Patent Description:
The subject matter disclosed herein generally relates to a remote sample delivery system for an automated sample test track.

<CIT> describes an automation system for an in vitro diagnostics environment including a plurality of intelligent carriers that include onboard processing and navigation capabilities. The intelligent carriers can include one or more image sensors to observe the relative motion of the track as the carrier traverses it. The carriers can also observe position marks on the track surface to provide absolute position information, which can include additional data, such as routing instructions. Synchronization marks may be provided to correct errors in the observed trajectory.

<CIT> describes an unmanned aerial vehicle transportation system for transporting hospital blood samples and a transportation method. The unmanned aerial vehicle transportation system comprises blood sample collection terminals, blood sample receiving terminals, sample boxes and unmanned aerial vehicles, wherein the blood sample collection terminals are arranged in all inpatient areas.

<CIT> describes an analytical laboratory system and method for processing samples. A sample container is transported from an input area to a distribution area by a gripper comprising a means for inspecting a tube. An image is captured of the sample container. The image is analyzed to determine a sample container identification. A liquid level of the sample in the sample container is determined. A scheduling system determines a priority for processing the sample container based on the sample container identification. The sample container is transported from the distribution area to a subsequent processing module by the gripper.

<CIT> describes an unmanned aerial vehicle (UAV) for transporting a payload is provided. The UAV comprises a body and one or more propellers rotatably connected to the body. The UAV further comprises a battery mounted to the body. The battery is releasable from the bottom of the UAV. The UAV further comprises a payload container mounted to the body. The payload container is releasable from the bottom of the UAV to a landing platform associated with a UAV station.

The underlying technical problem is solved by the subject-matter according to the independent claims. Additional embodiments are defined in the dependent claims.

Example methods and systems are directed to a remote sample delivery system, preferably an remote sample delivery system for an sample test track, preferably an automated sample test track. Examples disclosed herein merely typify possible variations. Unless explicitly stated otherwise, components and functions are optional and may be combined or subdivided, and operations may vary in sequence or be combined or subdivided. In the following description, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of example embodiments. It will be evident to one skilled in the art, however, that the present subject matter may be practiced without these specific details.

In one embodiment, a sample test tracks, which also hereinafter may refer to an automated sample test track, may obtain a biological sample and move the sample along a container conveyance arrangement to various test stations. In an example embodiment the biological sample may be a bodily fluid such as blood. In a further embodiment, the term test station as mentioned herein may refer to an automated test station. In a further embodiment, the test stations may perform discrete tests on the biological sample to assess for various conditions based on a list of tests ordered by a professional. In an example embodiment, the professional includes a medical professional such as a physician In a further embodiment, the container conveyance arrangement will deliver the sample to test stations that may be configured to perform tests that have been ordered and skip test stations that correspond to tests that have not been ordered.

In a further embodiment, operation of the biological sample within the sample test track may be contingent on bringing the biological sample to the sample test track. In one embodiment, either the biological sample, the sample test track, and/or both may be in remote locations. In a further embodiment, various sample test tracks may be available for use, but some of the sample test tracks may include test stations that are not able to perform all of the ordered tests. In a further embodiment, some of the sample test tracks may include delivery of the sample to a sample test track that may not be able perform all of the ordered tests. In a further embodiment, due to degradation of the biological sample over time it may become detrimental to a future ability of the tests to be performed. In a further embodiment, various sample test tracks in a given area may be relatively busier and have longer a wait time to run the tests on the biological samples than others in a given area. In a further embodiment, sending or routing a biological sample to a sample test track that has a large backlog may be inefficient and introduce unnecessary delay in obtaining test results.

In one embodiment. a remote sample delivery system has been developed that may allow for a relatively rapid and efficient transportation of biological samples to sample test tracks. In a further embodiment, the remote sample delivery system may be based on a unmanned autonomous vehicle (UAV) or "drone" that may be configured to secure a container for a biological sample. In a further embodiment, UAV may be configured to read a sample identifier, such as a barcode, radio frequency identifier ("RFID") tag, a sensor, a MEMS, an NFC sensor, a NEMS etc. In a further embodiment, the UAV may travel to a sample receiving station, preferably automatically, on a sample test track, and deposit the container on the sample test track. In a further embodiment, where multiple sample test tracks are available, the system may select a sample test track based on capacity of and wait time for each sample test track and the tests ordered for the biological sample, as provided on the sample identifier. In one embodiment, the moment a biological sample is picked up and an identifier attached, the UAV may be configured to transmit data to the system, which can pre-calculate the sample test track and reserve the test track based on the test ordered for better efficiency.

