High efficiency architectures for selective transport across fluid networks in organ systems, and systems and methods for generating thereof

Abstract

Systems and methods for designing and generating architectures for the selective transport across fluid networks in 3D printed organ systems are provided. An example method includes: identifying, two or more fluid networks of a reference organ system and a transport characteristic between the two or more fluid networks; generating a model of each fluid network that includes channel parameters for channels associated with the fluid network; determining, based on the transport characteristic, a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks; integrating the models of each fluid network to generate an organ system model that includes at least a representation of the functional region based on the wall thicknesses between respective channels between the two or more fluid networks; and generating a 3D printed organ system based on the organ system model.

Description

HIGH EFFICIENCY ARCHITECTURES FOR SELECTIVE TRANSPORT ACROSSFLUID NETWORKS IN ORGAN SYSTEMS, AND SYSTEMS AND METHODS FOR GENERATING THEREOFCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority pursuant to 35 U.S.C. § 119 to U.S. Provisional Patent Application No. 63 / 648,322, filed May 16, 2024, which is hereby incorporated by reference in its entirety.FIELD OF THE DISCLOSURE

[0002] The present disclosure is directed to engineering designs and architectures that can be used to form structures (e.g., 3D printed organ systems) for biological applications. More specifically, the present disclosure describes high efficiency devices and architectures for selective transport across fluid networks in organ systems, and systems and methods for generating the same.BACKGROUND

[0003] Organs transport vital fluids (e.g., blood, air, lymph, etc.) via complex three-dimensional (3D) transport systems employing biophysically and biochemically entangled fluid networks. Bioengineered tissues and organs have been manufactured using hydrogels that are 3D-printed to have fluid networks (e.g., vascular, ductal, airway, neural, etc.) and functional topologies that mimic the fluid networks of natural organs. As organs typically facilitate the transfer of heat and / or mass (e.g., solutes, nutrients, oxygen, proteins, etc.) across two or more fluid networks at high rates, there is thus a desire and need for bioengineered tissues and organs to do the same.

[0004] The problem of obtaining a high rate of heat or mass transport between two or more fluid networks, using minimal volume and energy, is common in chemical engineering and medical devices, and is especially important in the development of artificial organs. Transfer from one fluid network to another is maximized when the surface area between the two fluid networks is maximized. If the two fluid networks are separated by a wall, then there is generally a direct relationship between the transport across the fluid networks and the surface area between the twofluid networks and the wall, and an inverse relationship between the transport and the thickness of the wall.

[0005] Conventionally, medical devices such as artificial organ systems attempt to facilitate the continuous transfer of heat and / or mass between two fluid networks, or between a matrix and a fluid network, by merely causing fluids to flow through the medical device relying on the aforementioned relationships to facilitate the transfer. However, desirable characteristics for artificial organ systems include high transport per unit volume and low fluidic resistance (to minimize the pumping energy needed). In biological applications, other constraints, such as conditions in the boundary of a device or organ system (e.g., pressure at the inlets and outlets), shear stress on the walls of the device, as well as the material properties of the wall hamper the ability to achieve these desirable characteristics. There are also constraints unique to each biological application or organ system. For example, in blood-carrying devices, some flow patterns are more likely to cause clotting than others. For instance, areas of flow stagnation are more likely to result in clotting.

[0006] Fabricating a geometry that can perform well under these criteria and constraints, out of a material that is compatible with the fluids, is very difficult without additive manufacturing. Furthermore, even with the advent of additive manufacturing, there is a desire and need for 3D printed geometries for organ systems, and fabrication systems and methods thereof, that facilitate the transfer of mass and / or heat not only at high efficiencies, but also selectively based on the specific characteristics of the organ systems being modeled after.

[0007] Accordingly, there exists a desire and need for high efficiency architectures for selective transport across fluid networks in 3D printed organ systems, and systems and methods for fabricating such architectures.SUMMARY

[0008] In various embodiments, architectures and devices are disclosed for providing high- efficiency selective transport across fluid networks. An example device includes a plurality of fluid networks comprising at least a first and a second fluid network. Each fluid network can have a plurality of channels. The device may further include a matrix between the plurality of fluidnetworks. In some aspects, the matrix may form a wall between the plurality of fluid networks in a functional region of the device. The matrix may comprise of or be formed from a material configured to facilitate selective transport of a filtrate from the first fluid network to the second fluid network. The device may further include the functional region comprising at least portions of each of the plurality of fluid networks and the matrix. A cross-section of the functional region comprises an array of unit cells. Each unit cell may have or share a unit cell architecture facilitating the selective transport of the filtrate. The unit cell architecture can specify a cross-sectional shape, a channel size, and a relative location for each of a channel of the first fluid network and a channel of the second fluid network. The selective transport may provide a transport characteristic for the functional region that matches or satisfies a similarity threshold with a transport characteristic of a reference organ system.

[0009] In some embodiments, the reference organ system includes a plurality of reference fluid networks comprising at least a first reference and a second reference fluid networks corresponding to the first and second fluid networks, respectively. The first fluid network may be configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by the first reference fluid network. The second fluid network may be configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by the second reference fluid network.

[0010] In some embodiments, the first fluid network may be configured to exhibit the flow characteristic based on the channel size of the channel of the first fluid network, and a length of the channel of the first fluid network in the functional region. The second fluid network may be configured to exhibit the flow characteristic based on the channel size of the channel of the second fluid network, and a length of the channel of the second fluid network in the functional region. Furthermore, in some embodiments, the flow characteristics respectively exhibited by the first fluid network, the second fluid network, the first reference fluid network, or the second reference fluid network is at least one of a fluid conductance or a viscosity exhibited by the respective fluid networks.[OU] In some embodiments, the transport characteristic is one of: a filtrate production per unit volume of a fluid network of the plurality of fluid networks; a transport of mass per unit volume of the fluid network; or a transport of heat per unit volume of the fluid network.

[0012] In various embodiments, a device is disclosed for facilitating selective transport across fluid networks. The device may include two or more fluid networks comprising at least a first fluid network and a second fluid network. Each fluid network may include an afferent distribution network, an efferent collection network, and a functional region between the afferent distribution network and the efferent collection network. The functional region may be configured to cause a selective transport of a filtrate or a mass from the first fluid network to the second fluid network according to a transport characteristic of a reference organ system. A cross-section of the functional region comprises an array of unit cells sharing a unit cell architecture. The unit cell architecture specifies a cross-sectional shape, a channel size, and a relative location for each of: a channel of the first fluid network and a channel of the second fluid network.

[0013] In some embodiments, the device further includes a matrix forming a wall between the first fluid network and the second fluid network in the functional region. A thickness of the wall and a property of the matrix are configured to cause the selective transport of the filtrate or the mass from the first fluid network to the second fluid network. For example, the property of the matrix may comprise one or more of: a permeability of the matrix; a porosity of the matrix; or a charge conductivity of the matrix.

[0014] In various embodiments, a method is provided for designing an architecture for selective transport across fluid networks for a 3D printed organ system. Two or more fluid networks associated with a reference organ system may be identified. Furthermore, a transport characteristic between the two or more fluid networks within a functional region of the reference organ system can be identified. For each of the two or more fluid networks, a model of the fluid network may be generated (e.g., by a computing device having a processor). The model may include channel parameters for a plurality of channels associated with the fluid network. The computing device may determine, based on the transport characteristic, a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks. Furthermore, the models of each of the two or more fluid networks may be integrated to generatean organ system model. The organ system model may include at least a representation of the functional region based on the wall thicknesses between respective channels between the two or more fluid networks. In some aspects, the method may further include generating the 3D printed organ system based on the organ system model.

[0015] In various embodiments, a system is provided including a computer readable storage medium having program instructions embodied therewith. The program instructions executable by a processor can cause the processor to perform a method, such as one or more methods described herein. For example, the program instructions, when executed, can cause the processor to perform one or more methods described herein.

[0016] In various embodiments, a computer program product is provided for designing an architecture for selective transport across fluid networks for a 3D printed organ system. The computer program product includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a processor to cause the processor to perform one or methods described herein.

[0017] In various embodiments, a method is provided for generating a 3D printed organ system for selective transport across fluid networks. An organ system model representing at least a functional region of a reference organ system can be generated (e.g., using a computing device having a processor). The functional region can be characterized as having two or more fluid networks and a transport characteristic between the two or more fluid networks. Each fluid network can have a plurality of channels. A tile of the functional region can be generated on a build plane using the organ system model, based on a cross-sectional architecture of the functional region, a tile of the functional region. The tile can be extruded along a z-axis to form the functional region for the 3D printed organ system. Furthermore, at each end of the functional region, the plurality of channels of each fluid network may be plumbed to form a branching region. Printing gel may be added exterior to the two or more fluid networks and within a bounding volume for the 3D printed organ system. In some aspects, the printing gel may form a wall between the two or more fluid networks in the functional region.

[0018] In various embodiments, a system is provided including a computer readable storage medium having program instructions embodied therewith. The program instructions executable by a processor can cause the processor to perform a method, such as one or more methods described herein. For example, the program instructions, when executed, can cause the processor to perform one or more methods described herein.

