GB2604598A

GB2604598A - Method and system for managing stock of samples

Info

Publication number: GB2604598A
Application number: GB2103130.7A
Authority: GB
Inventors: Daniel Preston Mark; david smith Andrew
Original assignee: Prismea Ltd
Current assignee: Prismea Ltd
Priority date: 2021-03-05
Filing date: 2021-03-05
Publication date: 2022-09-14
Also published as: GB202103130D0; GB2604598A8

Abstract

A system for managing laboratory samples including at least a first mobile computing device such as a smartphone that includes a display, a camera for capturing an image of an array of stored laboratory samples stored in a storage unit such as a sample box or sample tray. A processor is provided for rendering the image of the array on the display and the system includes a means for inputting a tag of at least one sample in the array and an intra-array location, the samples position in the array, of the at least one sample. The identifying tag may contain a unique sample identifier and may be a simple tag or metadata or combined with a complex sample description. Further information such as the arrays shelf number in the storage unit & location of the building may be added to precisely define the samples location. A memory stores at least the input tag and corresponding intra-array location of the at least one sample.

Description

METHOD AND SYSTEM FOR MANAGING STOCK OF SAMPLES

TECHNICAL FIELD

The present disclosure relates to a method and system for managing a stock of items held in different locations and accessible to different persons.

In particular, the disclosure herein relates to a stock management system for items such as laboratory samples, the stock being stored at different locations and handled by different persons. The stock may be used by an international team in a coordinated international project. Laboratory samples may require storage at low temperatures and may have a finite 113 lifetime. They may be accessible and movable by a number of persons without notice or acknowledgement to other persons using the same samples.

BACKGROUND OF THE INVENTION

Clinical, biomedical, academic and pharmaceutical research standardly involves a research team investigating the properties of a range of substances. The purpose of such an undertaking is to obtain accurate reproducible results of a study into the substances. The substances may be any organic or chemical or other materials, subject to an analysis, investigation, clinicai trial, research or enquiry, including pharmaceuticals, drugs, tissue (human or animal), biopsies, genetic material, viruses, bacteria etc The work is frequently a coordinated joint effort by a large research team, the team and the samples of the substances under investigation being often spread over a number of locations. Samples are frequently accessible to a number of team members, who share the research facilities such as storage units (eg fridges, cupboards), equipment and premises.

Large studies can easily involve several 10,000 samples and instantly locating each sample in the project quickly become a challenge, although this may be indispensable to the success of the study. The management of the stock of samples, especially if the samples require low temperatures, is critical to the success of such research projects: it is vital to be able to accurately locate any sample at any time. A loss of a sample, even for a short period, or mistaking one sample for another, may impair or invalidate the results of the project.

Despite the importance of identifying and locating samples, many projects omit to use a reliable stock control If there is any sample stock control or if sampie locations are recorded at all, the records are often ad hoc, personal or not shared. Some lab inventory systems are cumbersome and unwieldy, and inconvenient to use. It is common for a team member to keep a personal note of where a sample has been last deposited by him/her, but the rest of the group is uninformed. Sometimes the personal note may take the form; for example; of a spreadsheet or memo or handwritten note, but still lacks any group access or control.

Control over the samples is made more complex by the shared access of the team to the samples. There are a number of situations in which samples can be misplaced or compromised: storage units becoming overused or full; tidying up or housekeeping, to provide order in a storage unit or "free up" space therein; samples being removed for clinical purposes, and returned, inadvertently and unrecorded, to a different storage unit; other unrecorded lc) movements of samples. Despite the growing trend toward remote working, the remoteness of team members, who nevertheless have access, albeit remotely, to shared samples: may give rise to further unrecorded sample movements.

Such circumstances can easily lead to samples becoming lost or untraceable. Even where the loss is temporary or short-term, the samples concerned may have been exposed to an undesirable temperature, environmental, security, IP and safety risks. Moreover; during any such period the samples in question may breach the rules of a particular clinical trial or, worse, the samples become non-compliant with national or international regulatory requirements. The results of the trial, or indeed, the trial itself, may be compromised by such breaches.

TECHNICAL OBJECTIVE AND BRIEF DESCRIPTION

It is therefore an object of the apparatus and method disclosed herein to overcome the above referenced shortcomings by providing a reliable method and system for managing a stock, for example a stock of laboratory samples, which reduces the chances of unrecorded movements of samples and maximises the traceability of samples subject to such movements, thereby enhancing reporting and auditing, which may be important in relation, for example, to regulatory requirements.

The disclosure herewith describes a method and system characterised by ease and flexibility of use and mitigates the need for ad hoc records. The method and apparatus disclosed herein facilitates shared accesslinput by a plurality of users via a communications network.

Under the method and apparatus of the invention a photograph of an array of samples (sample box or sample tray) may be taken, facilitating the sample to be allocated an identifying tag and its position location within the array (intra-array location). Further information, such the array's shelf number in the storage unit (cupboard, fridge, etc); the location, e.g. in a building, of the storage unit, and indeed the address of the building may be added to precisely define the sample's location.

In the system herein disclosed the photograph may be taken by a camera of mobile computing device, such a smartphone, and, via a communications network, to both a central server where the data is held and to other mobile computing devices also in communication with the central server. The identifying tag contains a unique sample identifier and may be a simple tag or a metatag or combined with a complex sample description.

By use of the method and apparatus herein disclosed inadvertent unrecorded movements of a sample, as well as gaps in areas previously occupied by samples, may be quickly identified, and the current location of a moved sample may be quickly ascertained. The system allows multiple users access/use of the location data: lost samples and inadvertent movements may be identified by a person other than the person originally locating the sample.

These and other technical objectives, as set out below, are achieved by the invention disclosed herein.

BRIEF DESCRIPTION OF THE FIGURES

Reference is now made to certain embodiments of the apparatus and method disclosed, by way of example, herein, one or more of which are illustrated in the accompanying drawings.

