Abstract: Provided are antibodies that specifically bind to human urokinase-type plasminogen activator receptor (uPAR). In some instances, the antibodies are cross-reactive one or more non-human animal uPAR polypeptides, such as a non-human primate uPAR, e.g., a cynomolgus uPAR. Fusion proteins and conjugates comprising the antibodies of the present disclosure are also provided. Methods of using the antibodies, fusion proteins and conjugates of the present disclosure to treat a condition associated with uPAR expression and/or activity are also provided. In some embodiments, the condition associated with uPAR expression and/or activity is cancer. Non-limiting examples of such cancers include those characterized by cancer cells that express uPAR on the surface thereof, cancers characterized by stromal cells in the tumor microenvironment that express uPAR on the surface thereof, and/or the like.

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: 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: 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: 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 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.