IP Library Granted Patent US 10,748,654
Granted Patent B2
US 10,748,654 · App. 15/193,676 · Granted Aug 18, 2020

Normalizing data sets for predicting an attribute of the data sets

Inventors: Piotr J. Chaba (Wilmington, NC); Daniel J. Baker (Letchworth, GB)
Assignee: PRA Health Sciences, Inc.
G16H40/20G16H10/20
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Quick Facts
Patent No.
US 10,748,654
App. No.
15/193,676
Granted
Aug 18, 2020
Kind
B2
Abstract

Systems and methods are provided for improving communication by various computing systems in a network. Each computing system can be used to receive and process data. The data can be associated with a process represented by a chain of tasks. The computing systems can determine various parameters associated with the chain of tasks for determining a risk associated with the chain of tasks. The computing system can also determine a risk associated with multiple chains of tasks and aggregate the risks associated with the multiple chains of tasks. Determining the risk associated with each chain of tasks in the multiple chains of tasks can normalize a risk represented by the chains of tasks. Determining the risk associated with each chain of tasks or normalizing the risks represented by the chains can improve communication by the various computing systems in the network.

Claims (106)

1. A method executed by a computing system that monitors one or more aspects of a clinical trial, the method comprising:

receiving, by a processing device of the computing system that monitors the one or more aspects of the clinical trial, a data set associated with the clinical trial, wherein the data set specifies a plurality of tasks to be completed for planning or implementing the clinical trial and a predetermined date by which the plurality of tasks are to be completed;

storing, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, the data set in a memory device of the computing system;

generating, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, a chain of tasks based on the stored data by determining a relationship between tasks in the plurality of tasks and electronically converting the stored data into the chain of tasks based on the relationship;

receiving, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, a first subset of data associated with the chain of tasks, wherein the first subset of data indicates a progress of completing the chain of tasks;

determining, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, a buffer index associated with the chain of tasks based on the first subset of data, the buffer index being a numerical value indicating a likelihood of the chain of tasks being completed by the predetermined date;

allocating, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, computing resources for subsequent use by the processing device of the computing system based on the buffer index by adjusting an amount of the computing resources that are allocated for subsequent use by the processing device depending on the buffer index; and

generating, by the processing device of the computing system that monitors the one or more aspects of the clinical trial, an interface for display that includes information about the chain of tasks, the first subset of data, or the buffer index.

2. The method of claim 1 , further comprising:

generating, by the processing device, a plurality of chains of tasks based at least in part on the stored data;

determining, by the processing device, a plurality of buffer indices associated with the plurality of chains of tasks, wherein each respective buffer index among the plurality of buffer indices associated with a respective chain of tasks and is determined by:

receiving a respective dataset corresponding to the respective chain of tasks, the respective dataset indicating a respective progress of completing the respective chain of tasks; and

determining the respective buffer index corresponding to the respective chain of tasks based on the respective dataset, the respective buffer index indicating a respective likelihood of the respective chain of tasks being completed by the predetermined date; and

ranking, by the processing device, the plurality of chains of tasks based on the plurality of buffer indices, each respective chain tasks being assigned a respective rank based on the respective likelihood of the respective chain of tasks being completed by the predetermined date.

3. The method of claim 1 , wherein the first subset of data includes:

a relationship indicator representing the relationship between tasks in the chain of tasks;

a challenging time associated with a task in the chain of tasks, the challenging time corresponding to an amount of time for completing the task;

an implementation indicator associated with the task in the chain of tasks, the implementation indicator representing an amount of time remaining before completing the task; and

a buffer period associated with the chain of tasks, the buffer period representing an amount of time after a final task in the chain of tasks.

4. The method of claim 3 , wherein determining the buffer index associated with the chain of tasks based on the first subset of data includes:

determining, by the processing device, a chain duration based at least in part on the challenging time, the chain duration representing an amount of time for completing the chain of tasks;

determining, by the processing device, an amount of time remaining before completing the chain of tasks based on the amount of time remaining before completing the task and a challenging time associated with another task in the chain of tasks; and

determining, by the processing device, a chain percentage by comparing the chain duration and the amount of time remaining before completing the chain of tasks.