[0019] In various embodiments, a computer program product is provided for generating a 3D printed organ system for selective transport across fluid networks. The computer program product includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a processor to cause the processor to perform one or more methods described herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] FIG. 1 is a block diagram showing an example computing system for designing and generating a 3D printed organ system having an architecture for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure.

[0021] FIG. 2 is a diagram showing aspects of an example fluid network, according to non-limiting embodiments of the present disclosure.

[0022] FIG. 3 is a diagram showing aspects of two example fluid networks, according to nonlimiting embodiments of the present disclosure.

[0023] FIG. 4 is a schematic illustrating pitch and wall thickness between channels, according to non-limiting embodiments of the present disclosure.

[0024] FIG. 5 is a schematic illustrating example unit cell architectures, according to non-limiting embodiments of the present disclosure.

[0025] FIG. 6 is a graph showing examples of the relative percentages of architecture components among different unit cell architectures, according to non-limiting embodiments of the present disclosure.

[0026] FIG. 7 is a schematic illustrating an example methodology for designing a 3D printed organ system for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure.

[0027] FIG. 8 is a flow diagram showing an example process for designing an architecture for selective transport across fluid networks for a 3D printed organ system, according to non-limiting embodiments of the present disclosure.

[0028] FIG. 9 is a graph showing normalized transport among different unit cell architectures, according to non-limiting embodiments of the present disclosure.

[0029] FIG. 10 shows diagrams and heatmaps illustrating the architecture, pressure field, and velocity field among different unit cell architectures, according to non-limiting embodiments of the present disclosure.

[0030] FIG. 11A shows heatmaps showing the pressure field, and velocity field within an extrusion of the unit cell architecture of square packed channels, according to non-limiting embodiments of the present disclosure.

[0031] FIG. 1 IB shows heatmaps showing the pressure field, and velocity field within an extrusion of the unit cell architecture of square packed channels, according to non-limiting embodiments of the present disclosure.

[0032] FIG. 12A shows a graph illustrating relationships between a transport characteristic (e.g., filtrate production), a matrix parameter (e.g., matrix permeability), and a channel parameter (e.g., channel size), according to non-limiting embodiments of the present disclosure.

[0033] FIG. 12B shows a graph illustrating relationships between a transport characteristic (e.g., filtrate production), a matrix parameter (e.g., matrix permeability), and a channel parameter (e.g., channel size), according to non-limiting embodiments of the present disclosure.

[0034] FIG. 13 is a flow diagram showing an example process for generating a 3D printed organ system for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure.

[0035] FIG. 14 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on alternating square packed circular channels, according to nonlimiting embodiments of the present disclosure.

[0036] FIG. 15 is an illustration of an example bounding volume used in generating a 3D printed organ system, according to non-limiting embodiments of the present disclosure.

[0037] FIG. 16 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on a set of square packed circular cannels belonging to two different fluid networks in a ratio of 3: 1 (“3: 1 ratio square packed circular channels”), according to non-limiting embodiments of the present disclosure.

[0038] FIG. 17 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on hexagonally packed hexagonal annuli, according to nonlimiting embodiments of the present disclosure.

[0039] FIG. 18 is a schematic illustrating example processes for plumbing and extrusion for generating a 3D printed organ system, according to non-limiting embodiments of the present disclosure.

[0040] FIG. 19 is a schematic illustrating an example blind network for a 3D printed organ system, according to non-limiting embodiments of the present disclosure.

[0041] It is to be understood that the figures are not necessarily drawn to scale, nor are the objects in the figures necessarily drawn to scale in relationship to one another. The figures are depictions that are intended to bring clarity and understanding to various embodiments of apparatuses, systems, and methods disclosed herein. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. Moreover, it should be appreciated that the drawings are not intended to limit the scope of the present teachings in any way.DETAILED DESCRIPTIONI. Overview

[0042] As explained above, bioengineered tissues and organs manufactured today aim to mimic the functional topologies of fluid networks of natural organs. As organs typically facilitate the transfer of heat and / or mass (e.g., solutes, nutrients, oxygen, proteins, etc.) across two or more fluid networks at high rates, there is a desire and need for bioengineered tissues and organs to do the same. It is very challenging to achieve a high rate of heat or mass transport between two or more compartments, using minimal volume and energy, especially in artificial organs. For example, transfer between two fluids traversing across two respective fluid networks, or between a matrix and a fluid network respectively, may be required to be performed in a continuous fashion. Furthermore, artificially created organs or medical devices are desired to have high transport per unit volume and low fluidic resistance (to minimize the pumping energy needed). Fabricating a geometry that can perform well under these criteria and constraints, out of a material that is compatible with the fluids, is very difficult without additive manufacturing. Even with the advent of additive manufacturing, there is a desire and need for 3D printed geometries for organ systems, and fabrication techniques, thereof that facilitate the transfer of mass and / or heat not only at high efficiencies, but also selectively based on the specific characteristics of the organ systems being modeled after.

[0043] Various embodiments of the present disclosure address one or more of the aforementioned desires and needs. In particular, the present disclosure describes architectures for facilitating selective transport across fluid networks for a 3D printed organ system, and systems and methods for designing and generating the same. In various embodiments, the architecture for the 3D printed organ system involves a unit cell. The unit cell corresponds to, and is modeled after, a 2- dimensional cross-section of a functional region of an organ system. The functional region may include two or more fluid networks (e.g., vasculature, ducts, airway, compartments, etc.) that carry different fluids (e.g., blood, air, bile, cellularized gel, etc.). Furthermore, the functional region may typically facilitate the selective transport or exchange of mass (e.g., filtrate, nutrients, solute, molecules, etc.) and / or heat between the compartments. The functional region may further include a medium between the fluid networks (referred to herein as “matrix”) facilitating the selectivetransport based on adjustable and / or preset characteristics of the matrix (referred to herein as “matrix parameters”). Each fluid network (e.g., vasculature, ducts, airway, compartments, etc.) may include a plurality of channels. Furthermore, a fluid network may include both an input port and an output port (for entry and exit of fluid, respectively) exposing the fluid network to boundaries of the organ system. Alternatively, the fluid network may include a single port exposing the fluid network to the boundary (such a fluid network may be referred to herein as a “blind” network). Alternatively, in some embodiments, the fluid network may be a closed network (e g., a compartment) without any exposure to boundaries of the organ system.[0441 Various embodiments of the present disclosure describe designing arrayed unit cells of a functional region of the 3D printed organ system, modeled after the functional region of an organ system (referred to herein as “reference organ system”). The unit cell may comprise an arrangement of a plurality of channels for each of one or more fluid networks and an arrangement of a matrix or matrices between channels of the various fluid networks. The present disclosure finds that transport characteristics that define or characterize the selective transport of mass and / or heat in a functional region of the reference organ system along with fluid characteristics that define the flow of fluid across the fluid networks in the reference organ system are useful metrics for designing high efficiency architectures for 3D printed organ systems. The present disclosure finds that various parameters for modeling an organ system, such as channel parameters (e g., channel sizes, channel lengths, the distances between a channel of one fluid network with a channel of another fluid network), the unit cell design, the branching design, along with the material properties of the medium between the channels (e.g., matrix parameters), may affect the fluid characteristics of the fluid networks and the transport characteristics defining the selective transport. Thus, if transport characteristics and fluid characteristics of a reference organ system are known, various aforementioned parameters (e.g., channel parameters, matrix parameters, unit cell design, branching design, etc.) can be designed, determined, and / or optimized to create a model of an organ system that achieves the same or substantially the same transport characteristics and fluid characteristics as the reference organ system.

[0045] Various embodiments describe systems and methods for designing, determining, and / or optimizing such model parameters to generate architectures for 3D printed organ systems thatachieve known transport characteristics and known fluid characteristics of the respective reference organ systems, in order to facilitate selective transport of mass and / or heat across fluid networks with high efficiency. In at least some embodiments, unit cells have small dimensions for the channel and wall thickness, resulting in very efficient transport between the fluid networks and / or matrices. In some aspects, the unit cells are small and numerous enough to incorporate numerous branching networks into architecture designs for the 3D printed organ systems. Various embodiments of the present disclosure describe extruding two dimensional unit cell arrays formed from unit cells to form a 3D functional region for the 3D printed organ system. In some aspects, the channels of each fluid network may branch from one or more input and output ports for the 3D printed organ system. Thus, the one or more input and output ports may branch into branched networks to feed a number of arrayed unit cells.

[0046] The present disclosure also describes methods of designing such architectures as well as generating 3D printed organ systems (e.g., via computer-aided design (CAD) and / or mechanically) based on such architectures, and systems for performing the methods described herein. For example, in various embodiments, the aforementioned architecture of an example organ system model may be used to generate (e.g., on a build plane of a 3D printing apparatus), a tile subunit of the functional region (e.g., using the cross-sectional architecture of the functional region as modeled using the unit cell array). The tile subunit may be extruded along a z-axis or z-direction to form the functional region for the 3D printed organ system. At each end of the functional region, the plurality of channels of each compartment (e.g., fluid network) can be plumbed to form a branching region. Furthermore, printing gel, hydrogel, or other suitable material (collectively referred to herein as “matrix”) can be added exterior to the two or more fluid networks and within a bounding volume for the 3D printed organ system. In some aspects, the matrix (e.g., printing gel) may form a wall between the two or more fluid networks (e.g., between a channel of each fluid network) within the functional region. In some embodiments, the aforementioned processes for generating the 3D printed organ system may be performed via computer-aided design (CAD), and the resulting CAD design and / or CAD-based instructions can be transmitted to a 3D printing apparatus.

