Abstract: A method for determining trial designs is provided. The method includes receiving, via at least one processor, one or more trial design criteria and one or more scenarios corresponding to a set of trial designs, and generating, via the at least one processor, simulation data based at least in part on replicating each of the set of trial designs with the one or more trial design criteria and the one or more scenarios. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria. The method further includes determining, via the at least one processor, an optimality criteria for evaluating the trial designs, searching, within the set of trial designs, via the at least one processor, for globally optimum designs based on the optimality criteria, and transmitting, via the at least one processor, globally optimum designs.

Abstract: A method for determining trial designs that includes obtaining simulation data for a set of trial designs that includes combinations of design options for a set of criteria. The simulation data includes performance parameters and performance parameter values associated with each design in the set of trial designs for the set of criteria. The method further includes determining an optimality criteria for evaluating the trial designs. The optimality criteria includes at least one of Pareto optimality or convex hull optimality for clinical trial design performance values. The method further includes: determining at least one of a cooling cycle, a parameter change, or a direction; and searching, within the set of trial designs, for a set of globally optimum designs based on the optimality criteria using simulated annealing. The simulated annealing is based at least in part on at least one of the cooling cycle, the parameter change, or the direction.

Abstract: A method for determining trial designs is provided. The method includes obtaining simulation data for a set of trial designs. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria; determining an optimality criteria for evaluating the trial designs; searching, within the set of trial designs, for globally optimum designs based on the optimality criteria; and recommending globally optimum designs.

Abstract: A method, according to some implementations, includes obtaining trial design simulation results for a set of trial designs and determining a set of Pareto designs in the set of trial designs based at least in part on the trial design simulation results and one or more performance parameters. The method further includes determining a set of convex hull designs in the set of trial designs, determining a set of recommended designs based at least in part on the set of Pareto designs and the set of convex hull designs, and transmitting the set of recommended designs.

Abstract: A method for searching clinical trial designs that includes: determining a first convex hull set from a first set of clinical trial designs for a first scenario; simulating the first convex hull set for a second scenario to determine first simulation results; removing the first convex hull set from the first set of clinical trial designs to generate a second set of clinical trial designs; determining a second convex hull set from the second set of clinical trial designs for the first scenario; simulating the second convex hull set for the second scenario to determine second simulation results; determining, based at least in part on the first simulation results and the second simulation results, a refined scenario convex hull set of clinical trial designs for the second scenario from the first convex hull set and the second convex hull set; and transmitting the refined scenario convex hull set.

Abstract: A method for determining trial designs is provided. The method includes receiving, via at least one processor, one or more trial design criteria and one or more scenarios corresponding to a set of trial designs, and generating, via the at least one processor, simulation data based at least in part on replicating each of the set of trial designs with the one or more trial design criteria and the one or more scenarios. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria. The method further includes determining, via the at least one processor, an optimality criteria for evaluating the trial designs, searching, within the set of trial designs, via the at least one processor, for globally optimum designs based on the optimality criteria, and transmitting, via the at least one processor, globally optimum designs.

Abstract: A method for trial design includes presenting on a graphical interface, a set of cards, wherein each card in the set is representative of a different trial design from a set of trial designs. The method further includes: monitoring a first set of user interactions with the set of cards; determining a user preference for one or more values of one or more parameters of the set of trial designs from the first set of user interactions; and presenting on the graphical interface a new card that is representative of a trial design consistent with the determined user preference. The method may also include monitoring a second set of user interactions with the new card and refining the determined user preference based at least in part on the second set of user interactions with the new card.

Abstract: A method for determining trial designs is provided. The method includes receiving, via at least one processor, one or more trial design criteria and one or more scenarios corresponding to a set of trial designs, and generating, via the at least one processor, simulation data based at least in part on replicating each of the set of trial designs with the one or more trial design criteria and the one or more scenarios. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria. The method further includes determining, via the at least one processor, an optimality criteria for evaluating the trial designs, searching, within the set of trial designs, via the at least one processor, for globally optimum designs based on the optimality criteria, and transmitting, via the at least one processor, globally optimum designs.