Figure 1 is an illustration of an apparatus in accordance with aspects of the invention.

Figure 2 is an illustration of an array image in accordance with exemplary aspects of the invention Figure 3 is an illustration of an array image in accordance with exemplary aspects of the invention herein disclosed.

Figure 4 is is a further illustration of highlighting in accordance with exemplary aspects of the apparatus and method of the invention herein disclosed.

Figure 5 is an illustration of an exemplary embodiment in accordance with the apparatus and method herein disclosed Figure 6 is an illustration of an exemplary embodiment in accordance with the apparatus and method herein disclosed.

The description makes use of certain alphanumerical references, as appropriate, to refer to features in the drawings. The same or similar references in the drawings and description have been used to indicate the same or similar parts of the arrangement disclosed herein.

DETAILED DESCRIPTION OF THE FIGURES AND EMBODIMENTS

Reference will be made in detail in this description to examples and embodiments of the apparatus and method disclosed herein, one or more of which are illustrated in the drawings.

Various embodiments, aspects and implementations of the present invention, as well as technical objectives and advantages will be apparent to those skilled in the art, upon 113 consideration of the description herein, in combination with the drawings. Unless indicated otherwise by the context, the terms "first", "second", "third", "last", etc are adopted just to distinguish one component from another, and are not intended to define or limit the position, location, alignment or importance of the components specified. The singular forms "a", "an", and "the" include plural references, unless, based on the context, this is clearly not the case.

An exemplary aspect of the present disclosure is directed to a system for managing laboratory samples comprising at least a first mobile computing device comprising a display, a camera for capturing an image of an array of stored laboratory samples stored in a storage unit, a processor for rendering the image of the array on the display, a means for inputting a tag of at least one sample in the array and an intra-array location, within the image, of the at least one sample, and a memory for storing at least the input tag and corresponding intra-array location of the at least one sample.

In an exemplary aspect of the present disclosure a means for inputting is a user interface, comprising means for manually inputting at least one of the tag and the intra-array location.

In an exemplary aspect of the present disclosure the system comprises a server and at least one communications channel configured to communicate first device data between the at least one mobile computing device and the server, wherein the server comprises a server processor for processing said data and a server memory for storing said data.

In an exemplary aspect of the present disclosure the at least one of the at least one mobile computing device and the server further comprises an artificial intelligence module for identifying the at least one sample in the image, assigning the tag and determining the intra-array location.

In an exemplary aspect of the present disclosure the artificial intelligence module is configured to communicate with the server processor and server memory, and to access, interrogate, modify or delete any of said data stored in said server memory.

In an exemplary aspect of the present disclosure the system comprises at least a second mobile computing device, having at least the same components as the first mobile computing device, and at least a second communications channel configured to communicate second device data between the at least a second computing device and the server.

In an exemplary aspect of the present disclosure the first and second mobile computing devices, are both configured to access each of the first device data and second device data stored at the server memory, using the first and second communications channels respectively, and further configured to interact with the server processor, using the first and second communications channels respectively, and modify the said data stored at the server memory.

In an exemplary aspect of the present disclosure the first and second mobile computing devices are further configured to compare the accessed data with the first device data and second device data respectively, and, based on said comparison, to identify any disparities therebetween.

In an exemplary aspect of the present disclosure the artificial intelligence module is further configured to compare the data stored on the server memory with first device data, and, based on said comparison, to identify any disparities therebetween.

In an exemplary aspect of the present disclosure the first and second mobile computing devices, and the artificial intelligence module, are configured to identify, based on said comparison, removals or absences of samples from any array.

In an exemplary aspect of the present disclosure the intra-array location of the at least one sample is the x-and y-coordinates, within the image of the array, of the at least one sample.

In an exemplary aspect of the present disclosure the tag comprises at least one of a unique identifier of the at least one sample and a date associated with the at least one sample.

In an exemplary aspect of the present disclosure the tag comprises a metatag containing a combination of metadata.

In an exemplary aspect of the present disclosure at least one of the input means or the artificial intelligence module is configured to input at least one of: (a) the location, within the storage unit, of the array; (b) the location, within the storage unit, of the array, the location being a shelf, or part of a shelf, of the storage unit and; (c) the location, in an identified building, of the storage unit, the storage unit being one of a cupboard, a fridge or a freezer.

An exemplary aspect of the present disclosure is directed to a method of managing laboratory samples comprising: capturing, by a camera of a first mobile computing device, an image of an array of stored laboratory samples stored in a storage unit; rendering, by a processor of the first mobile computing device, the image of the array on a display of the computing device; identifying, manually or by an artificial intelligence module, the at least one sample in the image, assigning, manually or by an artificial intelligence module, at least a first tag of the identified sample and determining, manually or by an artificial intelligence module, the intra-array location, within the image, of the identified sample; inputting at least the first tag and the first intra-array location; storing in a memory at least the first input tag and the first intra-array location of the at least one sample.

In an exemplary aspect of the present disclosure the inputting comprises inputting at least one of: (a) the location, within the storage unit, of the array; (b) the location, within the storage unit, of the array, the location being a shelf, or part of a shelf, of the storage unit, and; (c) the location, in an identified building, of the storage unit.

In an exemplary aspect of the method of the present disclosure the method comprises: communicating, using a first communication channel, between said first mobile computing device and a server, first device data comprising at least the said first tag and first intra-array location; processing, by a server processor at the server, said first device data; storing, at a server memory in the server, said first device data.

In an exemplary aspect of the method of the present disclosure the method comprises: capturing, by a camera in a second mobile computing device, at least a second image of a second array of stored laboratory samples stored in a storage unit; rendering, by a processor of the second mobile computing device, the at least second image on the display of the second mobile computing device; identifying, manually or by an artificial intelligence module, the at least one second sample in the second image, assigning, manually or by an artificial intelligence module, at least a second tag of the identified sample and determining, manually or by an artificial intelligence module, the second intra-array location, within the image, of the identified second sample; inputting, at an input means of the second mobile computing device, at least second device data, comprising at least a second tag of the at least one second sample in the array and a second intra-array location, within the second image, of the at least one second sample, storing, at least one of a memory of the second mobile computing device and the server memory, second device data, comprising at least the second input tag and corresponding second intra-array location of the at least one second sample.