[0047] It is noted that the designing and manufacturing the presently disclosed unit cells or the branching networks is very difficult, if not impossible, without additive manufacturing methods described herein, and according to the methods described herein. In some embodiments, the presently disclosed architecture can be fabricated via additive manufacturing, with or without additional post-processing steps, such that the 3D printed organ can be manufactured using material that enables the growth and function of cells seeded within it. The presently disclosed architecture and materials enabled by additive manufacturing can enable use of fluids (e.g., blood) that are incompatible with existing devices.IL Example Descriptions of Terms

[0048] As used herein the specification, “a” or “an” may mean one or more. As used herein in the claim(s), when used in conjunction with the word “comprising,” the words “a” or “an” may mean one or more than one. Some embodiments of the disclosure may consist of or consist essentially of one or more elements, method steps, and / or methods of the disclosure. It is contemplated that any method or composition described herein can be implemented with respect to any other method or composition described herein and that different embodiments may be combined.

[0049] As used herein, “substantially” means sufficient to work for the intended purpose. The term “substantially” thus allows for minor, insignificant variations from an absolute or perfect state, dimension, measurement, result, or the like such as would be expected by a person of ordinary skill in the field but that do not appreciably affect overall performance. When used with respect to numerical values or parameters or characteristics that can be expressed as numerical values, “substantially” means within ten percent.

[0050] The use of the term “or” in the claims is used to mean “and / or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and / or.” For example, “x, y, and / or z” can refer to “x” alone, “y” alone, “z” alone, “x, y, and z,” “(x and y) or z,” “x or (y and z),” or “x or y or z.” It is specifically contemplated that x, y, or z may be specifically excluded from an embodiment. As used herein “another” may mean at least a second or more.

[0051] The term “ones” means more than one.

[0052] As used herein, the term “plurality” can be 2, 3, 4, 5, 6, 7, 8, 9, 10, or more.

[0053] As used herein, the term “set of’ means one or more. For example, a set of items includes one or more items.

[0054] As used herein, the phrase “at least one of,” when used with a list of items, means different combinations of one or more of the listed items may be used and only one of the items in the list may be needed. The item may be a particular object, thing, step, operation, process, or category. In other words, “at least one of’ means any combination of items or number of items may be used from the list, but not all of the items in the list may be required. For example, without limitation, “at least one of item A, item B, or item C” means item A; item A and item B; item B; item A, item B, and item C; item B and item C; or item A and C. In some cases, “at least one of item A, item B, or item C” means, but is not limited to, two of item A, one of item B, and ten of item C; four of item B and seven of item C; or some other suitable combination.

[0055] As used herein, the term “about” refers to include the usual error range for the respective value readily known. Reference to “about” a value or parameter herein includes (and describes) embodiments that are directed to that value or parameter per se. For example, description referring to “about X” includes description of “X”. In some embodiments, “about” may refer to ±15%, ±10%, ±5%, or ±1% as understood by a person of skill in the art.

[0056] As used herein, the term “fluid network” refers to a network of vessels, ducts, compartments, and / or pathways configured to carry fluid. Although certain properties (e.g., heat, energy, etc.) or contents suspended or dissolved within a fluid (e.g., mass, oxygen, carbon dioxide, filtrate, solutes, etc.) of one fluid network may transfer or permeate to a fluid of another fluid network, fluid networks are fluidically independent of one another such the fluids of one fluid network does not flow into and / or merge with the fluid of another fluid network. In some embodiments, fluid networks may include one or more ports (e.g., input port, output port) that serve as a boundary with an exterior of an organ system. Alternatively, a fluid network may not necessarily have an input port and an output port, allowing the fluid network to function as a compartment. The term compartment can thus be used to refer to the above described species of afluid network. Alternatively, a fluid network may have a single port to serve as the boundary, such a fluid network may be referred to herein as a “blind network.”

[0057] As used herein, the term “channel” may refer to an individual segment serving as a passage for fluid in a fluid network. In some embodiments, a channel may comprise a segment situated between two branching points within the fluid network. For example, fluid within a fluid network may travel through a channel and bifurcate into two downstream channels after a branching point. Fluid flowing through any one of the downstream channels may further bifurcate after another branching point and may enter another two downstream channels. In some embodiments, a channel may be tubular. The cross-sectional shape of a channel may be circular or any polygonal shape, for example, a square or hexagonal shape. Also or alternatively, in some embodiments, a channel may be annular or ring shaped, for example, a circular ring, a hexagonal ring, or a square ring. In some embodiments, another channel (e.g., of a different fluid network) may be enclosed by the annular channel.

[0058] As used herein, the term “matrix” may refer to any medium located between fluid networks or between channels of the same or different fluid networks. The matrix may be used to facilitate the selective transport of mass and / or heat between fluid networks or between a fluid network and the matrix. In some embodiments, the selective transport may be facilitated through adjustable and / or preset parameters, characteristics, and / or properties of the matrix (collectively referred to herein as “matrix parameters”).

[0059] The terms “three-dimensional printing system,” “three-dimensional printer,” “3D printing,” “printing,” and the like generally describe various solid freeform fabrication techniques for making three-dimensional articles or objects by stereolithography (SLA), digital light processing (DLP), selective deposition, jetting, fused deposition modeling (FDM), multi -jet modeling (MJM) or multi-jet printing (MJP), and other additive manufacturing techniques now known in the art or that may be known in the future that use a build material to fabricate three- dimensional objects.

[0060] While the present teachings are described in conjunction with various embodiments, it is not intended that the present teachings be limited to such various embodiments. On the contrary,the present teachings encompass various alternatives, modifications, and equivalents, as will be appreciated by those of skill in the art.

[0061] In describing the various embodiments, the specification may have presented a method and / or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the various embodiments.III. Example Computing System for Designing And Generating A 3D Printed Organ System Having An Architecture For Selective Transport Across Fluid Networks

[0062] FIG. 1 is a block diagram showing an example computing system 100 for designing and generating a 3D printed organ system having an architecture for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure. The computing system 100, which may include or comprise one or more of the components shown in FIG. 1. In some embodiments, the computing system 100 may comprise a device or apparatus configured or equipped to design and provide instructions for generating a 3D printed organ system that facilitates selective transport across fluid networks. For example, the computing system 100 may comprise computing device 101 configured or equipped to design the 3D printed organ system and generate machine readable instructions 106 (e.g., a computer aided design (CAD)) that may cause another or the same device to generate the 3D printed organ system. Examples of such another device or components thereof are described for example, in U.S. Patent Application Publication No. 2024 / 0091412 Al; U.S. Patent Application Publication No. 2022 / 0339858 Al; U.S. Patent Application Publication No. 2022 / 0339883 Al; or U.S. Patent Application Publication No. 2022 / 0339882 Al ; each of which is hereby incorporated by reference in its entirety. Also or alternatively, the computing system 100 may further comprise a device configured to design and generate a 3D printed organ system that facilitates selective transport across fluid networks. For example, in such embodiments, the computing system 100 may include a 3D printing apparatus 124, a build plane 130, and / or other components for generating the 3D printed organ system.

[0063] In various embodiments, computing system 100 may include or comprise a computing device 101. The computing device 101 may be an example of one implementation for computing platform that configured to execute one or more steps of one or more methods or processes described herein (e.g., methods 800 and 1300 of FIGS. 8 and 13, respectively). The computing device 101 may include at least one processor 102, at least one memory device (e.g., memory 104), a modeling engine 108, a display 120, and a user interface (UI) 122.

[0064] The processor 102 may comprise any one or more types of digital circuit configured to perform operations on a data stream, including functions described in the present disclosure. In some aspects, the at least one processor 102 may include special purpose processors such as an image processor or a computer aided design (CAD) processor configured to generate organ system models described herein. Also or alternatively, the at least one processor 102 may comprise a general purpose processor. The memory 104 may comprise any type of long term, short term, volatile, nonvolatile, or other memory and is not to be limited to any particular type of memory or number of memories, or type of media upon which memory is stored. The memory 104 may store machine readable instructions 106 that, when executed by the processor 102, can cause the computing device 101 and / or the computing system 100 to perform one or more methods discussed herein. In some embodiments, the machine readable instructions 106 may include instructions for generating a 3D printed organ system that facilitates selective transport across fluid networks, and such instructions may be relied on (e.g., by a 3D printing apparatus 124) to recreate the 3D printed organ system on a build plane 130. Also or alternatively, such instructions may be stored in a computer readable medium (e.g., data store, data storage, storage device, data storage device, etc.), which may comprise any media that participates in providing instructions to processor 102 for execution. Such a medium can take many forms, (e.g., non-volatile media, volatile media, and transmission media, etc.).