One embodiment discloses a biological sample test system. In a further embodiment, the biological sample test system may include a remote sample delivery system, preferably an automated sample delivery system that may be configured to secure a container for a biological sample. In a further embodiment, the container may include a sample identifier.

In a further embodiment, the biological sample test system may include a sample receiving station. In a further embodiment, the sample receiving station may be configured to receive the container based on a sample identifier. In a further embodiment, the remote sample delivery system may be configured to navigate to the sample receiving station without any human intervention upon the container being secured to the remote sample delivery system.

In a further embodiment, a sample test track may include a plurality of test stations. In a further embodiment, a container conveyance arrangement may be configured to sequentially deliver the container to individual ones of the plurality of test stations based, at least in part, on sample identifier.

In a further embodiment, the remote sample delivery system may be configured to navigate to the sample receiving station based, at least in part, on the sample identifier. In a further embodiment, the biological sample test system may include a plurality of sample receiving stations and a plurality of sample test tracks. In a further embodiment, each individual ones of the sample test tracks may be associated with one of the plurality of sample receiving stations. In a further embodiment, the remote sample delivery system may be configured to deliver the container to a predetermined one of the plurality of sample receiving stations based, at least in part, on an associated one of the plurality of sample test tracks.

In a further embodiment, each of the plurality of sample test tracks may include a mix of test stations. In a further embodiment at least one of the plurality of sample test tracks may have a different mix of test stations than another of the plurality of sample test tracks. In a further embodiment, the remote sample delivery system may be configured to navigate to one of the plurality of sample receiving stations based, at least in part, on the mix of test stations of an associated one of the plurality of sample test tracks.

In a further embodiment, the sample identifier may correspond to a series of tests to be performed on the biological sample. In a further embodiment, the remote sample delivery system may be configured to navigate to the one of the plurality of sample receiving stations based on the mix of test stations of the associated one of the plurality of sample tracks being able to perform the series of tests.

In a further embodiment, each of the plurality of sample test tracks may have an availability status. In a further embodiment, the remote sample delivery system may be configured to navigate to the one of the plurality of sample receiving stations based on the availability status of the associated one of the plurality of sample tracks. In a further embodiment, each of the plurality of sample test tracks may be configured to update its availability status based, at least in part, on an expected wait time for a sample to be tested. In a further embodiment, the remote sample delivery system may be configured to navigate to a plurality of sample receipt locations and secure at least one container at each of the plurality of sample receipt locations.

A further embodiment may include securing, with a remote sample delivery system, a container for a biological sample using the system as disclosed above.

<FIG> illustrates a biological sample test system <NUM>, in an example embodiment. A sample test track <NUM> includes a plurality of test stations <NUM> connected by a container conveyance arrangement <NUM> (also referred to broadly as a container conveyance system). The test stations <NUM> may include various capabilities depending on the type of biological samples to be tested. In an example embodiment for blood test, any given tests station <NUM> may be able to perform pre- or post-analytical operations, including assessing, accessing, or closing off a container; immunoassay tests; coagulation tests and/or operations to promote coagulation; microbiology tests; molecular tests; hematology tests; and/or chemistry tests. The container conveyance arrangement <NUM> may be or include any suitable system with which to selectively move a container from one test station <NUM> to another test station <NUM> based on the tests ordered for the sample in the container, skipping test stations <NUM> that do not perform tests that have been ordered. The container conveyance system <NUM> may include, but is not limited to, conveyor belts, robotic arms and/or self-propelled vehicles.