An exemplary aspect of the method of the present disclosure comprises accessing, by the second mobile computing device, using a second communications channel configured to communicate between the at least second mobile computing device and the server, said first device data stored at the server memory.

An exemplary aspect of the method of the present disclosure comprises communicating, by the artificial intelligence module, with the server processor and server memory, and accessing, interrogating, modifying or deleting, by the artificial intelligence module, any of said data stored in said server memory.

In an exemplary aspect of the method of the present disclosure the second device data comprises at least the second array image, and second array image relates to the same array as the first array image, further comprising: comparing, by the processor of the second mobile computing device, the second device data with the accessed first device data, and; determining, by the processor of the second mobile computing device, for the first or second input tag, any disparities between the first array image and the second array image, based on the comparison.

An exemplary aspect of the method of the present disclosure comprises: interacting, via a user interface of the second mobile computing device and the second communications channel, with the server processor, and; modifying the said first data stored at the server memory using the second communications channel.

An exemplary aspect of the present disclosure is directed to a method, as set out herein, implemented by at least one computing device.

An exemplary aspect of the present disclosure is directed to a computer program product comprising program code instructions stored on a computer readable medium to execute the method steps, as set out herein, when said program is executed on a computer.

An exemplary aspect of the present disclosure is directed to a computing system configured to execute the method steps, as set out herein.

In accordance with an embodiment of the current disclosure a system for managing a stock of samples comprises at least one computing device (a first computing device), which is mobile and may, for example, be a computer, a desktop computer, a laptop, a tablet device; a mobile phone or a smartphone, connected via a communication channel, Or a communications network, to a server. The computing device comprises an image capture device or camera for producing images, which are rendered in real time on a screen, which may be a touchscreen, also comprised in the computing device.

The terms "communication channel' and "communications network" are used interchangeably herein; and refer to any channel or link, wired or wireless or a combination thereof, facilitating lo the two-way transmission of data, including the internet, private links, and dedicated networks.

In an embodiment of the method and apparatus herein, an input means may also be comprised in the first computing device. The input means of the computing device may comprise any form of input means, including manual user-determined input means, virtual input means (e.g. via the touchscreen, if present) and an artificial intelligence module (AIM), or any combination of these. Manual input means and virtual input means further comprises means for inputting and receiving user-determined titles, labels and names, comprising unicode or alphanumeric characters, including all languages, emojis, Asian characters, etc., which means may comprise a real or virtual keyboard (on the touchscreen, if present), and means for inputting and receiving user-determined input on the touchscreen, if present in the first computing device, including the x-and y-coordinates of such user-determined screen input within the image on the screen. The artificial intelligence module comprises means for intelligently interpreting and processing images rendered on the screen. Further details of the artificial intelligence module are provided in a later passage herein. Input via the input means may include any combination of manual input, manual touch on the touchscreen or intelligent input.

Laboratory samples are generally contained in a container, which is usually a vial or test tube or tube, which may be transparent or opaque. For brevity, reference herein to a laboratory sample or to a sample is to a laboratory sample contained in such a container. At least one laboratory sample is contained in a sample box or tray, referred to herein as a sample array, potentially with other samples and the sample array is stored on the shelf or section of a storage unit, this being a cupboard or a refrigerated storage or freezer, depending on the temperature requirements of the sample or samples. The samples may bear "real" tangible labels, identifying the sample, which are typed or handwritten, and applied or attached to a surface of the sample container where they can be read.

The operator of the first computing device directs the camera of the computing device to the sample array of interest, and, using the manual and/or virtual input means, activates the camera, which takes a photograph of the sample array. The computing device renders the image of the sample array on the screen of the device.

Using the displayed image and the input means any sample of the array may be assigned an identifying tag and a location within the array. The sample of interest within the image may be specified and distinguished from other samples in the array by moving a cursor to that sample or manually touching or clicking on its image within the image of the whole array on the touchscreen. The computing device may respond to the specifying of a sample within the array 1(:) with a highlighted area (e.g. a circle) on the screen denoting the relevant section of the image, the highlighted area being itself capable of enlargement or contraction to coincide with the section.

The location of the cursor or manual touch on the touchscreen, when either of these coincides with the sample of interest, is specified by its coordinates in the image, which may be cartesian (x-and y-coordinates), polar or any other coordinates capable of specifying position. As the reader will understand, the sample of interest will occupy a certain area within the image: this may be a circular area having a centre and radius, in which case the coordinates will correspond to the centre of the circular area. The specified coordinates at the time of manual/virtual input are the coordinates of the sample in question. The reader will understand that for any array image, the coordinates can only be occupied by a single sample i.e. each of the samples comprised within the array will have unique coordinates in the image. Another set of coordinates defines the boundaries of the sample array within the image, such that both the sample array itself and the individual samples in the array, may each be located by coordinates. Those coordinates uniquely identify the location of the sample in question and the array within the image. The coordinates of a sample define its intra-array location.

The word "tag" used extensively throughout this disclosure, refers to a means for labelling or identifying or describing any object to which it is attached or fixed, or any attribute or parameter associated therewith, and may include alphanumeric characters of any system of notation or other characters or drawings which serve to label or identify or describe. The term "tag" is used herein as a reference to any titles, labels, names: metatag or metadata, all of which may comprise at least alphanumeric characters and serve as a unique identifier of the laboratory sample in question. The assigned tag may comprise the same data as the "real" tangible label, typed or handwritten, and applied or attached to a surface of the sample container, or may be different to the real label.