[0065] The modeling engine 108 may comprise a software, program, module, and / or plug-in that, when executed by a processor, such as but not limited to the processor 102, causes the processor 102 to facilitate the designing of at least one organ system model 110. The organ system model 110 may be a design or a simulation of an actual organ system (e.g., heart, liver, lung, kidney, pancreas, vasculature, etc.) (the organ system or tissue referred to herein as “reference organsystem” for simplicity) to allow the generation of a 3D printed organ system modeled on the reference organ system. The organ system model 110 may include a representation of a functional region of the actual organ or tissue, which includes two or more fluid networks where a selective transport of mass and / or heat may occur between the two or more fluid networks. Furthermore, the organ system model 110 may be designed such that, unlike architectures for conventional 3D printed organ systems, the organ system model 110 more effectively facilitates the selective transport of mass and / or heat across fluid networks of the 3D printed organ systems, thereby more accurately modeling the selective transport found in the actual organ system. In some aspects, the designing may include receiving a selection of the organ or tissue on which the organ system model 110 is modeled upon, and any additional parameters to further customize the organ system model 110. The selections and user inputs for customizing the organ system model 110 may be received via the user interface (UI) 122.

[0066] Furthermore, the designing may include optimizing the organ system model 110 and / or optimizing one or more fluid network models 112 of the organ system model 110, representing one or more respective fluid networks of the reference organ system. For example, the modeling engine 108 may identify (e.g., based on user input or stored records of organ system data) the fluid networks involved in the reference organ system on which the organ system model 110 is being modeled after. The modeling engine 108 may further identify a transport characteristic 116 between two or more fluid networks within a functional region of the reference organ system. The transport characteristics 116 may comprise performance metrics for assessing the selective transport of mass and / or heat across fluid networks and / or between a fluid network and a matrix. In some embodiments, the performance metrics for the transport characteristics 116 may include, for example, known filtrate production per unit volume or a known diffusion of a solute or mass occurring for a selective transport across the two or more fluid networks in the reference organ system. In some embodiments, performance metrics for the transport characteristics 116 may be based on units of heat, mass, or moles transported between fluid networks per unit time per unit volume. In some embodiments, metrics for the transport characteristic may further be measured pressure drop or per unit pressure drop. For each of the identified fluid networks, the modeling engine 110 may be used to determine flow characteristics 115 of fluid transported through the fluid network (e.g., a conductance per unit, a viscosity of fluid, etc.) and boundary conditions 118 forthe fluid network (e.g., pressure, oxygen tension, analyte concentration, etc.). In various embodiments, the modeling engine 108 may be configured to compare the determined flow characteristics 115 a fluid network model 112, to known flow characteristics of a respective fluid network of the reference organ system. Based on the comparison, the modeling engine 108 may adjust various parameters of the fluid network model 112 (e.g., channel parameters 114) to select the fluid network model 112 so that it achieves flow characteristics 115 that match or are substantially similar to the known flow characteristics of the reference organ system.

[0067] Various aforementioned data concerning the reference organ system (e.g., number of fluid networks in the organ, transport characteristics, flow characteristics, and / or boundary conditions may be accessible to the modeling engine 110, and may be retrieved (e.g., from a reference organ systems database 111) and / or may be inputted via the user interface 122. The reference organ systems database 111 may comprise a database or repository of the aforementioned data for various reference organ system or tissues. In some aspects, the reference organ systems database 111 may further store templates for the construction of the organ system model 110. From one or more of the aforementioned data, the modeling engine may optimize fluid network models 112 for each of the fluid networks. The fluid network models 112 may include determinations or optimizations of channel parameters 114 for each channel of the fluid network represented by the fluid network model 112. The channel parameters 114 may include but are not limited to, for example, a channel size and a channel extrusion length for each channel of the fluid network. The modeling engine 108 may be used to integrate the various fluid network models 112 representing the respective fluid networks of the reference organ system into the organ system model 110.

[0068] The display 120 may comprise any medium for visually displaying information to a computer user. For example, the display 120 may comprise a cathode ray tube (CRT) or liquid crystal display (LCD). The user interface 122 may comprise functionalities (e.g., touchscreen, alphanumeric and other keys, cursor controls, input devices, microphone, etc.) for communicating information and command selections to the processor 102, such as for designing, modifying, further specifying, and / or customizing an organ system model 110 or adding information concerning a reference organ system model (e.g., to the reference organ systems database 111).

[0069] The computing system 100 may include further include a 3D printing apparatus 124. In some embodiments, the 3D printing apparatus 124 may be a part of or otherwise associated with the computing device 101. Alternatively, in some embodiments, the 3D printing apparatus 124 may be separate from the computing device 101. The 3D printing apparatus 124 may be configured to generate (e.g., 3D print) an organ system based on the organ system model designed by computing device 101. Non-limiting examples of the 3D printing apparatus 124 are further described, for example, in U.S. Patent Application Publication No. 2024 / 0091412 Al; U.S. Patent Application Publication No. 2022 / 0339858 Al ; U.S. Patent Application Publication No. 2022 / 0339883 Al; or U.S. Patent Application Publication No. 2022 / 0339882 Al; each of which is hereby incorporated by reference in its entirety.

[0070] In some aspects, the 3D printing apparatus 124 may generate the 3D printed organ system by fabricating a hydrogel construct. In at least one embodiment (e.g., as shown in FIG. 1), the 3D printing apparatus 124 may include, for example, a frame 124a, a stage 124b, an electronics board 124c, a container 124d, a projector 124e, and a build plane 130. Stage 124b can be attached to frame 124a and can include a motor attached to frame 124a. The motor can be a z-axis drive motor. Electronics board 124c can be configured for controlling movement of the stage 134b with respect to the frame 124a. Projector 124e can be configured for projecting images. The images can be image slices of a 3D model (e.g., the organ system model 110) of the hydrogel matrix construct for the 3D printed organ system. In some embodiments, the 3D printing apparatus 124 may additionally include a mirror configured for reflecting the images projected from projector 1124e into the container 124d. The container 124d can be configured to receive a solution 126. In some embodiments, the solution 126 can be a pre-polymerization solution comprising a photosensitive polymer and a photoabsorber additive material suitable to control light penetration. The additive material can be removable from a solid formed of the pre-polymerization solution. The photoabsorber additive material can be biocompatible. The photoabsorber additive material can be hydrophilic. The photoabsorber additive material can be hydrophobic. In accordance with various embodiments, the hydrophobic photoabsorber additive material can include a solvent. In accordance with various embodiments, the solution can include a thickener to prevent cell settling. Further examples of the solution 126 are described in U.S. Patent Application Publication No. 2024 / 0091412 Al, which is hereby incorporated by reference in its entirety.

[0071] The build plane 130 can be configured for holding a substrate 131, wherein the hydrogel matrix construct used to build the 3D printed organ system can be formed on the substrate 131. The substrate 131 can be integrated into the 3D printing apparatus 124 and / or the computing device 101 or can be a component wholly separate from the 3D printing apparatus 124 and / or the computing device 101 and, thus, can be considered to be not part of the 3D printing apparatus 124, the computing device 101 and / or the computing system 100. In accordance with various embodiments, the computing device 101 (e.g., the modeling engine 108) can be configured to create an organ system model 1 10 for the 3D printing apparatus 124 to replicate on the build plane 130 (e.g., using a hydrogel matrix construct).

[0072] In accordance with various embodiments, the 3D printing apparatus 124 may generate, using the aforementioned organ system model, a tile subunit 136 of the functional region of the reference organ system on which the organ system model is based on. The tile subunit 136 may comprise an array of unit cells representing a 2-dimensional cross section of the functional region. As previously discussed, the functional region typically facilitates the selective transport or exchange of mass (e.g., filtrate, nutrients, solute, molecules, etc.) and / or heat between two or more fluid networks and / or between a fluid network and a matrix. Thus, each unit cell of the unit cell array may involve an arrangement of channels of each of the two or more fluid networks, each fluid network carrying different fluids (e.g., blood, air, bile, etc ). Furthermore, the 3D printing apparatus 124 may be configured to extrude the tile subunit along a z-axis to form a functional region 134 for the 3D printed organ system. The functional region 134 may be modeled after the functional region of the reference organ system. The 3D printing apparatus 124 may be further configured to plumb the channels of the fluid networks at the ends of the functional region 134 to form branching regions 138 (e.g., at either end of the functional region 134). As will be described herein, the branching region may comprise a region where each of one or more fluid network branches (e.g., serially) from a single channel to multiple channels.

[0073] In some aspects, the 3D printing apparatus 124 may be further configured to form one or more input and output ports extending from one or both of the bounding regions. In some embodiments, a bounding volume 132 may be designated around the two or more fluid networks of the 3D printed organ system (e.g., around the functional regions, the branching regions, and / orthe input and output ports). Furthermore, in some embodiments, the 3D printing apparatus 124 may be configured to add printing gel exterior to the two or more fluid networks and within the bounding volume 132 for the 3D printed organ system.

[0074] In some embodiments, the 3D printing apparatus 124 can further comprise cells. For example, the 3D printing apparatus 124 can further comprise one or more of liver, lung, bone, endothelial, cardiac, pancreas, kidney, epithelial, muscle, cartilage, stem cells, skin, or eye cells.