The biological sample delivery system <NUM> further includes a sample receiving station <NUM> coupled to a pre-analytical test station <NUM>'. The pre-analytical test station <NUM>' may include intelligent multifunctional input. The sample receiving station <NUM> includes a location toreceive a remote sample delivery system <NUM>. Where the remote sample delivery system <NUM> is based on an UAV, the sample receiving station <NUM> includes a landing pad for the UAV. The sample receiving station <NUM> additional includes a device configured to secure a container from the remote sample delivery system <NUM> and transport the container from the remote sampledelivery system <NUM> to the pre-analytical test station <NUM>', for example a roboticarm, a bulk sorter, and the like.

As noted, the remote sample delivery system <NUM> may be based onan UAV, but may alternatively be based on any suitable automated vehicle, including ground systems. For the purposes of this description, an UAV will beutilized for illustrative purposes.

In the illustrative example, the remote sample delivery system <NUM> includes an aerial unmanned autonomous vehicle <NUM> (UAV), a sample container securing mechanism <NUM>, such as a test tube holder, and a sample identifier reader, such as a barcode reader, an RFID reader, or other systems known in the art or disclosed previously, including a visual scanner for color coded components of the container and the like. The sample container securing mechanism <NUM> may grip or otherwise enclose the sample container and may optionally provide environmental control, such as heating or cooling, as appropriate, systems to promote coagulation of the sample or other pre- analytical operations as appropriate, and the like. The sample identifier may include a unique identifier for the sample; a unique identifier for the patient fromwhom the sample was obtained; a date and time the sample was obtained; a unique identifier for the healthcare provider that obtained the sample; a destination for tests results; and discrete tests that are to be performed on the biological sample by test stations <NUM>.

Upon the remote sample delivery system <NUM> landing with or otherwise delivering a container <NUM> at or to the sample receiving station <NUM>, the sample receiving station <NUM> may secure the container <NUM>, for example, witha robotic arm, and move the container <NUM> to the pre-analytical test station <NUM>'. The pre-analytical test station <NUM>' may either obtain from the remote sample delivery system <NUM> the information from the sample identification or may conduct its own read of the sample identifier to obtain relevant information related to which tests are to be performed. The pre-analytical test station <NUM>' may receive containers <NUM> of any various types and sizes and may prioritize containers <NUM> based on a priority of the container, e.g., prioritizing STAT containers highest. The pre-analytical test station <NUM>' may identify containers <NUM> based on, e.g., a physical property of the container <NUM>, such as cap color, may check the sample volume and weight, may check a unique identifier, as disclosed herein, may capture an image of the container <NUM> and may identify a pre-spun status designed to be detected. The pre-analytical test station <NUM>' or another test station <NUM> may utilize synchronized dual centrifuges for workload balance between and among the various containers <NUM> and my include integrated cap removing devices to provide access to the biological sample contained within the containers <NUM>. The pre-analytical test station <NUM> may further include an automated aliquoter. Upon completion of the pre-analytical procedures and operations, the sample test track <NUM> may then transport the container <NUM> along the container conveyance system <NUM> to the various test stations <NUM> that correspond to the test as included on the sample identifier.

While containers <NUM> may be transported individually, it is to be recognized and understood that facilitation of operation of the system <NUM> may involve clustering containers <NUM> and moving such clusters of containers <NUM> through the system <NUM> or portions of the system and performing operations on each of the containers <NUM> within a given cluster. In various examples, clusters may be formed with racks or other container holders. In an example, test tube racks may be utilized to cluster test tube containers <NUM>. In such an example, the test tube rack is configured to receive and secure, at least in part, test tube containers <NUM>. Robotic arms may grasp or otherwise secure individual test tube containers <NUM> contained within the test tube rack and remove the individual test tube container <NUM> to variously test, process, or transfer the individual test tube container <NUM> to another test tube rack. In such an example, the test tube rack allows for the test tube containers <NUM> to be stored vertically with a cap or lid oriented up to prevent spills and provide ease of access. In various examples, one of the test stations may be or may include a universal rack-builder unit, e.g., for chemistry systems, hematology workcells, etc..