It is also foreseen that a tag may also be a metatag containing extensive data related to the sample including its history, expiry dates, names of connected persons, composition of substances etc. The rnetatag can contain any information deemed by the person entering the information to be relevant to the sample and going well beyond just providing an identifier of the sample.

The sample's tag and its location within the array (intra-array location) may be entered by means of the manual or virtual input means, or a combination of these two, of the computing device. The sample's tag may be typed in using a keyboard, manual or virtual, or voice input means, including voice recognition means, to assign a tag to the sample and the sample's intra-array location, i.e. the samples image coordinates, may be specified by touching the touchscreen at the image of the sample of interest, the location of the manual touch on the array image being converted into by the processor into corresponding coordinates in the image. By inputting both a sample's tag and its intra-array location, the sample becomes identifiable and locatable within the array. Further data regarding the location of the array may also be added to the intra-array location, such as the shelf number in the storage unit accommodating the array and the location of the storage unit itself in the building or institution (eg room number, floor number, department name etc), as well as the name and address of the building or institution.

All data inputs including captured images, tags, location data and other data; are stored remotely from the mobile computing device at a server, which is in communication with the computing device. Data communicated to the server via a two-way communication channel is entered and stored by the processor in the memory of the server. Details of the server, the database and database management module are provided in a later passage.

In order to ascertain whether a sample has already been assigned a tag; the images of samples as stored in the server database is consulted: whenever a sample is specified a search in the database is initiated to decide whether an assignment of a tag to the sample is required. A match between a sample image of interest and an image in the database already assigned a tag; means that no assignment is required. In this case the tag may be retrieved from the database may be communicated via the communication channel to the computing device, appearing to the user of the computer device as "recognized" and bearing its previously assigned tag (although there may nevertheless be an option, possibly requiring an enhanced user authorisation, to override the previously assigned tag, with a new tag to be input). If, on the other hand, there is no such match, the sample is assigned a tag as described.

Assignment of a new tag to a sample of interest includes the assignment of a unique identifier, which in itself may be generated by any suitable process: it may be simply sequential, by assignment of the next available unused number in a series; it may be linked to a person or to the sample type (a pharmaceutical, human tissue, DNA material etc); it may be arbitrary; it may contain distinct elements, which may themselves be sequential or arbitrary, etc. In an aspect of the apparatus and method of this disclosure the system comprises at least one artificial intelligence module, for identifying and/or distinguishing, without human intervention, different objects/entities displayed within the image, and comprises means for automatically generating titles, labels and names, comprising alphanumeric characters, associated with images displayed on the screen, or parts or regions of such images, of the objects/entities identified/distinguished. After the operator of the camera directs the camera to io a sample array and the array image is generated, the artificial intelligence module does the work previously described in relation to the manual/virtual input means, by intelligently identifying the individual samples shown in the array image, distinguishing one sample from another and intelligently assigning tags (where not already assigned); to one or more of them, as well as determining their respective intra-array locations in the image.

The server processor comprises the artificial intelligence module (AIM) which communicates with the mobile computing device(s) via the communication channel, as well as with the server database. The mobile computing device(s) may themselves also comprise an AIM in communication with the server and server database. Each AIM can access, interrogate and modify data stored either on the client side memory or in the server database.

References herein to an artificial intelligence module (AIM) includes references to means which work in combination with a processor and a memory, to generate "non-passive" input. An artificial intelligence module is suitable for processing images and data and providing an analysis thereof in order to modify the image or data, or flag up some analytic result. In this way, an image of a sample array may be analysed or interrogated, possibly pixel by pixel, in order to identify each of the samples therein as well as the gaps between the individual samples, such that the array is "mapped our as a collection of distinguishable and identifiable samples, each with a specific location in the array. Texts in images or part-images is readable by the artificial intelligence module, so that a sample's physical tag may be read directly from the image, and optionally may be re-used in the tag to be assigned to the sample.

In accordance with an embodiment of the invention, the further data regarding the location of the array, as described above, may also be input by means of an artificial intelligence module (AIM), this being in communication with means for automatically identifying details such as shelf number in the storage unit accommodating the array and the location of the storage unit itself in the building or institution (e.g. room number, floor number, department name etc). Any such further data is transmitted and/or updated at the server database as appropriate.

On the client side, all operations potentially involving or requiring any human input, such as the manual assignment of a tag or the specifying of a sample within an image, has appropriate prompts to help guide the user to perform the task. The prompts may take visual or audible form, such as the movement of a cursor to a field to be completed, or the generation of one or more highlighted areas in an array image to denote a sample (or samples) in the array, the generation of such prompts being triggered by the processor (in the computing device or server or both), potentially in conjunction with the artificial intelligence module.

In accordance with an embodiment of the invention Fig 1 shows the main hardware components of the system described herein, comprising a client side and a server side with io communication between the two sides. The client side comprise at least a first mobile computing device (101a, 101b,.. 101n), each of the at least one computing devices being in communication, via a dedicated communication channel or network (102a, 102b, ....102n), with a server (103) on the server side. For simplicity Fig. 1 illustrates the at least a first computing devices as phone-type device, but the devices may variously be, for example, a computer, a desktop computer, a laptop, a tablet device, a mobile phone or a smartphone, etc. Although not depicted in Fig. 1 the computing devices each comprise an image capture device or camera for producing images, which are rendered in real time on a screen, which may be a touchscreen, also comprised in the computing device. The first mobile computing device also comprises an input means for entering data, which may be a text input means or means for inputting data received from other sources, a processor for processing data, images and text, as well as a memory for storage of the same. The first computing device is capable of transmitting and receiving communications to/from the communication channel by means of a communications interface also comprised in the first computing device.

The server (103) comprises a communications interface (104) for communication via the communication channels (102a, 102b, ....102n), a processor (105) for processing data, comprising a database management module (DMM), a memory (106) for storing data, the memory comprising a database (106); and an artificial intelligence module (AIM) (108).

