# US 2021/0240885 A1 · Trial design with pareto techniques

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- Number: US 2021/0240885 A1
- Document ID: US20210240885A1
- Status: Published application
- Kind: A1
- Application number: 17/163,430
- Filed: 2021-01-30
- Published: 2021-08-05
- Earliest claimed: 2020-01-31
- Applicants: Cytel Inc.
- Inventors: Jaydeep Bhattacharya; James Bolognese; Alexandre Buer; Eric Edwards; Stanley Y. Huang; Yannis Jemiai; Cyrus Mehta; Nitin Patel; Anne Pelz; Ajay Prabhakar Sathe; Joshua A. Schultz; Pralay Senchaudhuri
- Web page: https://patentgrep.com/patent/US20210240885A1

## CPC

- G16H 10/20: for electronic clinical trials or questionnaires
- G06F 30/10: Geometric CAD
- G06F 30/12: characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
- G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30)
- G06F 30/27: using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
- G06N 3/08: Learning methods
- G06N 3/09: Supervised learning
- G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
- G06N 5/04: Inference or reasoning models
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- G06Q 10/06315: {Needs-based resource requirements planning or analysis}
- G06Q 10/067: Enterprise or organisation modelling
- G06Q 10/0674: {using process simulation}
- G06Q 10/101: Collaborative creation, e.g. joint development of products or services
- G06Q 30/0205: {based on location or geographical consideration}
- G16H 40/20: for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
- G16H 40/67: for remote operation
- G16H 50/50: for simulation or modelling of medical disorders
- G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients
- G06F 3/0484: for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F 2111/02: CAD in a network environment, e.g. collaborative CAD or distributed simulation
- G06F 2111/04: Constraint-based CAD
- G06F 2111/06: Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
- G06F 2111/08: Probabilistic or stochastic CAD
- G06F 2111/16: Customisation or personalisation
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A method for trial design with pareto techniques is provided. The method includes obtaining trial design simulation results for a set of trial designs and determining a score for each trial design based on a performance criteria. The method further includes evaluating Pareto optimality for each design in the set of trial designs to determine a Pareto frontier, filtering designs that are not on the Pareto frontier, and communicating the Pareto frontier designs.

## Claims

### Claim at position 1

1-475. (canceled)

### Claim 476

A method comprising:
obtaining trial design simulation results for a set of trial designs;
determining a score for each trial design based on a performance criteria;
evaluating Pareto optimality for each design in the set of trial designs to determine a Pareto frontier;
filtering designs that are not on the Pareto frontier; and
communicating the Pareto frontier designs.

### Claim 477 (depends on 476)

The method of claim 476 further comprising:
recommending designs within epsilon-distance from the Pareto frontier.

### Claim 478 (depends on 476)

The method of claim 476 further comprising:
identifying separations in the Pareto frontier and performing simulated annealing based on the separations.

### Claim 479 (depends on 476)

The method of claim 476 further comprising:
identifying different design types on the Pareto frontier and recommending different design types.

### Claim 480 (depends on 476)

The method of claim 476 further comprising:
identifying a second level Pareto frontier.

### Claim 481 (depends on 477)

The method of claim 477 further comprising:
receiving feedback for recommended designs and determining epsilon values for additional recommendations.

### Claim 482 (depends on 476)

The method of claim 476 further comprising:
clustering designs dominated by designs in the Pareto frontier.

### Claim 483 (depends on 476)

The method of claim 476 further comprising:
clustering designs that are within a margin of error.

### Claim 484 (depends on 476)

The method of claim 476 further comprising:
updating the Pareto designs in response to at least one of addition or subtraction of designs from the set of trial designs.

### Claim 485 (depends on 476)

The method of claim 476, further comprising:
updating the Pareto designs in response to an update of scenario probabilities.

### Claim 486 (depends on 476)

The method of claim 476, further comprising:
evaluating historical trial design selections to identify one or more trial design parameters based at least in part on one or more trial design criteria determined from a user via an interactive interface, wherein obtaining the trial design simulation results is based at least in part on a quick search data structure and the one or more trial design parameters;
generating a substitute for at least some of the trial design simulation results based at least in part on a relationship between the trial design simulation results and supplemental data;
generating a performance surface based at least in part on the set of trial designs;
evaluating one or more trial designs based at least in part on the performance surface; and
calculating a score based on normalized score component values corresponding to the design simulation results.

### Claim 487

An apparatus comprising:
a data processing circuit configured to obtain design data for a set of trial designs;
an optimality determining circuit configured to determine optimum designs using Pareto analysis from the set of trial designs; and
a design analysis circuit configured to analyze the Pareto designs and determine a modification to the Pareto analysis;
wherein the optimality determining circuit received the modification and determines a second set of optimum designs.

### Claim 488 (depends on 487)

The apparatus of claim 487, wherein the set of trial designs includes all design options for a set of criteria.

### Claim 489 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine designs within epsilon-distance of Pareto designs.

### Claim 490 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine designs dominated by the Pareto designs.

### Claim 491 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine designs clustered by the Pareto designs.

### Claim 492 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine twins of the Pareto designs.

### Claim 493 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine siblings of the Pareto designs.

### Claim 494 (depends on 487)

The apparatus of claim 487, wherein the optimality determining circuit modifies the Pareto analysis to determine second level Pareto designs.

### Claim 495

A system comprising:
an electronic device having an electronic display; and
a server in electronic communication with the electronic device and having at least one processor structured to:
obtain trial design simulation results for a set of trial designs;
determine a score for each trial design based on a performance criteria;
evaluate Pareto optimality for each design in the set of trial designs to determine a Pareto frontier;
filter designs that are not on the Pareto frontier; and
transmit the Pareto frontier designs to the electronic device;
wherein the electronic device displays the Pareto frontier on the electronic display.

### Claim at position 22

496-696. (canceled)