[0075] The aforementioned components of computing system 100, in accordance with various embodiments, can all be provided as part of single apparatus, device, or system. These various components, however, can also be provided in various other configurations whereby any one or more components can be provided as part of further sub-apparatus that interact with the main, system, device, or apparatus to together provide fundamentally the same functionality as those embodiments where all components are provided within the single system, device, or apparatus. Further, various embodiments can include only a portion of the components provided above as it should not be assumed that each and every component recited is necessary for the proper functionality of system 100.IV. Example Architectures For Selective Transport Across Fluid Networks For A 3D Printed Organ System

[0076] FIG. 2 is a diagram showing aspects of an example fluid network 200, according to nonlimiting embodiments of the present disclosure. As shown in FIG. 2, the fluid network 200 has an input end 202a (also referred to herein as input port) for afferent flow of a fluid and an output end 202b (also referred to herein as output port) for an efferent flow of the fluid. Nevertheless, it is contemplated that some fluid networks may not have an efferent flow (e.g., blind networks) as will be described further herein, in relation to FIG. 18. Since the input and output ends of the fluid network 200 are exposed to the exterior of the organ system, the conditions of the boundary of the organ system (boundary conditions 204a and 204b) may affect the flow characteristics of the fluid flowing through the fluid network 200, thus dictating the architecture of the organ system being modeled using methods described herein. As shown in FIG. 2, boundary conditions 204a-204b affecting both the afferent flow boundary and the efferent flow boundary may include, but are notlimited to a pressure on the boundary, an oxygen tensions at the boundary, and analyte concentration. In some embodiments, the boundary conditions at the afferent flow end may be different from the boundary conditions at the efferent flow end.

[0077] As shown in FIG. 2, the fluid network 200 branches into multiple channels from the input end 202a, while the branched channels of the fluid network 200 coalesce into a single channel at the output end 202b. The regions of the fluid network 200 that feature such branching into a plurality of channels, as well as the coalescing of the branches may be referred to as the branching regions 206a and 206b. Furthermore, as shown in FIG. 2, a portion of one branching region 206a, where afferent flow of the fluid from the input end branches into multiple channels, may be referred to as an afferent distribution network 208a, whereas a portion of the other branching region 206b, where efferent flow of the fluid from multiple channels coalesce into a less number of channels or a single channel, may be referred to as an efferent collection network 208b.

[0078] As fluid flows in the fluid network 200 past the afferent distribution network 208a, the fluid in the fluid network may enter the functional region 210 of the organ system. The fluid network 200 within the functional region 210 may be characterized by an array 212 of unit cells 214, as shown in FIG. 2. Each unit cell 214 of the unit cell array 212 may comprise an arrangement of channels of the fluid network 200 relative to channels of other fluid network(s) for the organ system to facilitate the selective transport or exchange of mass (e.g., fdtrate, nutrients, solute, molecules, etc.) and / or heat between the fluid network 200 shown in FIG. 2 and the other fluid networks of the organ system. Various non-limiting examples of arrangements for unit cell array are further described herein. Furthermore the unit cell 214 and / or unit cell array 212 may be characterized by other design parameters, such as channel parameters (e.g., size and length of each channels), wall thickness (e.g., distances between channels), and pitch, as will be described herein. After undergoing selective transport of mass (e.g., filtrate, solute, nutrients, molecules, etc.) or heat within the functional region 210, the fluid within the fluid network 200 may flow into the efferent collection network 208b and then into the output end 202b.

[0079] FIG. 3 is a diagram showing aspects of two example fluid networks, 300a and 300b, according to non-limiting embodiments of the present disclosure. Like the fluid network 200 shown in FIG. 2, fluid networks 300a and 300b also each share branching regions 302a and 302band a functional region 306. Each fluid network may be configured to carry different fluids as appropriate for the organ system being modeled. For example, fluid network 300b may be configured to carry blood whereas fluid network 300a may be configured to carry urine to model a kidney. For at least one of the fluid networks (e.g., fluid network 300a), a portion of one branching region 302a may be characterized as an afferent distribution network 304a due to an afferent flow of fluid being distributed through a plurality of channels, and a portion of another branching region 302b may be characterized as an efferent collection network 304b due to an efferent flow of fluid being collected from a plurality of channels into a reduced number of channels or a single channel. In some embodiments, a fluid network (e.g., fluid network 300a) may have an afferent distribution network in a first branching region (e.g., branching region 302a) and the efferent collection network in a second branching region (e.g., branching region 302b), whereas another fluid network (e.g., fluid network 300b) may have an afferent distribution network in the second branching region (e.g., branching region 302b) and the efferent collection network in the first branching region (e.g., branching region 302a). Also or alternatively, two or more fluid networks may have afferent distribution networks and efferent collection networks in the same branching regions.

[0080] In some embodiments, the radius of each generation of branching in the branching regions can be set using Murray’s Law (e g., the cube of the radius of a branch is equal to the sum of cubes of the radii of the next downstream branch, or n3= n3+ n3) to minimize the resistance of flow in the fluid networks in networks, relative to their total volume. Also or alternatively, the dimensions and arrangement of the branching network channels can be chosen so as to minimize the volume of the device taken up by the branching networks.

[0081] A cross section of the functional region 306 of the organ system being modeled may be characterized as an extrusion of a unit cell array 308. As previously discussed, the unit cell array (e g., unit cell array 308) may comprise a plurality of unit cells (e.g., unit cell 310), which may each be an arrangement of channels of the two or more fluid networks 300a and 300b that facilitate the selective transport appropriate for the organ system. As shown in FIG. 3, the unit cell 310 can be as simple as two parallel tubes. Some example arrangements for unit cells may include square packing and hex packing. Various non-limiting examples of arrangements for unit cell array arefurther described herein (e.g., in relation to FIG. 5). In some embodiments, the functional region 306 need not have a uniform cross-section. For example, a unit cell array at one cross section of the functional region may be different from a unit cell array at another cross-section of the functional region. Also or alternatively, in some embodiments, unit cells may not necessarily be the same, and there may be unit cells based on groups of unit cells, each group having like features. As shown in FIG. 3, the functional region 306 may be formed of an extruded 2D pattern of a unit cell array 308. The unit cells of a unit cell array can be fabricated with very high fidelity with stereolithographic processes because they are insensitive to cure-through of the resin. As will be discussed below in relation to FIG. 4, the unit cell may be further characterized by distances between a channels of fluid network.

[0082] FIG. 4 is a schematic illustrating pitch 40 and wall thickness 42 between channels, according to non-limiting embodiments of the present disclosure. The two-dimensional unit cell, which may constitute a unit of a unit cell array, which may be extruded to form a functional region for a 3D printed organ system may be defined by the pitch 40 and wall thickness 42 between repeated features of the unit cells. In the example shown in FIG. 4, the repeated features are channels (represented in FIG. 4 as two-dimensional circles, two of which are depicted with hatching, and two of which are depicted without hatching). As shown in FIG. 4, the pitch 40 describes the center-to-center distance between channels (or between another repeated feature of the unit cell). The wall thickness 42 describes the length of porous scaffold between the channels (or between another two repeated features of the unit cell). In some embodiments, the unit cell may be characterized by the pitch and wall thickness between channels of different fluid networks. Also or alternatively, in some embodiments, the unit cell may be characterized by the pitch and wall thickness between channels of the same fluid network. In some embodiments, the unit cells may be characterized further, for example, by the size or shape of the channels. Furthermore, the unit cells may be characterized by the arrangement of the channels of one fluid network to channels of another fluid network, as will be described for example in FIG. 5.

[0083] FIG. 5 is a schematic illustrating example unit cell architectures, according to non-limiting embodiments of the present disclosure. The unit cell architectures may characterize a unit cell, for example, in how fluid networks are arranged in relation to one another. As a unit cell is a two-dimensional constituent of a two dimensional unit cell array, the unit cell may also characterize a unit cell array, which may represent a cross-section of a functional region of an organ system. As shown in FIG. 5, unit cell architectures may include but are not limited to a hex packed channels 502 and square packed channels 504. In hex packed channels 502, channels of fluid networks may be arranged in a hexagonal grid with predetermined wall thickness and pitch to one another. In square packed channels, the channels of fluid networks may be arranged in a Cartesian grid with predetermined wall thickness and pitch to one another. Although the example unit cells shown in arrangements 502 and 504 depict one channel of a first fluid network (e.g., vasculature, denoted as 502a and 504a) with three channels of a second fluid network (e.g., cellularized gel, depicted as 502b and 504b), it is contemplated that any ratio of channels of one fluid network to channels of another fluid network(s) may be used, in accordance with the organ system being modeled.

[0084] In some embodiments, two or more fluid networks may be arranged such that a channel or compartment of one fluid network encapsulates (e.g., as a concentric ring) a channel or compartment of another fluid network. Examples of such arrangements, where compartments or channels are completed surrounded by another, include but are not limited to a hex packed annuli 506 and the square packed annuli 508 in FIG. 5. The examples show the outer compartment being part of a fluid network comprising cellularized gel (506b and 508b) and the inner compartment being part of a fluid network comprising vasculature (506a and 508a). A predetermined distance (e.g., wall thickness and pitch) may separate the respective compartments or channels of such fluid networks. In some embodiments, the space between fluid networks may be fdled with a printed gel (502c, 504c, 506c, and 508c).