We now consider the workings of the system, starting with the client side. As stated above, the operator may direct the camera of the mobile computing device toward an array of samples and activate the camera to take a photograph of the array and render the image of the array on a screen. In accordance with an aspect of the invention Fig 2 illustrates a photograph an array of samples. In this example the samples are stored in parallel tube-like slots, the photograph showing the ends of the elongate sample containers with real labels on the ends of each elongate container, but any size or any form of container is envisaged with labels fixed at any point on the container. In the example of Fig 2 the samples are shown in regular rows and columns but all patterns or configurations of storing or stacking are envisaged. This photograph of the sample array may be made visible to the operator by displaying it on the screen of the mobile computing device.

By moving a cursor or by inputting into a touchscreen of the computing device, different points in the displayed image of the array may be indicated by the operator. As stated earlier, a sample of interest within the image may be specified and distinguished from other samples in the array by moving a cursor to that sample or manually touching or clicking on its image within the image of the whole array on the touchscreen. The display responds to such specifying of a sample within the array by generation of a highlighted area (e.g. a circle) on the display the relevant location of the image, the highlighted area being itself capable of enlargement or contraction to coincide with the section. Enlargement or contraction of the highlighted area may be prompted by various size options 301 presented to the user, as shown in Fig. 3, or may enacted by physical manipulation directly onto a touchscreen.

In the exemplary aspect of the invention illustrated in Fig. 4 the operator has specified two areas or locations in the image 401, each corresponding to a different sample in the array. As explained in a later passage, the images of individual samples may be intelligently identified within the array of samples, in which case the corresponding areas in the image will be highlighted.

In Fig. 4 only two areas are highlighted, but there is no restriction on the number of areas highlighted and it is possible to highlight any number of areas. The areas specified are shown here as yellow highlighted circles, with diameters roughly corresponding to the images of the samples of interest, but any shape and any colour of the areas specified may be envisaged. The size of the highlighted circles is depicted in Fig 4 to approximately coincide with the diameters of the samples of interest, but the reader will understand that any number of samples could have been included in the array and the sample diameters would adjust accordingly: it is therefore envisaged that the size of the highlighted circles, denoting an area of interest within the image, may be adjusted accordingly, either by the operator specifying a larger smaller circle or by an intelligent means automatically making the size adjustment, as described in a later passage. The highlighted circles may overlap, without impacting on the locations of their centres or on the sample coordinates (intra-array location) of the sample.

In Fig. 4 enlargements of the two specified areas 402 and 403 are shown below the image 401 of the complete array and display the real sample tags applied to the samples in question.

The reader will have understood that the two specified areas 402 and 403 illustrate two distinct images of samples within the image of the complete array.

The samples in question are either completely new (not previously photographed) and therefore untagged in the system, or samples which have been previously photographed by an operator of the system and have already a tag assigned to them. Using the communication link to the server, the images are entered in the server processor and compared with images already saved in the server memory to identify the samples in question are already entered and tagged in the server memory.

We shall discuss in detail in a later passage how data is entered, saved, processed, accessed and interrogated at the server, but we shall now consider the case of a completely new and untagged sample. The process and apparatus of tagging a sample is now discussed in relation to an embodiment of the invention as illustrated at Fig 5 Using the second specified area 503 (as shown as 403 in the image 401 in Fig.4) on the display of the mobile computing device 501 as an example, an untagged sample has been distinguished from other samples illustrated in the array image 401 and is ready to be tagged. According to a request input in the input means by the user, or automatically whenever a specified area is highlighted or hovered over in the array image, the image of specified area 403 may be enlarged, cut-out and reproduced separately (or any combination of the three) on the display means. An option to assign a tag to the sample may, at this time, be called up by the operator or prompted or automatically offered to the user on the display means, as shown at 504.

Various means for assigning a tag to the specified area 503 and the corresponding sample are available, as mentioned earlier. Using a physical/virtual input means (or combination thereof) a new tag can be entered by the operator to uniquely identify the sample in question: an input field 502 is provided on the display and the tag to be assigned is entered by a manual/virtual keyboard and the link is created between the image 503. The system may offer predictive text to the operator. In the example illustrated at Fig 5 the tag "cDNA DMS0 417" is entered into the field 502. Once the entry in the field is finalised (e.g. by a tick or click or clicking "enter" or similar) the tag is assigned to the image 503. The assignment of the tag "cDNA DMSO 417" to the sample illustrated in 503 must be recorded not only on the mobile computing device but also, via a communication link, at the server, as explained in a later passage.

The image 401 of Fig. 4 is shown in an exemplary embodiment of the invention at Fig. 6, this time with an exemplary coordinate system (x, y) overlaid on the array image 601. As will be understood by the reader different locations in the image 601 in the display may be referenced by a coordinate system (Cartesian, polar, or any other coordinate system), the coordinates x and y defining a unique location within the image. The coordinate system may be applied to the areas of interest specified by the operator, as discussed above, and their coordinates determined: the coordinates of the two areas of interest shown in Fig. 6 are (xl, yi) and (x2, Y2). in the example illustrated yi and y2 are shown to be almost equal, as the two highlighted areas are in the same row, but any values of x and ymay be envisaged. The coordinates may be those within the image and automatically assigned as the areas are highlighted by the operator or may be manually input by the operator, overriding any coordinate values assigned automatically. The determination of the coordinates may also be applied to highlighted areas of interest without operator input and intelligently identified by the artificial intelligence module as mentioned above and discussed in more detail below.

The reader will understand from the foregoing that the location of a sample within the array, i.e. its intra-array location, may be thus specified or determined. In Fig. 6 the intra-array locations of the two samples highlighted are (xi, yi) and (x2, y2) or the equivalent in other coordination systems.

