otherwise specified.

[0150] Those skilled in the art will generally understand that the terms used herein, particularly in reference to the claims (e.g., the body of the claims), are generally “non-restrictive” terms (for example, the term “including” should be interpreted as “including but not limited,” and the term “having” as “having at least,” and similar terms should be interpreted similarly). Furthermore, those skilled in the art will understand that where a particular number of claims to be introduced is intended, such description should be explicitly stated within the claim, and where such description is absent, such description does not exist. For example, to aid understanding, the following claims may include the use of the introductory phrases “at least one” and “one or more” to introduce the claims. However, the use of such phrases should not be interpreted as meaning that the introduction of a claim description with the indefinite article "a" or "an" limits any particular claim to embodiments containing such introduced claim descriptions, even if the same single claim includes claim descriptions with the introduction phrase "one or more" or "at least one" and claim descriptions with an indefinite article such as "a" or "an" (for example, "a" and / or "an" should be interpreted as meaning "at least one" or "one or more"). Furthermore, when a particular number of claim descriptions being introduced is explicitly described, a person skilled in the art will recognize that such descriptions must be interpreted as meaning that there are at least that number of descriptions (for example, the description "two descriptions" alone, without other modifying phrases, means at least two descriptions or two or three or more descriptions). Furthermore, when using idiomatic expressions similar to "at least one of A, B, and C," such constructions are generally intended to mean that a person skilled in the art would understand the idiomatic expression (for example, "a system having at least one of A, B, and C" would include, but not be limited to, systems having only A, only B, only C, A and B together, A and C together, B and C together, and / or a system having A, B, and C together).When using idiomatic expressions similar to "at least one of A, B, or C," such constructions are generally intended to mean what a person skilled in the art would understand (for example, "a system having at least one of A, B, or C" would include, but not be limited to, a system having A only, B only, C only, A and B together, A and C together, B and C together, and / or a system having A, B and C together). A person skilled in the art will further understand that virtually any disjunctive term and / or phrase presenting two or more other terms, whether in this specification, claims, or drawings, must be understood as potentially including one of these terms, either one of these terms, or both. For example, the phrase "A or B" would be understood to include the possibilities of "A" or "B" or "A and B."

[0151] In addition, when describing features or aspects of the disclosure of the present invention in relation to the Markush group, a person skilled in the art will recognize that the disclosure of the present invention is also described in relation to any individual component or subgroup of components of the Markush group.

[0152] As will be understood by those skilled in the art, for all purposes relating to providing written details, all scopes disclosed herein also encompass all possible sub-scopes and combinations of sub-scopes. It will be readily apparent that all scopes listed are sufficiently detailed to allow for division into at least two, three, four, five, ten, etc., sub-scopes. As a non-limiting example, each scope described herein can be readily divided into a lower third, a middle third, an upper middle third, etc. Likewise, as will be understood by those skilled in the art, all phrases such as “up to,” “at least,” “greater than,” and “less than,” include the numerical value being described and mean a scope that can be subsequently divided into sub-scopes as described above. Finally, as will be understood by those skilled in the art, a scope includes each individual component. That is, for example, a group having 1 to 3 articles means a group having 1, 2, or 3 articles. Similarly, a group having 1 to 5 articles means a group having 1, 2, 3, 4, or 5 articles, and so on.

[0153] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be obvious to those skilled in the art. The various aspects and embodiments disclosed herein are illustrative and not intended to be limiting, and the true scope and spirit are shown by the following claims. [Explanation of Symbols]

[0154] 100b Analysis System 104b Pre-analysis instrument 108b Analytical Instruments 204b Laboratory Information System 220b Core Application for Organization