[0085] Thus, the pitch, wall thickness, and arrangement of unit cell features such as individual channels or compartments of various fluid networks can be modified to different relative volume proportions of the fluid networks and the spaces between the fluid networks. In some embodiments, the spaces between the fluid networks may be filled with a printed gel (502c, 504c, 506c, and 508c) or other porous scaffold. Furthermore, as will be described in FIG. 6, the relative proportion of components of the unit cell, such as the relative proportions of each fluid network or gap between fluid networks can be modified and may be a further defining factor for the unit cell architecture.

[0086] FIG. 6 is a graph showing the relative percentages of architecture components among different unit cell architectures, according to non-limiting embodiments of the present disclosure. As shown in the graph, the architecture components may include channels or compartments associated with a fluid network (e.g., vasculature), channels or compartments associated with another fluid network (e.g., cellularized gel), and space between the fluid networks that may be filled, for example, with a printing gel. The relative proportions of these components for the example unit cell architectures described in FIG. 5 are shown in the graph of FIG. 6. It is contemplated that some proportions may be advantageous for different fluid combinations. For example, suppose the 3D printed organ system is to be used for gas exchange between fluids in fluid network A and fluid network B, and that the fluid in fluid network A has a much higher solubility for the gas than the fluid in fluid network B. In such an example, it may better to have more of the unit cell volume allocated to fluid network B to maximize the extent of the gas exchange.

[0087] After an appropriate unit cell architecture is determined, based on the nature of the selective transport that occurs in the organ system being modeled, the unit cell architecture may be used to generate a two-dimensional (2D) unit cell array using systems and methods described herein. The 2D unit cell array can then be extruded (e.g., along a z-axis) to form a 3D functional region modeled after the functional region of the organ system. As previously discussed, the functional region may comprise a region of an actual or 3D printed organ system (or model thereof) that typically facilitates the selective transport or exchange of mass (e.g., filtrate, nutrients, solute, molecules, etc.) and / or heat between channels of two or more fluid networks. The functional region is able to facilitate the selective transport as the region may comprise channels in which the wall thickness and / or pitch is at their shortest, thus providing the highest degree of transport across the space between them. In some aspects, the space between the channels may comprise a porous scaffold, further facilitating the selective transport.

[0088] After the unit cell array is extruded to form the 3D functional region, the channels of the fluid network can then be plumbed together on one end to form the afferent distribution network (e.g., as in afferent distribution networks 204a and 304a) and on the other end to form an efferent collection network (e.g., as in an efferent collection networks 204b and 304b). The afferentdistribution networks and efferent collection networks formed through the plumbing may comprise branching regions.

[0089] The present disclosure describes various devices for providing high-efficiency selective transport across fluid networks. Such devices may rely on architectures, concepts, systems, methods, and components described herein, such as but not limited to the aforementioned architectures, components, and concepts. For example, a device may include a plurality of fluid networks comprising at least a first and a second fluid network (such as but not limited to fluid networks 300a and 300b). Each fluid network can have a plurality of channels (such as but not limited to the channels described in relation to FIGS. 2-4). The device may further include a matrix that forms a wall between the plurality of fluid networks in a functional region of the device. The matrix (such as but not limited to the printed gel described in relation to FIG. 5 and 6) may comprise of material configured to facilitate selective transport of a filtrate from the first fluid network to the second fluid network. The device may further include a functional region (e.g., functional regions 210 and 306) comprising at least portions of each of the plurality of fluid networks and the matrix. A cross-section of the functional region comprises an array of unit cells (e.g., unit cell array 212 and 308). Each unit cell (e.g., unit cell 214 and 310) may have or share a unit cell architecture facilitating the selective transport of the fdtrate (such as but not limited to the unit cell architectures described in relation to FIG. 5). The unit cell architecture can specify a cross- sectional shape, a channel size, and a relative location for each of: a channel of the first fluid network and a channel of the second fluid network. The selective transport may provide or may be measured or defined by a transport characteristic for the functional region that matches or satisfies a similarity threshold with a transport characteristic of a reference organ system. The reference organ system may be, for example, an actual organ system (e.g., heart, liver, kidney, pancreas, etc.) for which the device is being modeled (e.g., for the high-efficiency selective transport of the organ system).

[0090] In some embodiments, the reference organ system includes a plurality of reference fluid networks comprising at least a first reference and a second reference fluid networks corresponding to the first and second fluid networks, respectively. The first fluid network is configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by thefirst reference fluid network. The second fluid network is configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by the second reference fluid network.

[0091] In some embodiments, the first fluid network (e.g., fluid network 300a) may be configured to exhibit the flow characteristic based on the channel size of the channel of the first fluid network, and a length of the channel of the first fluid network in the functional region. The second fluid network (e.g., fluid network 300b) may be configured to exhibit the flow characteristic based on the channel size of the channel of the second fluid network, and a length of the channel of the second fluid network in the functional region. Furthermore, in some embodiments, the flow characteristics respectively exhibited by the first fluid network, the second fluid network, the first reference fluid network, or the second reference fluid network is at least one of a fluid conductance or a viscosity exhibited by the respective fluid networks.

[0092] In some embodiments, the transport characteristic is one of: a filtrate production per unit volume of a fluid network of the plurality of fluid networks; a transport of mass per unit volume of the fluid network; or a transport of heat per unit volume of the fluid network.

[0093] In various embodiments, a device is disclosed for facilitating selective transport across fluid networks. The device includes two or more fluid networks comprising at least a first fluid network and a second fluid network. Each fluid network may include an afferent distribution network, an efferent collection network, and a functional region between the afferent distribution network and the efferent collection network. The functional region (e g., functional region 210 or 306) may be configured to cause a selective transport of a filtrate or a mass from the first fluid network to the second fluid network according to a transport characteristic of a reference organ system. A cross-section of the functional region comprises an array of unit cells (such as but not limited to the unit cell arrays 210 and 308) sharing a unit cell architecture (such as but not limited to the unit cell architectures shown in FIG. 5). The unit cell architecture may specify a cross- sectional shape, a channel size, and a relative location for each of: a channel of the first fluid network and a channel of the second fluid network.

[0094] In some embodiments, the device further includes a matrix forming a wall between the first fluid network and the second fluid network in the functional region (such as but not limited to the printing gel forming a wall between the vasculature and the cellularized gel in FIG. 5). A thickness of the wall and a property of the matrix are configured to cause the selective transport of the filtrate or the mass from the first fluid network to the second fluid network. For example, the property of the matrix may comprise one or more of: a permeability of the matrix; a porosity of the matrix; or a charge conductivity of the matrix.

[0095] In some embodiments, for each fluid network, an inlet may be fluidly connected to and configured to deliver fluid to the afferent distribution network. An outlet may be fluidly connected to and configured to receive fluid from the efferent collection network. The inlet and outlet may be exposed to one or more boundary conditions for the device (such as but not limited to afferent boundary conditions 204a and efferent vascular boundary conditions 204b, respectively). Furthermore, in some aspects, the unit cell architecture may be designed and / or calibrated, based on the one or more boundary conditions, to allow the functional region (e.g., functional region 210 or 306) to cause the selective transport according to the transport characteristic of the reference organ system.V. Designing An Organ System Model For Selective Transport Across Fluid Networks

[0096] FIG. 7 is a schematic illustrating an example methodology for designing a 3D printed organ system 750 for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure. As shown in FIG. 7, the basis for designing a 3D printed organ system 750 can be a known organ system used as a reference (reference organ system 710). For example, there may be a need for a bioengineered organ system (e.g., a bioengineered heart, liver, lung, kidney, pancreas, vasculature, etc.) based on the prevalence of patients suffering a disease or debilitating medical condition that impairs or destroys the organ system (e.g., a tumor affecting the heart, liver, lung, kidney, pancreas, vasculature, etc.). The reference organ system 710 may be characteristically known to have a functional region 712 comprising two or more fluid networks 714. For example, an organ system such as a kidney may be characteristically known to have fluid networks of a blood vasculature and a urinary tract. Furthermore, such fluid networks 714 of the reference organ system 710 may characteristically have known flow characteristics 716. Forexample, the fluid networks 714 may comprise of channels that may be known to exhibit such flow characteristics. In various embodiments, such flow characteristics 716 may include but are not limited to a fluidic conductance (e.g., a fluidic conductance per unit volume of the channel), a fluidic resistance (e.g., a fluidic resistance per unit volume of the channel) or a viscosity of the fluid across one or more channels of the fluid network. The reference organ system 710 may also be characteristically known to have a transport characteristic 718 within the functional region 712 of the reference organ system 710. The transport characteristic 718 may comprise a metric of selective transport that typically occurs across two or more fluid networks in the functional region 712. For example, in various embodiments, the transport characteristic 718 may include but is not limited to a filtrate production occurring across the two or more fluid networks (e.g., filtrate production per unit volume of fluid transported across a fluid network, filtrate production per unit surface area of a wall of a fluid network, etc.) or a diffusion of a mass (e.g., solute, molecule, nutrient, etc.) occurring across the fluid network (e.g., per unit volume of fluid transported through the fluid network). Furthermore, the reference organ system 710 may have known boundary conditions 720 for the boundaries of the fluid networks involved. The aforementioned information concerning the reference organ system 710 may thus be received for the design of the 3D printed organ system (e.g. by a computing system and / or device such as computing system 100 and computing device 101).