The intra-array location defines a sample's location in the array, but the location of the array itself needs also to be defined for the sample to be absolutely locatable in the world. As stated above, as well as the infra-array location, other location data associated with the sample has to be captured and recorded, such as the shelf number in the storage unit; the location of the storage unit in the building e.g. room number, floor number, department name etc), as well as the name and address of the building. These can be input using manual/virtual and automated input means. The input means of the mobile computing device may include input means for entering these location data in the same manner as inputting a sample's tag, i.e. entering the shelf number, storage unit location etc via a manual or virtual keyboard. Alternatively, some or part of this information may be captured by automatic input means, for example bar codes, RFID etc from which shelf number, storage unit number, floor number and the like can be readily downloaded and combined with the intra-array location to provide a complete sample location.

As stated previously, the server (103) of Fig 1 comprises a communications interface (104) for communication with individual mobile computing devices (101) via the communication channels (102), a processor (105) for processing data, with the database management module (DMM), and a memory (106) for storing data. Any data on any sample; comprising both the sample's tag and the sample's location data (infra-array location or other location data or both), once captured by a mobile computing device (101), in the manner previously described, is automatically transmitted to the server (103). A database comprising all such data on all samples is stored in the server memory (106). On instructions from processor (105), including those submitted from the client side, the DMM performs, in a conventional manner, all the operations associated with data stored in a database. The database is controlled by the database management module comprised in the processor and is responsible for processing, saving and entering data into the database, as well as accessing previously entered data and interrogating or updating the database. The database on the server side represents the central depositary of all data relating to any sample.

We now explain the access to the data held at the server. As stated above, data is centrally stored at the server and accessed remotely from a mobile computing device. The data is accessible not only to that mobile computing device which originally captured the data and transmitted it to the central server, but also to other computing devices, as long as they have the proper authority for access.

In other words, in accordance with a process and apparatus of an embodiment of the invention, the centrally stored data can be shared by a plurality of computing devices (first computing device, second computing device, etc). Each computing device has its own camera, input means and/or AIM, etc, as previously explained, and is configured to generate or receive or record, independently of the other computing devices, its own images of samples and sample arrays, its own tags, its own intra-array locations etc, i.e. collectively, its own data, in the manner described previously: a first computing device providing "first device data", a second computing device providing "second device data", and so on. Although the data stored on the server may have been captured by a particular computing device e.g. the first computing device, providing first device data, other computing devices (second, third computing devices, etc) communicating with the server, using their own respective communication channels, if they have the relevant authority to do, may also access the same first device data, in order to read it, interrogate it or, as we explain below, modify or update it. Similarly, a first computing device may access, modify or update the data of a second computing device ("second device data"), and so on.

The second device data may relate to a different array and different samples to that of the first device data, but may also relate to the same array and the same samples. Second device data may comprise a second array image, in the sense that this image has been captured by the second device, but the second array image is not necessarily of a different array or of different samples to that/those already associated or photographed by another computing device. The second device data comprising a second tag and second array-location of a second sample, may in fact relate to the sample (the first sample), as comprised in the first device data. Thus, there is no "tethering" of any mobile computing device (101a, 101b, ... 101n) to a particular array or particular storage unit -mobile computing devices are free to move between arrays and storage units -thus facilitating the comparison of data (e.g. first device data and second device data) where they relate to the same array or at least on common sample, as described in a later passage herein, thereby facilitating identification of unregistered removals, updating, modifications and deletions of data stored centrally at the server database. The database management module DMM is able to accommodate device data from different devices relating nevertheless to the same sample.

For an operator to access a sample's data from a mobile computing device, the operator will have to enter into a tag field the tag relevant to that sample. In accordance with an embodiment of the invention, the processor on the computing device, will, along with other functionalities, menus, fields and options, render a blank field to be filled using the relevant tag: Using the example previously cited, the operator may enter the tag "cDNA DMS0 4/1', or a part thereof, in the blank field. The tag entered, as it is a tag unique to a particular sample, or the part to thereof entered; allows the corresponding entry to be found in the sample database: entering just a part of the tag e.g. "cDNA" may be sufficient to find the corresponding entry, or at least to find a plurality of samples each with "cDNA" (the part-tag) in their respective tags; and possibly to render this plurality to the user; to enable a user selection from the plurality. The computing device, via the communication link, accesses the database on the central server and retrieves the data for that entry, transmitting this data back to the computing device, using again the communication link. The data is displayed on the screen of the communication device and may be read by the operator, who is accordingly informed of the location of the sample (including its intra-array location) and any other data retrieved from the central server related to the sample tagged "cDNA DMSO 4/7". The operator will then be able to physically locate the sample and, if necessary, retrieve the physical sample from the storage unit.

The operator, has, instead of searching by sample name, also the option of searching by other criteria, such as consulting "likely"/ "possible" locations or holders (persons) of a sample, which the operator perceives may "lead" to the sample sought: if the sample's tag is not known, but the sample will nevertheless be recognized by the person searching for it, locations or colleague names may be entered via the computing device and link to the database, in order to ascertain which samples are registered under these categories and if the sample sought is among them.

In a process and method in accordance with the invention, a facility comprising both a "check-in" and "check-out" is provided. A sample with a tag (and therefore identifiable) is "checked out" when it is removed from its recorded location, even briefly or temporarily, by taking the necessary steps on the mobile communication device which accordingly transmits that sample's new status of "checked out" to the central server, where the corresponding record is accordingly modified with an appropriate flag. The flag may, for example; indicate that the sample is currently located on the workbench (e.g. a virtual bench) of a named person. Other operators, using other communication devices, will see that the sample in question has been checked out and will understand that the sample is not present in its recorded location. The steps required to register on the communication device the sample's 'checked out" status comprise selection of the relevant sample, by entering the sample's tag, e.g. entering "cDNA DMS0 4h"in the blank field, as stated above, and when the data is retrieved from the server, such that the sample is live, then activating a tick box or notification box or other suitable field displayed on the computing device. The operator, and indeed all other users consulting the entry for that sample, e.g. "cDNA DMSO 4h", will see that it is "checked out" A further option would be to also indicate the name of the person who is responsible for the check out, so that other users can contact that person if they need to. The central server io database will record both the "checked out' status and the person responsible for the check out.

