# US 2021/0241864 A1 · Trial design with simulated annealing > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0241864 A1 - Document ID: US20210241864A1 - Status: Published application - Kind: A1 - Application number: 17/163,436 - 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/US20210241864A1 ## 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 simulated annealing includes obtaining, via at least one processor of a trial design platform, initial trial design simulation results data for a set of trial designs. The method may further include identifying an initial design from the design simulation results data, predicting, performance data of designs for variations of parameters corresponding to the set of trial designs, and identifying a new design for simulation by varying parameters of the initial simulated design based on the predicting. The method may also include simulating the new design, determining performance data of the new design, and identifying a second new design for simulation by varying parameters of the new design based on the simulated performance of the new design. ## Claims ### Claim 1 A method comprising: obtaining, via at least one processor of a trial design platform, initial trial design simulation results data for a set of trial designs and generated, in part, via the trial design platform; identifying, via the at least one processor, an initial design from the design simulation results data; predicting, via the at least one processor, performance data of designs for variations of parameters corresponding to the set of trial designs; identifying, via the at least one processor, a new design for simulation by varying parameters of the initial simulated design based on the predicting; simulating, via the at least one processor, the new design and determining, via the at least one processor, performance data of the new design; and identifying, via the at least one processor, a second new design for simulation by varying parameters of the new design based on the simulated performance of the new design. ### Claim 2 (depends on 1) The method of claim 1, wherein the initial design is a Pareto design. ### Claim 3 (depends on 1) The method of claim 1, wherein the initial design is a convex hull design. ### Claim 4 (depends on 1) The method of claim 1, wherein the predicting is based on historical data. ### Claim 5 (depends on 1) The method of claim 1, wherein the predicting is based on Delaunay triangulations. ### Claim 6 (depends on 1) The method of claim 1, wherein variations of different parameters are simulated in parallel. ### Claim 7 (depends on 1) The method of claim 1, further comprising: determining, via the at least one processor, a magnitude of variations based on historical data. ### Claim 8 (depends on 1) The method of claim 1, wherein varying of the parameters is directed to gaps in the simulated designs. ### Claim 9 (depends on 1) The method of claim 1, wherein varying of the parameters is based on a parameter priority rating. ### Claim 10 (depends on 1) The method of claim 1, wherein the initial trial design simulation results data provides a coarse representation of design options. ### 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 initial trial design simulations results data 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 initial trial design simulations results data based at least in part on a relationship between the initial trial design simulations results data and supplemental data; generating a performance surface based at least in part on a set of trial designs corresponding to the initial trial design simulations results data; 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 initial trial design simulations results data. ### Claim 12 An apparatus comprising: an analysis circuit structured to receive data for an initial design; an evaluation circuit structured to vary parameters of the initial design to generate a second design; and a simulation circuit configured for simulating the second design and determining a performance of the second design; wherein the evaluation circuit is further structured to vary parameters of the second design to generate a third design based at least in part on the performance of the second design. ### Claim 13 (depends on 12) The apparatus of claim 12, wherein the initial design is a Pareto design. ### Claim 14 (depends on 12) The apparatus of claim 12, wherein the initial design is a convex hull design. ### Claim 15 (depends on 12) The apparatus of claim 12, wherein the evaluation circuit is structured to predict the performance of the second design based on historical data. ### Claim 16 (depends on 12) The apparatus of claim 12, wherein the evaluation circuit is structured to predict the performance of the second design based on Delaunay triangulations. ### Claim 17 (depends on 12) The apparatus of claim 12, wherein variations of different parameters are simulated in parallel. ### Claim 18 (depends on 12) The apparatus of claim 12, further comprising: determining one or more magnitudes of variations of parameters based on historical data. ### Claim 19 (depends on 12) The apparatus of claim 12, wherein variations of parameters are directed to gaps in the simulated designs. ### Claim 20 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 and a memory device that stores an application that adapts the at least one processor to: obtain initial trial design simulation results data for a set of trial designs; identify an initial design from the design simulation results data; predict performance for designs for variations of parameters; identify a new design for simulation by varying parameters of the initial simulated design based on the predicting; simulate the new design and determine the performance of the new design; identify a second new design for simulation by varying parameters of the new design based on the simulated performance of the new design; and transmit, to the electronic device, data structured for display on the electronic display and corresponding to the second new design.