5. The method of claim 4 , wherein determining the buffer index associated with the chain of tasks based on the first subset of data includes:

determining, by the processing device, a remaining buffer period for the chain of tasks based on the implementation indicator and the buffer period by comparing the amount of time remaining before completing the task in the chain of tasks and the buffer period, wherein the remaining buffer period indicates an amount of the buffer period remaining; and

determining, by the processing device, a buffer percentage by comparing the buffer period and the remaining buffer period.

6. The method of claim 5 , wherein determining the buffer index associated with the chain of tasks based on the first subset of data further includes:

determining, by the processing device, the buffer index by comparing the chain percentage and the buffer percentage;

determining, by the processing device, whether the buffer index is above or below a risk threshold by comparing the buffer index to the risk threshold;

outputting, by the processing device, data corresponding to the buffer index via the interface; and

outputting, by the processing device, a risk level indicating the likelihood of completing the chain of tasks by the predetermined date in response to determining that the buffer index is above or below the risk threshold.

7. The method of claim 6 , further comprising:

receiving, by the processing device, a desired buffer index; and

adjusting, by the processing device, the buffer index to a new value based on: i) the desired buffer index; ii) the predetermined date; and iii) the buffer period for the chain of tasks.

8. The method of claim 1 , further comprising:

receiving, by the processing device, a second subset of data; and

determining, by the processing device, an updated buffer index associated with the chain of tasks based on the second subset of data, the updated buffer index corresponding to an updated likelihood of completing the chain of tasks by the predetermined date; and

generating, by the processing device, an updated interface for display that includes data associated with the chain of tasks, the second subset of data, or the updated buffer index.

9. A system configured to monitor one or more aspects of a clinical trial, the system comprising:

a processing device; and

a non-transitory computer-readable medium communicatively coupled to the processing device, wherein the processing device is configured to perform operations for monitoring the one or more aspects of the clinical trial, the operations comprising:

receiving a data set associated with the clinical trial, wherein the data set specifies a plurality of tasks to be completed for planning or implementing the clinical trial and a predetermined date by which the plurality of tasks are to be completed;

storing the data set;

generating a chain of tasks based on the stored data by determining a relationship between tasks in the plurality of tasks and electronically converting the stored data into the chain of tasks based on the relationship;

receiving a first subset of data associated with the chain of tasks, wherein the first subset of data indicates a progress of completing the chain of tasks;

determining a buffer index associated with the chain of tasks based on the first subset of data, the buffer index being a numerical value indicating a likelihood of the chain of tasks being completed by the predetermined date;

allocating computing resources for subsequent use by the processing device of the system based on the buffer index by adjusting an amount of the computing resources that are allocated for subsequent use by the processing device depending on the buffer index; and

generating an interface for display that includes information about the chain of tasks, the first subset of data, or the buffer index.

10. The system of claim 9 , wherein the processing device is further configured to:

generate a plurality of chains of tasks based at least in part on the stored data;

determine a plurality of buffer indices associated with the plurality of chains of tasks, wherein each respective buffer index among the plurality of buffer indices associated with a respective chain of tasks and is determined by:

receiving a respective dataset corresponding to the respective chain of tasks, the respective dataset indicating a respective progress of completing the respective chain of tasks; and

determining the respective buffer index corresponding to the respective chain of tasks based on the respective dataset, the respective buffer index indicating a respective likelihood of the respective chain of tasks being completed by the predetermined date; and

rank the plurality of chains of tasks based on the plurality of buffer indices, each respective chain tasks being assigned a respective rank based on the respective likelihood of the respective chain of tasks being completed by the predetermined date.

11. The system of claim 9 , wherein the first subset of data includes:

a relationship indicator representing the relationship between tasks in the chain of tasks;

a challenging time associated with a task in the chain of tasks, the challenging time corresponding to an amount of time for completing the task;

an implementation indicator associated with the task in the chain of tasks, the implementation indicator representing an amount of time remaining before completing the task; and

a buffer period associated with the chain of tasks, the buffer period representing an amount of time after a final task in the chain of tasks.