Claims

1. An electronic system for analyzing multiple biological samples using multiple electronic instruments, Multiple electronic instruments including multiple analysis modules and related analysis submodules and multiple pre-analysis modules and related pre-analysis submodules, A memory that stores available assay resources, assay resources required for multiple assays, and operational metrics for the electronic system, The process involves receiving multiple assay instructions from an instruction provider regarding multiple biological samples from at least one subject. A step of determining one or more assays to be performed on each electronic instrument for each biological sample based on the assay command, The step of determining the available assay resources and the operating status of the multiple electronic instruments, A step of determining the operating sequence for one or more assays in order to maximize at least one operating metric for the electronic system, based on the available assay resources and the operating states of the plurality of electronic instruments. A step of allocating assay resources from among the assay resources available for the one or more assays to be performed, The steps of configuring each of the plurality of electronic instruments based on the aforementioned operating sequence, A step of performing the one or more assays on the plurality of biological samples using the plurality of electronic instruments configured in the determined order, A processor programmed to perform a method including, An electronic system characterized by including

2. The electronic system according to claim 1, characterized in that the operational metrics for the electronic system include operational metrics related to the number of valid assay results per period, the number of biological samples tested per period, or a combination thereof.

3. The electronic system according to claim 2, characterized in that the number of valid assay results is determined based on the biochemical stability of the biological sample and the biochemical stability of the assay resource.

4. The electronic system according to claim 2, wherein the operational metrics for the electronic system further include operational metrics related to the time required of laboratory personnel to operate the electronic system per period, the maximum amount of time the electronic system does not require input from the laboratory personnel, the minimum number of times the electronic system requires input from the laboratory personnel per period, or a combination thereof.

5. The electronic system according to claim 4, characterized in that the required user time is determined based on the number of interruptions of the electronic system per period.

6. The electronic system according to claim 2, characterized in that the aforementioned period includes a 24-hour period.

7. The electronic system according to claim 1, characterized in that the operational metrics for the electronic system include operational metrics related to the amount of consumables consumed to complete the one or more assays.

8. The electronic system according to claim 1, characterized in that the operation metric for the electronic system includes one or more operation metrics related to predetermined conditions.

9. The electronic system according to claim 8, characterized in that the one or more predetermined conditions include the urgency of the assay, the profile of the at least one subject, the identity of the command provider, or a combination thereof.

10. The electronic system according to claim 1, characterized in that the step of determining the sequence of operations includes a step of determining the sequence of operations for one or more assays based on the available assay resources.

11. The electronic system according to claim 1, characterized in that the step of determining the sequence of operations includes the step of organizing the plurality of biological samples into a plurality of sample batches.

12. The electronic system according to claim 11, characterized in that the electronic instrument is configured to process batches of samples simultaneously.

13. The electronic system according to claim 12, characterized in that the assay resources are configured such that the electronic instrument processes batches of the samples simultaneously.

14. The electronic system according to claim 1, characterized in that the step of determining one or more assays to be performed includes the step of retrieving information related to the one or more assays from a database of a laboratory information management system.

15. The aforementioned processor further, In the step of monitoring the operating status of the electronic instrument, including the fault status, The stage of notifying laboratory staff of the aforementioned failure status, A step of determining an updated operating sequence for one or more assays in order to maximize at least one operational metric of the electronic system, Programmed to perform a method that includes, The electronic system according to feature 1.

16. The electronic system according to claim 15, characterized in that the at least one operation metric used in the step of determining the operation sequence and the at least one operation metric used in the step of determining the updated operation sequence are the same.

17. The step of determining the updated operation order is: The step of releasing the allocation of assay resources for performing the one or more assays that were not performed, A step of updating the assay resources available for performing the one or more assays after releasing the allocation of the assay resources, and A step of determining the updated operating sequence for one or more assays to maximize the at least one operating metric for the electronic system, based on the updated available assay resources and the operating state of the electronic instruments. including, The electronic system according to claim 15, characterized in that it is as described above.

18. The aforementioned processor further, A step of receiving the results of a first assay among the one or more assays on a biological sample from among the multiple biological samples, which has been determined using one or more of the multiple electronic instruments configured in the order determined above. The step of determining that it is not necessary to perform a second assay among the one or more assays on the biological sample, and A step of determining an updated operating sequence for one or more assays in order to maximize at least one operational metric of the electronic system, Programmed to perform a method that includes, The electronic system according to feature 1.