Abstract: A waste extraction system includes a precipitation tank comprising a waste stream input, a solution input, and a waste stream output, wherein the waste stream input is fluidly coupled to an upstream segment of a main waste pathway, a column effluent tank, an adsorption column positioned between and fluidly coupled to the precipitation tank and the column effluent tank along the main waste pathway, wherein the adsorption column houses an ion exchange resin and is positioned downstream the precipitation tank, a solution pathway extending from a solution source to the solution input of the precipitation tank, the solution source housing an alkaline solution, and a particle filtration unit positioned between and fluidly coupled to the precipitation tank and the adsorption column.

Abstract: A method, according to some implementations, includes generating a plurality of base datasets using a random number generator and determining scenario specifications. The method may further include identifying at least one transformation function for at least one of the plurality of base datasets based on the scenario specifications and transforming the at least one of the plurality of base datasets using the at least one transformation function. In some cases, the method may also include generating scenario parameters based on the at least one transformed datasets.

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.

Abstract: A method, according to some implementations, includes displaying an interface structured to evaluate design data by a group of users and identifying user parameters for each user in the group. The method ma further include configuring the interface for each user in the group based at least in part on the user parameters, receiving, via the interface, user input data from one or more users in the group, and scoring designs based on the user input and user parameters.

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.

Abstract: A method, according to some implementations, includes obtaining trial design simulation results for a set of trial designs and determining a set of Pareto designs in the set of trial designs based at least in part on the trial design simulation results and one or more performance parameters. The method further includes determining a set of convex hull designs in the set of trial designs, determining a set of recommended designs based at least in part on the set of Pareto designs and the set of convex hull designs, and transmitting the set of recommended designs.

Abstract: A method for trial design includes presenting on a graphical interface, a set of cards, wherein each card in the set is representative of a different trial design from a set of trial designs. The method further includes: monitoring a first set of user interactions with the set of cards; determining a user preference for one or more values of one or more parameters of the set of trial designs from the first set of user interactions; and presenting on the graphical interface a new card that is representative of a trial design consistent with the determined user preference. The method may also include monitoring a second set of user interactions with the new card and refining the determined user preference based at least in part on the second set of user interactions with the new card.

Abstract: A method, according to some implementations, includes providing inputs to a plurality of trial design simulation engines, receiving first outputs of the plurality of trial design simulation engines in response to the inputs, and providing variations of the inputs to the plurality of trial design simulation engines. The method may further include receiving second outputs of the plurality of trial design simulation engines in response to the variations evaluating the first and the second outputs to determine delta values, and determining, based in part on the delta values, a plurality of normalization factors for the plurality of trial design simulation engines.

Abstract: A method for determining trial designs is provided. The method includes receiving, via at least one processor, one or more trial design criteria and one or more scenarios corresponding to a set of trial designs, and generating, via the at least one processor, simulation data based at least in part on replicating each of the set of trial designs with the one or more trial design criteria and the one or more scenarios. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria. The method further includes determining, via the at least one processor, an optimality criteria for evaluating the trial designs, searching, within the set of trial designs, via the at least one processor, for globally optimum designs based on the optimality criteria, and transmitting, via the at least one processor, globally optimum designs.

Abstract: A method, according to some implementations, includes determining, via at least one processor, a plurality of possible sites for recruiting patients from for a trial and determining, via the at least one processor and for each of one or more subgroupings of the plurality of possible sites, a predicted patient recruitment value. The method may include determining, via the at least one processor, a candidate subgrouping of the plurality of possible sites having a predicted patient recruitment value that globally optimizes a desired site selection criteria, and transmitting, via the at least one processor, data corresponding to the candidate subgrouping.

Abstract: A method, according to some implementations, includes receiving, via at least one processor, output data of a plurality of trial design simulations for a plurality of scenarios and evaluating, via the at least one processor, the output data to determine changes in performance over the plurality of scenarios. The method may further include generating, via the at least one processor, visual tornado diagram data structured to generate a visual tornado diagram on an electronic display of an electronic device and transmitting, via the at least one processor, the visual tornado diagram data to the electronic device.