Wlien the operator has finished with the sample and it can be returned to its physical storage location then it can be "checked in" again. If the location is identical to the physical location from where the sample has previously been removed, then "check in" is merely the reverse of the steps described for "check out" and the relevant field on the computing device is de-activated/unchecked to return the status to "checked in", which will be communicated to the sample's entry in the server database and updated accordingly.

However, if the sample is re-located, i.e. placed at a location which is different from its original location, then the sample's entry in the database has to be amended accordingly, with a new intra-array location or other new location data. As the reader will understand; any new location has to be ascertained and communicated to the server, so that the existing location data for that sample can be overwritten or updated in the database. The steps required to determine any new location are those already described, comprising taking a photo of the array of samples, identifying the sample of interest etc, as already described above, except that this is for a sample whose tag is already registered in the database. The sample is distinguished from the other samples in the array in way previously described -clicking on a specified area, as previously described, will distinguish the sample of interest. The image of the sample will be already in the database and its re entry by means of a newly taken photo will be recognized by the processor as a re-location. An alternative option; which does not rely on recognition of existing images, is for the sample's tag (already entered in the database) to be entered in an empty field. Another alternative option is for the computing device to render a prompt containing suggested samples, any of which may be selected by the user. Whatever option is taken, the server processor, when interrogating the database, will recognize the sample; record the interaction and update the sample's location. Once it has been updated, the location may be viewed by other users as the sample's new location.

As stated above, in accordance with an exemplary aspect of method and apparatus of this disclosure, operators should be authorised. Clearly, the inventory management would be insecure if unknown or unauthorised persons started removing or re-locating samples in a haphazard way, so it is important that all users sign by means of a secure means. This could be done on a project-basis, company-basis or other appropriate basis: operators will be required, in a known way, to sign e.g. by means of a user name and password to obtain secure access. The "check-out" and "check-in" of samples is accordingly registered in the name of the person undertaking the action and movements and/or histories of samples may be traced to the appropriate person accordingly.

io In an exemplary embodiment of the invention a mobiie computing device can may access and interrogate data stored on the server memory, using the relevant communication channel, and compare with its own derived data. For example, a first and a second mobile computing device may compare its own derived data with the accessed stored data of the other mobile computing device, ie with the second device data and first device data respectively, including where this relates to the same arrays, and, based on said comparison, to identify any disparities therebetween where they relate to the same object, such as that between two images of the same array arising, for example from the unregistered removal of a sample. In this way, unrecorded and unregistered removals, or unexpected vacancies or gaps in an array may be recognized as "missing" samples.

In an exemplary aspect of the apparatus and method herein disclosed, the artificial intelligence module (AIM), referred to above, is also suitable for identifying changes in sample array and will "notice" changes, such as the unregistered removal of a sample.

The artificial intelligence module in receipt of a new image of a sample array compares this array with other arrays held in the memory, thereby identifying two photographs with a high degree of similarity as well as any discrepancies between them, such as a removedldisplaced sample, which may be present in one but not in the other. In this way, unrecorded and unregistered removals, or unexpected vacancies or gaps in an array may be interpreted by the artificial intelligence module (AIM) as "missing" samples. This can trigger various procedures, including messages to all registered users of the system or users specifically associated in the database with the missing sample, that the sample is no longer located in its previously registered position, possibly with an enquiry to the relevant persons as to its current physical location, so it can be traced and re-registered. A user, in possession of the sample in question, perhaps at a workbench or in a laboratory etc, would be alerted by the message, and may respond appropriately, including by replacing the sample in its previous location or a new iocation, and capturing an image, as appropriate.

Whenever new input is received, such as a newly captured image of an array, the AIM performs an enquiry on such inputs, and extracts all relevant data for entry into the database or interrogation thereof as appropriate. The AIM acts upon all such input to update the database as appropriate.

Although this disclosure makes reference to several examples of the aspects and embodiments, it will be readily understood that embodiments of the invention are not restricted to those which are explicitly referenced herein: all aspects and embodiments may be modified to comprise any number of amendments, alterations, variations or substitutions, including those which may not be explicitly referenced herein. The embodiments and examples are lo described for the purpose of explanation and are not intended to limit the scope of the claims in any way. It will be apparent to the reader that variations may be made to the embodiments described herein that fall within the scope of the invention which is defined in the claims. The present disclosure covers any variations, amendments and modifications which fall within the scope of the accompanying claims and their equivalents.

Where some features of various examples or embodiments appear in some examples, embodiments or drawings and not in others, this is only for brevity and intelligibility. Accordingly, any component or feature of any example, embodiment or figure may, in combination with any component or feature of any other example, embodiment or figure, referenced or claimed. Components, features and structures of the aspects and embodiments disclosed herein may be combined, as appropriate. Even if such combinations are not illustrated, or explicitly referenced herein, in relation to a particular aspect of an embodiment, this is just for brevity and should not be understood to mean that such combinations are excluded or cannot occur: the different features and of the various aspects and embodiments may be mixed and combined as appropriate and this disclosure should be construed as covering all combinations and permutations of features referenced herein.