19. The aforementioned processor further, The step of tracking the available assay resources, and The stage of notifying laboratory staff when assay resources are unavailable or expected to be unavailable. Programmed to perform a method that includes, The electronic system according to feature 1.

20. A method for high-throughput automation of bioassays on multiple electronic instruments, The stage of receiving multiple assay instructions for multiple biological samples, A step of determining one or more assays to be performed on each of a plurality of electronic instruments for each biological sample based on the assay command, A step of determining the available assay resources and the status of the multiple electronic instruments, A step of determining the operating sequence for one or more assays in order to maximize at least one operating metric for the electronic system, based on the available assay resources and the states of the plurality of electronic instruments. The steps of configuring each of the plurality of electronic instruments based on the aforementioned operating sequence, A step of performing the one or more assays on the plurality of biological samples using the plurality of electronic instruments configured in the determined order, A method characterized by including the following.

21. The operation metric for the electronic system includes the operation metric for each of the plurality of electronic instruments, The target operating metric for the electronic system includes a target operating metric for each electronic instrument to perform the one or more assays. The method according to the present invention, characterized by the present invention.

22. The method according to 21, characterized in that the operating metric for each electronic instrument includes the amount of idle time per period.

23. The method according to 20, characterized in that the operational metrics for the electronic system include metrics relating to the duration of the assay, the priority of the biological samples, the biochemical stability of each biological sample, the state of the electronic instruments, the simultaneity of the assay resources required to perform the plurality of assays, or any combination thereof.

24. The method according to 20, characterized in that the assay resources include a diluent, reagents, assay control sample, pipette tip, sample tube, extraction tube, polymerase chain reaction (PCR) plate, available space in a waste container, or any combination thereof.

25. The method according to 20, characterized in that the plurality of electronic instruments include a plurality of analysis modules and associated analysis submodules, and a plurality of pre-analysis modules and associated pre-analysis submodules.

26. The method according to 20, characterized in that the step of determining the operation sequence for the one or more assays includes the step of allocating assay resources to the one or more assays to be performed.

27. An electronic system for analyzing multiple biological samples using multiple electronic instruments, A memory that stores assay resources and operational metrics associated with each electronic instrument in the plurality of electronic instruments, A database of assays performed on biological samples, A database of available electronic instruments communicating with an electronic system, the database including assay resources available for each electronic instrument, The sequence of operations for performing each of the assays on the biological sample and the identity of the electronic instrument scheduled to perform the assay, An interface configured to send operation commands to the first electronic instruments listed in the operation sequence in order to perform the first assay, A step of monitoring the first electronic instrument to determine when the first assay is completed, The steps include instructing a second electronic instrument to perform a second assay on the biological sample, and The stage of updating the operational schedule within the electronic system to indicate that the second assay has begun. A processor programmed to perform a method including, An electronic system characterized by including

28. A system for high-throughput automation of biological assays, Memory for storing instructions, The stage in which multiple assay commands for multiple biological samples are received from multiple analytical systems, A step of determining a plurality of assays that need to be performed on each sample in the plurality of biological samples based on the assay instruction, A step of identifying the analytical system available for performing each type of assay within the plurality of assays, The step of determining the assay resources within the identified analytical system that are available for performing the multiple assays, In order to maximize the efficiency of performing the aforementioned multiple assays, the steps include determining the order in which to perform each assay within the multiple assays based on the available assay resources, and A step of instructing one or more analytical systems to perform a specific assay from the plurality of assays based on the determined order, A processor programmed by the instruction to perform a method including, A system characterized by including

29. The aforementioned processor, A step of determining the assay location of the first biological sample among the plurality of biological samples, A step of comparing the analytical system available at the assay site with the plurality of assays performed at the assay site, and Steps include initiating the transfer of the first biological sample from the assay location to the second assay location, The program is designed to implement a method that further includes, The system according to feature 28.

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