In an example, the test tube racks include a six-by-six rack with capacity for thirty-six test tubes. Such test tube racks have dimensions of <NUM> millimeters by <NUM> millimeters, a height of <NUM> millimeters, and a net weight of <NUM> grams. In an example, the test tube racks include a six-by-fourteen rack with capacity for eighty-four test tubes. Such test tube racks have dimensions of <NUM> millimeters by <NUM> millimeters, a height of <NUM> millimeters, and a net weight of <NUM> grams. In an example, the test tub racks include a storage rack with a capacity for <NUM> test tubes. Such storage racks have dimensions of <NUM> millimeters by <NUM> millimeters, a height of <NUM> millimeters, and a net weight of <NUM> grams.

The sample test track <NUM> includes various identifier readers <NUM> positioned throughout. The identifier readers <NUM> are configured to identify containers <NUM> according to whatever mechanisms are utilized to provide sample identifiers as noted above, e.g., barcode readers, RFID tag readers, and so forth. The identifier readers <NUM> are positioned within test stations <NUM> and at various points on the container conveyance system <NUM>. Such locations may be selected in order to give a desired degree of resolution as to the location and status of each container <NUM> within the sample test track <NUM>.

The biological sample test system <NUM> further includes an electronic data storage <NUM>, a network interface <NUM>, a user interface <NUM>, and a processor <NUM>. Those components <NUM>, <NUM>, <NUM>, <NUM> may be local to the system <NUM> or may be accessed remotely by the system <NUM>. The network interface <NUM> communicatively couples the identifier readers <NUM>, electronic data storage <NUM>, user interface <NUM>, and processor <NUM> together. The electronic data storage <NUM> stores records, such as electronic medical records ("EMRs") relating to the containers <NUM> within the system <NUM> and the samples contained therein, in an electronic data repository. The processor <NUM> provides general processing for the system <NUM>.

Upon a container <NUM> passing through an identifier reader <NUM>, the record corresponding to that container <NUM> is updated with to note which specific identifier reader <NUM> the container has most recently passed by. Inferentially, the container <NUM> would then be understood to be located between the identifier reader <NUM> that had last noted the presence of the container <NUM> and the immediately subsequent identifier reader <NUM> within the sample test track <NUM>. If the identifier reader <NUM> is located within a test station <NUM> then it is to be understood that the identified container <NUM> is within the test station <NUM>.

As the container <NUM> passes through various test stations <NUM>, the record may similarly be updated with the results of the tests run within the test station <NUM>. Thus, as a container <NUM> progresses through the sample test track <NUM> the record for the container <NUM> and the sample contained therein will increasingly be populated with information from test results and the location of the container <NUM> within the system sample test track <NUM>.

<FIG> illustrates an example of a biological sample test system <NUM> in an extended operation area, in an example embodiment. In the illustrated example, there are multiple sample test tracks <NUM> to which a biological sample may be delivered. In various examples, the various sample test tracks <NUM> include different test stations <NUM>, meaning that certain sample test tracks <NUM> may be able to perform a given test while others may not. Moreover, each sample test track <NUM> may have a variety of containers <NUM> in various stages of tests, including waiting for tests to be performed, meaning each sample test track <NUM> may have a wait time or expected time until tests may be expected to be completed.

Located within a transportation distance, e.g., a range of operation of the automated remote sample delivery system, of the biological sample test system <NUM> generally are multiple sample pickup locations <NUM>. A sample pickup location <NUM> may be a site where a biological sample may be obtained, placed in a container <NUM> with a sample identifier, and made ready to be secured by the remote automated sample delivery system <NUM>, such as a hospital, clinic, pharmacy, or any location that is suitably equipped, including a private residence or non-medical commercial or industrial facility. The sample pickup locations <NUM> have the capacity for the remote automated sample delivery system <NUM> to land or to access without necessarily landing.

The biological sample test system <NUM> generally includes processing capabilities, as disclosed herein, to plan a route of the automated remote sample delivery system <NUM> to pick up containers <NUM> from various sample pickup locations <NUM> and deliver the containers <NUM> to various automated sample test tracks <NUM>. The route planning may be based on criteria related to the capabilities and availabilities of the automated sample test tracks <NUM>, the time necessary to transit between and among the automated sample test tracks <NUM> and the sample pickup locations <NUM>, and the priority of any given sample, e.g., if a sample has an urgent or time-sensitive status. Such processing capabilities may be included across the biological sample test system <NUM> in the form of networked processors, e.g., via cellular, WiFi, or other wired or wireless networking protocols, as well as remotely available, e.g., "cloud" computing services. In various examples, the automated remote sample delivery system <NUM> includes an onboard processor that is capable of acting independently or in conjunction with other processors.