12. The system of claim 11 , wherein the processing device is further configured to determine the buffer index associated with the chain of tasks based on the first subset of data by:

determining a chain duration based at least in part on the challenging time, the chain duration representing an amount of time for completing the chain of tasks;

determining an amount of time remaining before completing the chain of tasks based on the amount of time remaining before completing the task and a challenging time associated with another task in the chain of tasks; and

determining a chain percentage by comparing the chain duration and the amount of time remaining before completing the chain of tasks.

13. The system of claim 12 , wherein the processing device is further configured to determine the buffer index associated with the chain of tasks based on the first subset of data by:

determining a remaining buffer period for the chain of tasks based on the implementation indicator and the buffer period by comparing the amount of time remaining before completing the task in the chain of tasks and the buffer period, wherein the remaining buffer period indicates an amount of the buffer period remaining; and

determining a buffer percentage by comparing the buffer period and the remaining buffer period.

14. The system of claim 13 , wherein the processing device is further configured to determine the buffer index associated with the chain of tasks based on the first subset of data by:

determining the buffer index by comparing the chain percentage and the buffer percentage;

determining whether the buffer index is above or below a risk threshold by comparing the buffer index to the risk threshold;

outputting data corresponding to the buffer index via the interface; and

outputting a risk level indicating the likelihood of completing the chain of tasks by the predetermined date in response to determining that the buffer index is above or below the risk threshold.

15. The system of claim 14 , wherein the processing device is further configured to:

receive a desired buffer index; and

adjust the buffer index based on i) the desired buffer index; ii) the predetermined date; and iii) the buffer period for the chain of tasks.

16. A non-transitory computer-readable medium storing program code that is executable by a processing device of a computing system configured to manage one or more aspects of a clinical trial, the program code being executable for causing the processing device to perform operations comprising:

receiving a data set associated with the clinical trial, wherein the data set specifies a plurality of tasks to be completed for planning or implementing the clinical trial and a predetermined date by which the plurality of tasks are to be completed;

storing the data set;

generating a chain of tasks based on the stored data by determining a relationship between tasks in the plurality of tasks and electronically converting the stored data into the chain of tasks based on the relationship;

receiving a first subset of data associated with the chain of tasks, wherein the first subset of data indicates a progress of completing the chain of tasks;

determining a buffer index associated with the chain of tasks based on the first subset of data, the buffer index being a numerical value indicating a likelihood of the chain of tasks being completed by the predetermined date;

allocating computing resources for subsequent use by the processing device of the computing system based on the buffer index by adjusting an amount of the computing resources that are allocated for subsequent use by the processing device depending on the buffer index; and

generating an interface for display that includes information about the chain of tasks, the first subset of data, or the buffer index.

17. The non-transitory computer-readable medium of claim 16 , further comprising program code to cause the computing system to perform the operations of:

generating a plurality of chains of tasks based at least in part on the stored data;

determining a plurality of buffer indices associated with the plurality of chains of tasks, wherein each respective buffer index among the plurality of buffer indices associated with a respective chain of tasks and is determined by:

receiving a respective dataset corresponding to the respective chain of tasks, the respective dataset indicating a respective progress of completing the respective chain of tasks; and

determining the respective buffer index corresponding to the respective chain of tasks based on the respective dataset, the respective buffer index indicating a respective likelihood of the respective chain of tasks being completed by the predetermined date; and

ranking the plurality of chains of tasks based on the plurality of buffer indices, each respective chain tasks being assigned a respective rank based on the respective likelihood of the respective chain of tasks being completed by the predetermined date.

18. The non-transitory computer-readable medium of claim 16 , wherein the first subset of data includes:

a relationship indicator representing the relationship between tasks in the chain of tasks;

a challenging time associated with a task in the chain of tasks, the challenging time corresponding to an amount of time for completing the task;

an implementation indicator associated with the task in the chain of tasks, the implementation indicator representing an amount of time remaining before completing the task; and

a buffer period associated with the chain of tasks, the buffer period representing an amount of time after a final task in the chain of tasks.

