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: Provided herein are methods of treating a subject who has multiple myeloma and has received one to three prior treatment(s). Infusions of chimeric antigen receptor (CAR)-T cells comprising a CAR capable of specifically binding to an epitope of BCMA are administered to the subject.

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: An energy efficient, high-performance reactor (1) for wastewater treatment is disclosed herein. The reactor (1) has a chamber (14) provided with an inlet (11) to allow the entry of the wastewater, and an outlet (21) to allow the treated water to exit. The chamber includes an electrode assembly (13), wherein each of the pair of electrodes includes a layer of metal matrix composites. A polarity switching DC power is provided across the electrode assembly (13), thereby inducing an array of microelectrodes for enhanced surface area and better efficiency for the reaction.

Abstract: Provided herein are methods of treating a subject who has multiple myeloma and has received one to three prior treatment(s). Infusions of chimeric antigen receptor (CAR)-T cells comprising a CAR capable of specifically binding to an epitope of BCMA are administered to the subject.

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 method, according to some implementations, receiving, for each trial design of a set of trial designs, a simulated performance and presenting, for at least two criteria, a plot of the simulated performance. The method may further include presenting, for at least one additional criteria, a plurality of contour lines on the plot and selecting a subset of the set of trial designs based on the plurality of contour lines.

Abstract: A method and system including identifying, via at least one processor, a user role; configuring, via the at least one processor, an interface for the user role, wherein configuring the interface includes determining an interface view for the user role; and displaying, via the at least one processor, the interface with the interface view.

Abstract: A method for trial design analysis that includes receiving, for each trial design of a plurality of trial designs, a set of simulated performance criteria for a set of trial designs, and visualizing, on a graph, values for a first simulated performance criteria and a second simulated performance criteria from the set of simulated performance criteria for each trial design using a location of points on the graph corresponding to the set of trial designs. The method further includes identifying optimal designs based on an optimality criteria using the set of the simulated performance criteria, and determining a tradeoff metric for the first simulated performance criteria and the second simulated performance criteria. The method further includes displaying, the tradeoff metric as a set of lines on the graph, wherein a slope of the lines corresponds to a value of the tradeoff metric.

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 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, 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 available resources value. The method may further include determining, via the at least one processor, which subgrouping of the plurality of possible sites has a predicted available resources value that globally optimizes a desired site resource criteria.

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 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.

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.

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.