The route processing may be relatively simple or complex, based on the processing capabilities and information available. Thus, for instance, when the components of the biological sample test system <NUM> are fully networked and available generally and the system <NUM> "knows" where all of the containers <NUM> for pickup are located, the location of the remote sample delivery system <NUM>, and the availability and capabilities of the sample test tracks <NUM>, the system <NUM> may optimize the pickup and delivery of containers <NUM> based on total time to process each container <NUM>, or based on a priority of each sample <NUM>, or according to any other consideration. Thus, for instance, the system <NUM> may cause the remote sample delivery system <NUM> to visit multiple sample pickup sites <NUM> before visiting a single sample test track <NUM> that is capable of handling all of the containers <NUM> that are picked up at the visited sample pickup sites <NUM>. Further, if efficient for time, the remote sample delivery system <NUM> may pick up multiple containers <NUM> and then visit multiple automated sample test tracks <NUM>, leaving one or more containers <NUM> at each sample test tracks <NUM> dependent on the capabilities and availability of each of the sample test tracks <NUM>.

Moreover, where the remote sample delivery system <NUM> is limited to its own onboard processing for route calculation then the routes may be relatively simple. The remote sample delivery system <NUM> may proceed to a pickup location, obtain the container <NUM>, and then transit to either the nearest sample test track <NUM> or to the nearest sample test track <NUM> that the remote sample delivery system <NUM> "knows" to have the necessary capabilities.

While the illustrated example embodiment of <FIG> includes multiple automated sample test tracks <NUM>, it is to be recognized and understood that various principles disclosed with respect to <FIG> may be applied to circumstances in which only one sample test track <NUM> is included in the biological sample test system <NUM>. Thus, in such examples, the remote sample delivery system <NUM> may only transit between sample pickup locations <NUM> and the sample test track <NUM>. Considerations of available tests and test wait time or backlog may not factor into decision about how the remote sample delivery system <NUM> operates when only one sample test track <NUM> is available or otherwise included in the biological sample test system <NUM>.

<FIG> illustrates a block diagram illustrating components of a machine <NUM>, according to some examples, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically, <FIG> shows a diagrammatic representation of the machine <NUM> in the example form of a computer system and within which instructions <NUM> (e.g., software) for causing the machine <NUM> to perform any one or more of the methodologies discussed herein may be executed. In alternative examples, the machine <NUM> operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine <NUM> may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine <NUM> may be a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a smartphone, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions <NUM>, sequentially or otherwise, that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term "machine" shall also be taken to include a collection of machines that individually or jointly execute the instructions <NUM> to perform any one or more of the methodologies discussed herein.

The machine <NUM> includes a processor <NUM> (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a radiofrequency integrated circuit (RFIC), or any suitable combination thereof), a main memory <NUM>, and a static memory <NUM>, which are configured to communicate with each other via a bus <NUM>. The machine <NUM> may further include a graphics display <NUM> (e.g., a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)). The machine <NUM> may also include an alphanumeric input device <NUM> (e.g., a keyboard), a cursor control device <NUM> (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), a storage unit <NUM>, a signal generation device <NUM> (e.g., a speaker), and a network interface device <NUM>.

The storage unit <NUM> includes a machine-readable medium <NUM> on which is stored the instructions <NUM> (e.g., software) embodying any one or more of the methodologies or functions described herein. The instructions <NUM> may also reside, completely or at least partially, within the main memory <NUM>, within the processor <NUM> (e.g., within the processor's cache memory), or both, during execution thereof by the machine <NUM>. Accordingly, the main memory <NUM> and the processor <NUM> may be considered as machine-readable media. The instructions <NUM> may be transmitted or received over a network <NUM> via the network interface device <NUM>.