[0097] The design may further involve the optimization 730 of various parameters (e.g., channel parameters 732) of each fluid network to match, or otherwise satisfies a similarity threshold with, the known flow characteristics 716 of the fluid network 714 in the reference organ system 710. It is contemplated that at least some of these flow characteristics (e.g., fluidic resistance, fluidic conductance, viscosity etc.) are based on a relationship between pressure drop along the fluid network and the flow rate of fluid along the fluid network 714. In 2D extruded unit cells, the flow characteristics for each fluid network (e.g., the fluidic resistance, the fluidic conductance, viscosity etc.) may be a function of channel parameters 732, such as the size (e g., channel cross-sectional diameter or area), and the length of the channel (e.g., extrusion length). Thus, the known flow characteristics 716 can thus be used to generate models for each fluid network (fluid network models 734), where each fluid network model 734 indicates optimal channel parameters 732 foreach channel of the fluid network to allow the fluid network to match or otherwise attain a similarity threshold with the known flow characteristics 716.

[0098] In an example embodiment, the known flow characteristics 716 to be achieved by optimizing parameters for each fluid network (e.g., channel parameters 732) may include a known fluid conductance per unit volume for each fluid network of the reference organ system and a known viscosity for each fluid within the respective fluid network. In order to optimize parameters to generate a model for each fluid network, it is assumed that the functional region in the 3D printed organ system would comprise an extruded unit cell array, where each unit cell would indicate the size of channels for each fluid network, and the extrusion length would indicate the channel length. It is assumed that, at some pressure, the flow per unit pressure per unit volume can match, or satisfy a similarity threshold with, that of the reference organ system.

[0099] Flow characteristics, such as fluid conductance or fluid resistance, can be expressed as Hagen-Poiseuille flow equations modeling the flow of fluid through a channel. For example, the conductance of fluid through a channel (e.g., in a square packed channel unit) can be derived from the Hagen-Poiseuille flow equation in the laminal flow regime:C = 2 * (128 L), where C is the conductance, D is the channel diameter, r] is the viscosity, and L is the channel length.

[0100] The volume of the subunit (V) can be represented with respect to its characteristic feature size (D) and extrusion length (L):V = (4D)2L

[0101] Dividing the conductance (C) by the volume of the subunit (V), one may derive an equation describing the desired flow characteristic (i.e., fluid conductance per unit volume) as a function of the characteristic feature dimension, the length of the extruded subunit, and the viscosity (77) of the fluid:

[0102] By applying a target fluid conductance per unit volume value (e.g., the known fluid conductance per unit volume for the reference organ system), one may obtain a set of channel diameter and channel length values that can be used to generate the fluid network model for the organ system. This process may be replicated for other fluid networks of the reference organ system to generate other fluid network models.

[0103] As will be discussed further below, the fluid network models 734 along with the known transport characteristics 718 of the reference organ system 710 can then be used to design of the rest of the 3D printed organ system. For example, the known channel parameters 732 (e.g., channel size and channel length for each of the fluid networks) may be used to optimize other features and parameters of an organ system model in order to match, or satisfy a similarity threshold with, the known transport characteristics 718 of the reference organ system 710. Such features or parameters for the organ system model may include but are not limited to matrix parameters 742, unit cell architecture 744, and branching design 746. The matrix parameters may include, for example, a porosity, a permeability, charge conductivity, or other material property of the space between fluid networks (e.g., the porous scaffold). The branching design 746 may include, for example, the dimensions, numbers, or arrangement of branches at the branching regions for the 3D printed organ system 750.

[0104] As will be discussed in relation to FIG. 9, different unit cell architectures may thus exhibit different transport characteristics (e.g., filtrate production, mass diffusion, heat conductivity, etc.) across fluid networks, when other parameters are controlled. Furthermore, as will be discussed in relation to FIG. 10, such differences in transport characteristics may result from differences in pressure and velocity fields caused by the differences in the unit cell architectures. Furthermore, as will be discussed in relation to FIG. 11, using the channel parameters determined to achieve the known flow characteristics, the pressure and velocity fields for unit cell architectures based on the channel parameters can be used to determine the optimal unit cell architecture to match, or achieve a similarity threshold with, the known transport characteristics.

[0105] In some embodiments, boundary conditions 720 characteristic of various biological applications may further constrain the optimization of various parameters for the fluid network models (e.g., acceptable fluidic resistance) and / or the organ system model. For example, for anartificial organ receiving blood from the heart, the fluidic resistance must be such that the pressure required to achieve sufficient flow for the required rate of transport is not greater than normal blood pressure. Thus, boundary conditions 720 such as blood pressure emanating upstream from the organ system may dictate the design of the fluid network models.

[0106] FIG. 8 is a flow diagram showing an example process 800 for designing an architecture for selective transport across fluid networks for a 3D printed organ system, according to non-limiting embodiments of the present disclosure. One or more blocks, steps, or methods of process 800 may be performed by a computing system, such as computing system 100, or a component thereof (e. g, computing device 101). For ease of explanation, process 800 is described as being performed by a computing device having a processor. Such a computing device, however, does not necessarily represent a single computing device, and such a computing device may include but is not limited to computing device 101 having the processor 102.

[0107] Process 800 may begin with the computing device identifying two or more fluid networks associated with a reference organ system, at block 802. Furthermore, at block 804, the computing device may identify a transport characteristic between the two or more fluid networks within a functional region of the reference organ system. For example, a computing device (e.g., computing device 101) may be instructed (e g., viaauser input via user interface 122) to design an architecture for an organ system model based on a reference organ system. The computing device may then query and retrieve known characteristics about the reference organ system (e.g., from a reference organ system database 111), such as information about the reference organ system having two or more fluid networks in its functional region and the transport characteristics for the functional region of the reference organ system. The transport characteristics may define or characterize the selective transport in the functional region of the reference organ system.

[0108] In some embodiments, the computing device may additionally retrieve the transport characteristics and flow characteristics for the reference organ system. The flow characteristics may characterize the flow of fluid in each fluid network of the reference organ system. In some embodiments, the computing device may additionally retrieve known boundary conditions for the fluid networks of the reference organ system. The boundary conditions may include chemical or physical conditions at the boundaries of the organ system that affect the flow characteristics offluid within the fluid networks of the organ system. For example, the boundary conditions may include but are not limited to one or more of a pressure, an oxygen level, a tension, or an analyte concentration at a boundary of the fluid network.

[0109] In some embodiments, the computing device may additionally retrieve a cross-sectional architecture associated with a reference organ system. The cross-sectional architecture may specify a relative location, within a cross-section of a functional region of the reference organ system, of each of a plurality of channels of each fluid network of the two or more fluid networks to each of a plurality of channels of other fluid networks of the two or more fluid networks. As will be described further below, the representation of the functional region in an organ system model to be generated by the computing device may be based on the cross-sectional architecture.

[0110] In some aspects, the aforementioned information of the reference organ system (e.g., the fluid networks of the reference organ system, the transport characteristics of the functional region, the flow characteristics of the fluid networks, cross-sectional architecture, the boundary conditions, etc.) may be retrieved by the computing device prior to identification of the information (e.g., identified at block 802). Also or alternatively, the aforementioned information may be inputted into the computing device (e.g., via user input via user interface 122). Also or alternatively, aspects of the aforementioned information that are unknown or otherwise not retrievable may be determined or deduced based on aforementioned information that is known and / or retrieved.[0U1] At block 806, the computing device may generate, for each of the two or more fluid networks, a model of the fluid network. In some aspects, each fluid network may be fluidically independent of each other. Furthermore, may correspond to a vascular network, a duct, an airway, a cellularized gel or cell chamber, or a compartment. The model of the fluid network (e.g., fluid network model 112) may indicate channel parameters for a plurality of channels associated with the fluid network. The channel parameters may include but are not limited to, for example, a size of each channel (e.g., area, circumference, diameter, etc.), a shape of each channel, a length of each channel (e.g., extrusion length), a distance between channels (e.g., between channels of the same fluid network or of another fluid network), or an arrangement of channels (e.g., unit cell design). In some embodiments, prior to generating the model of the fluid network, the computingdevice may identify or determine one or more flow characteristics of fluid transported through the fluid network and identify one or more boundary conditions for the fluid network. The one or more flow characteristics may include but are not limited to, for example, a conductance per unit and a viscosity of fluid across the plurality of channels of the fluid network within the functional region. The model of the fluid network may be generated using the one or more flow characteristics and the one or more boundary conditions.

[0112] For example, generating the model of the fluid network may include initializing values for the channel parameters based on boundary conditions of the fluid network; and optimizing the channel parameters of the channels based on simulated flow characteristics. In some aspects, optimizing the channel parameters may be an iterative process whereby the channel parameters are iteratively adjusted until the simulated flow characteristics math or otherwise achieve a similarity threshold with known flow characteristics of the respective fluid network of the reference organ system.

