AUTOMATED SCHEDULER FOR LABORATORY EQUIPMENT

• US 20180080949A1
• Filed: 09/14/2017
• Published: 03/22/2018
• Est. Priority Date: 09/21/2016
• Status: Active Application

• Current Assignee: Roche Diagnostics Operations Incorporated (Roche Holding AG)
• Original Assignee: Roche Diagnostics Operations Incorporated (Roche Holding AG)
• Inventors: Jost, Friedrich, Korner, Stephan, Oosterbroeck, Rijk Edwin, Janner, Gabriele Piero
• Application Number:
  US15/704,017
• Publication Number:
  US 20180080949A1
• Time in Patent Office: Days
• CPC Class Codes: G01N 2035/0094 optimisation; experiment design
• CPC Class Codes: G01N 2035/0096 post analysis management of samples, e.g. marking, removing, storing
• CPC Class Codes: G01N 35/0092 Scheduling
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis

Abstract

A method is presented. The method includes receiving at least one order, generating one or more optimization problem instances using one or more resource descriptions of automated laboratory equipment, one or more protocol descriptions of the automated laboratory equipment, an objective function and the at least one order. The method further includes providing the one or more optimization problem instances as input to a constraint optimization solver and processing the one or more optimization problem instances by the constraint optimization solver to generate the schedule of operations to carry out the at least one order on the automated laboratory equipment.

Claims

1. A method for providing a schedule of operations for automated laboratory equipment, the method comprising:

receiving at least one order, wherein each order requires the execution of one or more protocols on the automated laboratory equipment;

generating one or more optimization problem instances using one or more resource descriptions of the automated laboratory equipment, one or more protocol descriptions of the automated laboratory equipment, an objective function and the at least one order, wherein the one or more resource descriptions describe the resources present in the automated laboratory equipment and capabilities and constraints of the resources, wherein each protocol description describes a protocol the automated laboratory equipment can carry out, wherein each protocol description includes a definition of one or more protocol steps to be carried out by the automated laboratory equipment, wherein each protocol description includes one or more constraints to be observed when carrying out the protocol steps on the laboratory equipment, wherein the objective function defines an optimization goal for a schedule of operations for the automated laboratory equipment;

providing the one or more optimization problem instances as input to a constraint optimization solver; and

processing the one or more optimization problem instances by the constraint optimization solver to generate the schedule of operations to carry out the at least one order on the automated laboratory equipment.

2. The method of claim 1, wherein the processing of the one or more optimization problem instances by the constraint optimization solver takes place during run-time of the automated laboratory equipment.

3. The method of claim 2, wherein the processing of the one or more optimization problem instances by the constraint optimization solver takes place during run-time of the automated laboratory equipment in response to a triggering event, wherein the triggering event is one of an arrival of one or more new orders, a change in the resources of the automated laboratory equipment, a user input, a modification of an order forecast, a lapse of a predetermined period of time, an error, an exceptional situation, or a combination of two or more of these events.

4. The method of claim 1, wherein the processing of the one or more optimization problem instances by the constraint optimization solver is repeated automatically in response to the occurrence of a respective triggering event.

5. The method of claim 1, further comprising,

collecting a batch of multiple orders for the automated laboratory equipment;

and

processing the optimization problem instance by the constraint optimization solver to generate a schedule of operations (for the batch of multiple orders at the same time.

6. The method of claim 1, wherein the processing step takes place during development- or design-time of instrument software of the automated laboratory equipment, or wherein the processing step takes place during development- or design-time of schedules of operations of the automated laboratory equipment.

7. The method of claim 1, wherein the method is carried out to simulate a behavior of the automated laboratory equipment, wherein the at least one order is at least one hypothetical order for the automated laboratory equipment and the schedule of operations is a schedule for the at least one hypothetical order.

8. The method of claim 1, further comprising,

changing the one or more resource descriptions, the one or more protocol descriptions and/or the objective function automatically by the automated laboratory equipment during operation, wherein the automatic change happens in response to detecting that resources are not available, an error modus, a user input or state change of the automated laboratory equipment.

9. The method of claim 1, further comprising,

providing the schedule of operations to a controller of the automated laboratory equipment;

and

instructing, by the controller, the automated laboratory equipment to carry out the operations according to the schedule.

10. The method of claim 1, wherein the optimization goal is one of the list of optimizing a throughput of the automated laboratory equipment, processing one or more particular orders as fast possible, using as little of a predetermined resource as possible, balancing of workload of two or more resources, or a combination of these goals.

11. The method of claim 1, wherein the automated laboratory equipment includes a plurality of automated laboratory devices, wherein the orders are orders to be carried out by a plurality of automated laboratory devices and wherein the constraint optimization solver processes the one or more optimization problem instances to generate a schedule of operations for the plurality of automated laboratory devices.

12. The method of claim 1, wherein the automated laboratory equipment is part of a laboratory environment, wherein the orders are orders to be carried out in the laboratory environment and wherein the generic constraint optimization solver processes the one or more optimization problem instances to generate a schedule of workflows in the laboratory environment.

13. The method of claim 1, wherein the protocol descriptions are defined independently of potential solutions for the schedule of operations and wherein the resource descriptions are defined independently of potential solutions for the schedule of operations.

14. A laboratory network, the laboratory network comprising:

automated laboratory equipment; and

a computer system configured to carry out the method of claim 1 to generate the schedule of operations for the automated laboratory equipment.

15. A computer-readable medium including instructions thereon, which when executed by a computer system make the computer system carry out the method of claim 1.