# US 2021/0240884 A1 · Trial design with convex-hull techniques

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- Number: US 2021/0240884 A1
- Document ID: US20210240884A1
- Status: Published application
- Kind: A1
- Application number: 17/163,429
- 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/US20210240884A1

## 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, according to some implementations, 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 may further include evaluating the designs in the set of trial designs to determine a convex hull for the set of trial designs, filtering designs based on the convex hull, and communicating the convex hull designs.

## Claims

### Claim 1

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 the designs in the set of trial designs to determine a convex hull for the set of trial designs;
filtering designs based on the convex hull; and
communicating the convex hull designs.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
recommending designs within epsilon-distance from designs on the convex hull.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
identifying facets in the convex hull and performing simulated annealing based on the facets.

### Claim 4 (depends on 1)

The method of claim 1, further comprising:
identifying different design types on the convex hull and recommending different design types.

### Claim 5 (depends on 1)

The method of claim 1, further comprising:
identifying a second level convex hull.

### Claim 6 (depends on 2)

The method of claim 2, further comprising:
receiving feedback for recommended designs and determining epsilon values for additional recommendations.

### Claim 7 (depends on 1)

The method of claim 1, further comprising:
clustering designs dominated by designs in the convex hull.

### Claim 8 (depends on 1)

The method of claim 1, further comprising:
clustering designs that are within a margin of error.

### Claim 9 (depends on 1)

The method of claim 1, further comprising:
updating the convex hull designs in response to at least one of addition or subtraction of designs from the set of trial designs.

### Claim 10 (depends on 1)

The method of claim 1, further comprising:
updating the convex hull designs in response to an update of scenario probabilities.

### Claim 11 (depends on 1)

The method of claim 1, 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; and
evaluating one or more trial designs based at least in part on the performance surface,
wherein calculating the score is further based on normalized score component values corresponding to the trial design simulation results.

### Claim 12

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 convex hull analysis from the set of trial designs; and
a design analysis circuit configured to analyze the convex hull designs and determine a modification to the convex hull analysis;
wherein the optimality determining circuit is further structured to receive the modification and determine a second set of optimum designs.

### Claim 13 (depends on 12)

The apparatus of claim 12, wherein the set of trial designs includes all design options for a set of criteria.

### Claim 14 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine designs within epsilon-distance of convex hull designs.

### Claim 15 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine designs dominated by the convex hull designs.

### Claim 16 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine designs clustered by the convex hull designs.

### Claim 17 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine twins of the convex hull designs.

### Claim 18 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine siblings of the convex hull designs.

### Claim 19 (depends on 12)

The apparatus of claim 12, wherein the optimality determining circuit modifies the convex hull analysis to determine second level convex hull designs.

### Claim 20

A system comprising:
an electronic device including an electronic display; and
a server in electronic communication with the electronic device and including 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 the designs in the set of trial designs to determine a convex hull for the set of trial designs;
filter designs based on the convex hull; and
transmit the filtered designs to the electronic device;
wherein the electronic device is structured to display the filtered designs on the electronic display.