Claims

CLAIMSA system for managing laboratory samples comprising at least a first mobile computing device comprising a display, a camera for capturing an image of an array of stored laboratory samples stored in a storage unit, a processor for rendering the image of the array on the display, a means for inputting a tag of at least one sample in the array and an intra-array location, within the image, of the at least one sample, and a memory for storing at least the input tag and corresponding intra-array location of the at least one sample.
2. A system as in any previous claim, wherein the means for inputting is a user interface, comprising means for manually inputting at least one of the tag and the intra-array location.
3. A system as in any previous claim, and further comprising a server and at least one communications channel configured to communicate first device data between the at least one mobile computing device and the server, wherein the server comprises a server processor for processing said data and a server memory for storing said data.
4. A system as in Claim 3, wherein at least one of the at least one mobile computing device and the server further comprises an artificial intelligence module for identifying the at least one sample in the image, assigning the tag and determining the intra-array location.
A system as in Claim 4, wherein the artificial intelligence module is configured to communicate with the server processor and server memory, and to access, interrogate, modify or delete any of said data stored in said server memory.
6. A system as in any one of Claims 3 to 5, further comprising at least a second mobile computing device, having at least the same components as the first mobile computing device, and at least a second communications channel configured to communicate second device data between the at least a second computing device and the server.
7 A system as in Claim 6, wherein the first and second mobile computing devices, are both configured to access each of the first device data and second device data stored at the server memory, using the first and second communications channels respectively, and further configured to interact with the server processor, using the first and second communications channels respectively, and modify the said data stored at the server memory.
8. A system as in Claim 7, wherein the first and second mobile computing devices are further configured to compare the accessed data with the first device data and second device data respectively, and, based on said comparison, to identify any disparities therebetween.
9. A system as in any one of Claims 3 to 7, wherein the artificial intelligence module is further configured to compare the data stored on the server memory with first device data, and, based on said comparison, to identify any disparities therebetween.
10. A system as in any one of Claims 8 to 9, wherein the first and second mobile computing devices, and the artificial intelligence module, are further configured to identify, based on said comparison, removals or absences of samples from any array.is
11. A system as in any preceding claim, wherein the intra-array location of the at least one sample is the x-and y-coordinates, within the image of the array, of the at least one sample.
12. A system as in any preceding claim, wherein the tag comprises at least one of a unique identifier of the at least one sample and a date associated with the at least one sample.
13. A system as in any preceding claim, wherein the tag comprises a metatag containing a combination of metadata.
14. A system as in any of Claims 3 to 13, wherein at least one of the input means or the artificial intelligence module is configured to input at least one of a. the location, within the storage unit, of the array.b. the location, within the storage unit, of the array, the location being a shelf, or part of a shelf, of the storage unit.c. the location, in an identified building, of the storage unit, the storage unit being one of a cupboard, a fridge or a freezer.
15. A method of managing laboratory samples comprising: capturing, by a camera of a first mobile computing device, an image of an array of stored laboratory samples stored in a storage unit, - rendering, by a processor of the first mobile computing device, the image of the array on a display of the computing device, - identifying, manually or by an artificial intelligence module, the at least one sample in the image, assigning, manually or by an artificial intelligence module, at least a first tag of the identified sample and determining, manually or by an artificial intelligence module, the intra-array location, within the image, of the identified sample, - inputting at least the first tag and the first intra-array location, - storing in a memory at least the first input tag and the first intra-array location of io the at least one sample
16. A method as in Claim 15, wherein the tag comprises at least one of a unique identifier of the at least one sample and a date associated with the at least one sample.
17. A method as in any of Claims 15 to 16, wherein the intra-array location of the at least one sample is the x-and y-coordinates, within the image of the array, of the at least one sample
18. A method as in any of Claims 15 to 17, wherein the inputting further comprises inputting at least one of a. the location, within the storage unit, of the array.b. the location, within the storage unit, of the array, the location being a shelf, or part of a shelf, of the storage unit.c. the location, in an identified building, of the storage unit.
19. A method as in any of Claims 15 to 18, further comprising: - communicating, using a first communication channel, between said first mobile computing device and a server, first device data comprising at least the said first tag and first intra-array location, - processing, by a server processor at the server, said first device data - storing, at a server memory in the server, said first device data.
20. A method as in any of Claims 15 to 19, further comprising.- capturing, by a camera in a second mobile computing device, at least a second image of a second array of stored laboratory samples stored in a storage unit, - rendering, by a processor of the second mobile computing device, the at least second image on the display of the second mobile computing device, identifying, manually or by an artificial intelligence module, the at least one second sample in the second image, assigning, manually or by an artificial intelligence module, at least a second tag of the identified sample and determining, manually or by an artificial intelligence module, the second intraarray location, within the image, of the identified second sample, -inputting, at an input means of the second mobile computing device, at least second device data, comprising at least a second tag of the at least one second sample in the array and a second intra-array location, within the second image, of the at least one second sample, storing, at at least one of a memory of the second mobile computing device and the server memory, second device data, comprising at least the second input tag and corresponding second intra-array location of the at least one second sample.
21. A method as in Claim 20 further comprising: - accessing, by the second mobile computing device, using a second communications channel configured to communicate between the at least second mobile computing device and the server, said first device data stored at the server memory.
22. A method as in Claim 21, further comprising: - communicating, by the artificial intelligence module, with the server processor and server memory, and accessing, interrogating, modifying or deleting, by the artificial intelligence module, any of said data stored in said server memory.
23. A method as in any of Claims 21 or 22, wherein the second device data further comprises at least the second array image, and second array image relates to the same array as the first array image, further comprising: - comparing, by the processor of the second mobile computing device, the second device data with the accessed first device data, and - determining, by the processor of the second mobile computing device, for the first or second input tag, any disparities between the first array image and the second array image, based on the comparison.
24. A method as in any of Claims 20 to 23 further comprising: -interacting, via a user interface of the second mobile computing device and the second communications channel, with the server processor, and modifying the said first data stored at the server memory using the second communications channel.
25. A method implemented by a system, comprising one or more computing devices in io communication with a server, the method comprising the steps of any of Claims 15 to 24.
26. A computer program product comprising program code instructions stored on a computer readable medium to execute the method steps according to any one of Claims 15 to 24 when said program is executed on a computer.
27. A computing system, comprising one or more computing devices in communication with a server, configured to execute the method steps according to any one of the Claims 15 to 24.