As used herein, the term "memory" refers to a machine-readable medium able to store data temporarily or permanently and may be taken to include, but not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, and cache memory. While the machine-readable medium <NUM> is shown in an example to be a single medium, the term "machine-readable medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term "machine-readable medium" shall also be taken to include any medium, or combination of multiple media, that is capable of storing or carrying instructions (e.g., software) for execution by a machine (e.g., machine <NUM>), such that the instructions, when executed by one or more processors of the machine (e.g., processor <NUM>), cause the machine to perform any one or more of the methodologies described herein. Accordingly, a "machine-readable medium" refers to a single storage apparatus or device, as well as "cloud-based" storage systems or storage networks that include multiple storage apparatus or devices. The term "machine-readable medium" shall accordingly be taken to include, but not be limited to, one or more data repositories in the form of a solid-state memory, an optical medium, a magnetic medium, or any suitable combination thereof.

<FIG> is a user interface <NUM> for tracking containers <NUM> within the sample test track <NUM>, in an example embodiment. The user interface <NUM> may be on a computer display or on a display for a tablet computer, smartphone, or the like. The user interface <NUM> may have or be a touchscreen interface and/or may be interfaced with via a mouse or other remote device.

The user interface <NUM> includes an abstract diagram <NUM> of the sample test track <NUM> generally and the test stations <NUM> in particular overlaid with icons <NUM> of containers <NUM> and where the containers <NUM> are based on the location of the container <NUM> obtained from the associated record stored in the electronic data storage <NUM>. In the illustrated example, each icon <NUM> is generic with no particular distinguishing information unless a user selects the icon <NUM>, whereupon information, such as a unique identifier of the associated container <NUM>, may be displayed. In alternative examples, however, some or all of the icons <NUM> are accompanied by a unique identifier of the associated container <NUM>.

While the illustrated example of the diagram <NUM> is abstract, it is to be recognized and understood that the user interface <NUM> may optionally provide less abstract imagery. For instance, the icons <NUM> may be images of containers or vials, the automated test stations <NUM> may be depicted with various degrees of photo-realism, and so forth. The user interface <NUM> may provide a mechanism for switching between abstract and more-realistic images.

In various examples, each icon <NUM> is the same. However, in alternative examples, icons <NUM> may differ in order to provide status information for the associated container <NUM>. For instance, icons <NUM> may vary in color depending on the status of the container <NUM>; if the container <NUM> is actively being tested by an automated test station <NUM> then the icon <NUM> may be green; if the container <NUM> is in transit on the container conveyance system <NUM> then the icon <NUM> may be yellow; if the container <NUM> is waiting to be tested in a test station <NUM> then the icon <NUM> may be red; and so forth. Moreover, the icons <NUM> may vary in appearance in more ways than simply changing color to denote the status of the container <NUM> and the sample within, as desired. Further, where multiple containers <NUM> are essentially co-located, e.g., because the containers <NUM> are located in the same test tube holder, the icons <NUM> may be enlarged or otherwise changed to denote representing multiple individual, co-located containers <NUM>.

Upon selecting an icon <NUM>, a window <NUM> may display information about the container <NUM>, the sample within, and the status of the container <NUM> within the automated sample test track <NUM> based on the record of the container <NUM> as obtained from the electronic data storage <NUM>. As illustrated, the window <NUM> displays a unique identifier <NUM>; a location description <NUM> of the current location of the container <NUM>; and test status <NUM>, detailing the tests that have been performed, the results of those tests, and the tests that are yet to be performed. It is to be recognized and understood that any pertinent, desired information may be obtained and displayed in the window <NUM>, and that the window may provide one or more links to other sources of information regarding the container <NUM> and sample that may be impractical or impossible to display in the window <NUM>.

The user interface <NUM> further includes a search line <NUM>, allowing a user to input search terms to identify a desired container <NUM>. The search terms may include any information about the container <NUM> and sample included in the associated record, and the processor <NUM> may compare the search terms against each record to identify one or more records that correspond to the search terms. In the even that more than one container <NUM> corresponds to the search terms the user may be prompted to select one among the potential results. Upon identifying the desired container <NUM> based on the search terms, the user interface <NUM> may highlight or otherwise draw attention to the associated icon <NUM> to illustrate the location of the container <NUM> within the automated sample test track <NUM>. In various examples, information relating to the container <NUM> and sample may be displayed in the window <NUM>. If one particular container is not identified then each icon <NUM> pertaining to a potential container <NUM> may be highlighted or otherwise identified.