19. The non-transitory computer-readable medium of claim 18 , wherein the operation of determining the buffer index associated with the chain of tasks based on the first subset of data includes:

determining a chain duration based at least in part on the challenging time, the chain duration representing an amount of time for completing the chain of tasks;

determining an amount of time remaining before completing the chain of tasks based on the amount of time remaining before completing the task and a challenging time associated with another task in the chain of tasks; and

determining a chain percentage by comparing the chain duration and the amount of time remaining before completing the chain of tasks.

20. The non-transitory computer-readable medium of claim 19 , wherein the operation of determining the buffer index associated with the chain of tasks based on the first subset of data includes:

determining a remaining buffer period for the chain of tasks based on the implementation indicator and the buffer period by comparing the amount of time remaining before completing the task in the chain of tasks and the buffer period, wherein the remaining buffer period indicates an amount of the buffer period remaining;

determining a buffer percentage by comparing the buffer period and the remaining buffer period;

determining the buffer index by comparing the chain percentage and the buffer percentage;

determining whether the buffer index is above or below a risk threshold by comparing the buffer index to the risk threshold; and

determining a risk level indicating the likelihood of completing the chain of tasks by the predetermined date based on whether the buffer index is above or below the risk threshold; and

outputting the risk level.

21. The method of claim 1 , wherein the buffer index is determined based on (i) a buffer percentage specifying how close a buffer period is to being completed, and (ii) a chain percentage specifying how close the chain of tasks is to being completed in its entirety.

22. The method of claim 21 , wherein the buffer index is determined by dividing the buffer percentage by the chain percentage.

Assignments (10)
TERMINATION AND RELEASE OF SECURITY INTEREST IN SPECIFIED PATENTS RECORDED AT REEL 56752, FRAME 0410 Recorded Jul 16, 2026
From: CITIBANK, N.A., LONDON BRANCH, AS NOTES COLLATERAL AGENT
To: SOURCE HEALTHCARE ANALYTICS, INC.; PRA HEALTH SCIENCES, INC.
Reel/Frame 076015/0509 →
SECURITY INTEREST Recorded May 22, 2026
From: PRA HEALTH SCIENCES, INC.
To: CITIBANK, N.A., LONDON BRANCH, AS COLLATERAL AGENT
Reel/Frame 074744/0445 →
SECURITY INTEREST Recorded Jun 5, 2024
From: PRA HEALTH SCIENCES, INC.
To: CITIBANK N.A., LONDON BRANCH., AS NOTES COLLATERAL AGENT
Reel/Frame 067623/0652 →
SECURITY AGREEMENT Recorded Jul 2, 2021
From: SOURCE HEALTHCARE ANALYTICS, INC.; PRA HEALTH SCIENCES, INC.
To: CITIBANK, N.A., LONDON BRANCH
Reel/Frame 056752/0410 →
RELEASE OF SECURITY INTEREST IN PATENTS (RELEASES RF 050890/0571) Recorded Jul 1, 2021
From: PNC BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
To: PRA HEALTH SCIENCES, INC.
Reel/Frame 056751/0749 →
SECURITY INTEREST Recorded Jul 1, 2021
From: PRA HEALTH SCIENCES, INC.
To: CITIBANK, N.A., LONDON BRANCH, AS COLLATERAL AGENT
Reel/Frame 056735/0249 →
SECURITY INTEREST Recorded Nov 1, 2019
From: PRA HEALTH SCIENCES, INC.
To: PNC BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 050890/0571 →
TERMINATION AND RELEASE OF SECURITY INTEREST IN PATENTS (RELEASES RF 040696/0779) Recorded Oct 31, 2019
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: PRA HEALTH SCIENCES, INC.
Reel/Frame 050901/0228 →
SECURITY INTEREST Recorded Dec 20, 2016
From: PRA HEALTH SCIENCES, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 040696/0779 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 27, 2016
From: CHABA, PIOTR J; BAKER, DANIEL J
To: PRA HEALTH SCIENCES, INC
Reel/Frame 039019/0114 →
Continuity (2)
Provisional Application 62188065 · Jul 2, 2015
Related Publication 20170004412A1 · Jan 5, 2017