The user interface <NUM> may further provide information about the automated sample test track <NUM> and the status of the automated test stations <NUM> and container conveyance system <NUM>. In an example, a user may select a particular automated test station <NUM> to obtain information about the automated test station's <NUM> function and status, e.g., a number of containers <NUM> that are being tested by the automated test station <NUM>, a capacity of the automated test station <NUM> to take more containers, and an operational status of the automated test station <NUM>, e.g., operational, non-operational, reduced capacity, etc..

Moreover, the user interface <NUM> may provide an indication of backlogs. For instance, if more than a predetermined number of containers <NUM> are in a particular location then the user interface <NUM> may highlight the location or otherwise denote that a backlog has occurred. The user interface <NUM> may further denote the number of containers <NUM> that are present in the location and/or the number of container <NUM> by which the predetermined number is exceeded.

Further, the user interface <NUM> may an identify automated test station <NUM> that is potentially out of compliance and provide an alert noting the potential failure. The system <NUM> generally and the processor <NUM> specifically may identify the potential failure based on a comparison of the records of containers <NUM> and samples that have been tested by the automated test station <NUM> against standard pass/fail criteria for the associated test. If a higher percentage of those tests have failed over a predetermined period of time, the automated test station <NUM> may be flagged as potentially having failed and the user interface <NUM> highlight or otherwise draw attention to the automated test station <NUM> with an accompanying alert detailing the basis for the finding of the potential failure.

Techniques such as artificial intelligence or machine learning may be used to perform the method as disclosed herein, wherein the system can automatically learn and improve from experience of past history that may be stored in a repository. Other techniques may be used to automate and improve the system. In an example embodiment, the UAV may access the repository to efficiently automate the processing of the biological sample based on historical data present in the repository.

Certain examples are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied on a machine-readable medium or in a transmission signal) or hardware modules. A "hardware module" is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.

A hardware module may be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module may include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module may be a special-purpose processor, such as a field programmable gate array (FPGA) or an ASIC. A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module may include software encompassed within a general-purpose processor or other programmable processor.

Accordingly, the phrase "hardware module" should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, "hardware-implemented module" refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.

In this context, algorithms and operations involve physical manipulationof physical quantities. It is convenient at times, principally for reasons of common usage, torefer to such signals using words such as "data," "content," "bits," "values," "elements," "symbols," "characters," "terms," "numbers," "numerals," or the like.

Claim 1:
A biological sample test system (<NUM>), comprising:
a remote sample delivery system (<NUM>) comprising an aerial unmanned autonomous vehicle (<NUM>) and a sample container securing mechanism (<NUM>) secured to the aerial unmanned autonomous vehicle (<NUM>), configured to secure a container (<NUM>) for a biological sample, the container (<NUM>) including a sample identifier;
a sample receiving station (<NUM>), configured to receive the container (<NUM>) from the remote sample delivery system (<NUM>), wherein the remote sample delivery system (<NUM>) is configured to automatically navigate to the sample receiving station (<NUM>) upon the container (<NUM>) being secured to the remote sample delivery system (<NUM>), and wherein the remote sample delivery system (<NUM>) is configured to navigate to the sample receiving station (<NUM>) based, at least in part, on the sample identifier; and
a sample test track (<NUM>), comprising a pre-analytical test station (<NUM>') and a plurality of test stations (<NUM>) and a container conveyance system (<NUM>) configured to sequentially deliver the container (<NUM>) to individual ones of the plurality of test stations (<NUM>) based, at least in part, on the sample identifier,
wherein the sample receiving station (<NUM>) is coupled to the pre-analytical test station (<NUM>'), and
wherein the sample receiving station (<NUM>) includes a landing pad for the aerial unmanned autonomous vehicle (<NUM>).