[0113] At block 808, the computing device may determine a wall thickness between a channel of one fluid network (first fluid network), to a channel of another fluid network (second fluid network), for each of the two or more fluid networks. Also or alternatively, the computing device may determine a pitch between the channel of the first fluid network and the channel of the second fluid network, for each of the two or more fluid networks. As previously discussed in relation to FIG. 4, while the wall thickness may measure the distance between channels, the pitch may additionally account for the size of the channels. In some embodiments, the determination of the wall thickness and / or the pitch between the channels may be a result of an optimization process. For example, the optimization the wall thickness and / or the pitch may be an iterative process where, at each iteration, the computing device may simulate flow characteristics in the fluid networks based on a wall thickness and / or a pitch. The iterations may continue until the simulated flow characteristics match or otherwise satisfy similarity thresholds with known flow characteristics of the respective fluid networks of the reference organ system. Also or alternatively, the determination of the wall thickness and / or pitch may be a result of an optimization process involving the simulation of transport characteristics across fluid networks to achieve simulatedtransport characteristics that match or otherwise similarity thresholds with known transport characteristics of the functional region of the reference organ system.

[0114] At block 810, the computing device may integrate the models of each of the two or more fluid networks to generate an organ system model (such as but not limited to organ system model 110 integrating fluid network models 112). For example, the fluid network models 112 may each indicate channel parameters 114 of the respective channels of the fluid network that allow the fluid network to achieve the same or substantially similar flow characteristics 1 15 as the respective fluid network of the reference organ system. The organ system model, in integrating the various fluid network models of the organ system may additionally model remaining parameters of the organ system such that the functional region of the modeled organ system achieves the same or substantially similar transport characteristics as the respective functional region of the reference organ system. For example, the organ system model may additionally model the arrangement of channels and / or fluid networks with respect to one another in a unit cell of a cross-section of the functional region (e.g., unit cell architecture), the branching design of the branching of individual channels of each fluid network, as well as the properties of the medium between the fluid networks (e.g., the matrix). Thus, in some embodiments, the organ system model 110 may additionally model one or more of matrix parameters, unit cell architecture, branching designs of each fluid network, among other parameters of the organ system. The modeling of such parameters may be a result of an optimization of the aforementioned parameters so that the modeled functional region is able to achieve transport characteristics that match or satisfy a similarity threshold with the known transport characteristics of the respective functional region of the reference organ system.

[0115] At block 812, a 3D printed organ system may be generated based on the organ system model. For example, a computing device, such as computing device 101, may design the organ system model based on the above described blocks, and may generate machine readable instructions (e.g., such as machine readable instructions 106) for the bioprinting of the organ system model. In some embodiments, the machine readable instructions may include a computer- aided design (CAD) file. Also or alternatively, the machine readable instructions may include instructions for how to 3D print and / or bioprint the various components of the organ system, such as the unit cell (e.g., as a tile subunit), a unit cell array (e.g., as a tile), a functional region (e.g., asan extruded tile), branching networks, inlet and outlets, and the like. In some aspects, the machine readable instructions may include instructions for the addition and type of contents for various components of the 3D printed organ system. For example, the machine readable instructions may provide instructions for the type of printing gel (e.g., the type of hydrogel) to be used for the matrix based on the determined matrix parameters, and / or how to develop and / or add cellularized gel for one or more fluid networks. In some embodiments, the machine readable instructions 106 may be provided to a 3D printing apparatus, such as 3D printing apparatus 124 to generate the 3D printed organ system based on the machine readable instructions 106. In some embodiments, the same computing device designing the 3D printing organ system may bioprint the 3D printing organ system.

[0116] As will be discussed herein, FIGS. 13-18 describe example embodiments for generating the 3D printed organ system based on the organ system model. The organ system model may include a representation of a cross-section of the respective functional region of the reference organ system. The cross-section may be modeled as a tile. The tile may comprise subunits or unit cells. Each unit cell may show an arrangement of a plurality of channels of each of the two or more fluid networks within the functional region. In at least some embodiments, generating the 3D printed organ system involves generating, on a build plane, the tile of the functional region; extruding the tile along a z-axis to form the functional region for the 3D printed organ system; and plumbing, at each end of the functional region, the plurality of channels of each fluid network to form a branching region. In some embodiments, generating the 3D printed organ system may further involve designating a bounding volume for the 3D printed organ system. The bounding volume may indicate the boundaries of the 3D printed organ system. For example, the bounding volume may include the at least the two or more fluid networks. In some embodiments, generating the 3D printed organ system may further involve adding printing gel in at least a portion of a void volume resulting from a Boolean subtraction of the two or more fluid networks from the bounding volume.

[0117] FIG. 9 is a graph showing normalized transport among different unit cell architectures, according to non-limiting embodiments of the present disclosure. The different unit cell architectures, which reflect different shapes and arrangements of channels of fluid networks in relation to one another, include square packed channels, hexagonal packed channels, squarepacked annulus, and hexagonal packed annulus, as previously discussed in relation to FIGS. 6 and 7. In order to design a 3D printed organ system that matches, or achieves a similarity threshold with, the transport characteristics of the reference organ system, an appropriate unit cell architecture may need to be selected. In at least one embodiment, a transport characteristic may be a measure of advective transport of filtrate, mass, and / or heat across fluid networks. The filtrate production per unit volume or a diffusion of a mass (e.g., solute, nutrient, molecule, etc.) per unit volume are examples of metrics that can be used for the measurement of advective transport of a filtrate or mass cross the fluid networks. Since different unit cell architectures may have different channel shapes and surface areas per unit of channel length (for a given diameter or width of a cross-section of a channel), the surface areas for channels represented by the various unit cell architectures referenced in FIG. 9 are normalized (e.g., to account for differences in surface areas).

[0118] FIG. 9 thus shows an example transport characteristic, the filtrate production per unit of volume, based on a unit of channel length and based on a normalized surface area of the channel walls in that unit of channel length. As shown FIG. 9, packing efficiency analysis informs optimal architectures to support advective transport. By normalizing the surface area of the channels across the various unit cell architectures, the graph shows the resulting normalized filtrate production per unit surface area for each of the various unit cell architectures. Moreover, the graph shows that the square packed channels provide the greatest advective transport per unit of surface area of the channel.

[0119] Although various examples rely on filtrate production per unit of volume as a metric for the transport characteristic of the reference organ system, it is contemplated that other metrics for transport characteristic can also be used. Although filtrate production per unit of volume may be useful for measuring filtrate transported across fluid networks or across a fluid network into a matrix, mass diffusion per unit of volume may be useful for measuring mass transport across fluid networks via perfusion. Furthermore, other performance metrics for measuring the transport characteristic can be based on units of heat, mass, or moles transported between fluid networks per unit time per unit volume. In some embodiments, metrics for the transport characteristic may further be measured pressure drop or per unit pressure drop.

[0120] FIG. 10 shows diagrams and heatmaps illustrating the architecture, pressure field, and velocity field among different unit cell architectures, according to non-limiting embodiments of the present disclosure. As previously discussed, differences in transport characteristics may result from differences in pressure and velocity fields caused by the differences in the unit cell architectures. For example, the shape of the cross-section of channels or the geometrical arrangement of channels to one another within a unit cell may affect the pressure exerted by fluid within the channels and / or the pressure exerted by the matrix on the surface area of the channels.

[0121] Furthermore, the shape and arrangement may also affect the velocity of filtrate or mass permeating across channels, for example, to leave a channel of one fluid network and enter a channel of another fluid network. Thus, transport characteristics across fluid networks (e.g., filtrate production, mass diffusion, etc.) may be affected by the pressure and velocity fields influenced by the unit cell architectures. FIG. 10 shows the pressure and velocity fields of various unit cell architectures - square packed channels, hexagonal packed channels, hexagonal packed annuli, and square packed annuli - on a digital micromirror device (DMD) pixel grid. Furthermore, the present disclosure finds that as the sizes of various features of a unit cell (e.g., sizes of channels) are driven down, square packed channels may allow for an exact or precise registration of channel parameters, as shown in the DMD pixel grid. Thus, the 2D transport simulation of pressure and velocity fields within a unit cell can be informative in deciding which unit cell architecture can enable the highest degree of filtrate transport per unit surface area or mass diffusion per unit surface area. Also or alternatively, the 2D transport simulation of pressure and velocity fields within a unit cell can be informative in deciding which unit cell architecture can provide the transport characteristics required by the reference organ system.

[0122] FIG. 11A and FIG. 11B show heatmaps showing the pressure field, and velocity field within an extrusion of the unit cell architecture of square packed channels, according to nonlimiting embodiments of the present disclosure. Moreover, FIG. 11 demonstrates that, in some embodiments, unit cell architectures can be extruded to simulate pressure and velocity fields across a 3-dimensional space (e.g., as shown in heat maps 1110 and 1120, respectively). This 3D simulation can be useful as functional regions may be formed from an extrusion of a unit cell array. Thus, since transport characteristics can be influenced by pressure and velocity fields, thesimulation of pressure field and velocity fields across a three-dimensional space can be used to inform or guide the three-dimensional design of functional regions. For example, extrusion lengths for various channels may be determined using this simulation so that the functional region thus designed is able to achieve a transport characteristic (e.g., filtrate production across fluid networks, mass diffusion across fluid networks, etc.) that matches, or satisfies a similarity threshold with, the known transport characteristic of the reference organ system.

[0123] FIG. 12 shows graphs illustrating relationships between a transport characteristic (e.g., filtrate production, mass diffusion, etc.), matrix permeability, and channel size, according to nonlimiting embodiments of the present disclosure. Moreover, the graphs of FIG. 12 demonstrate an example methodology for using a known transport characteristic (e.g., filtrate produced per unit volume, mass diffused per unit volume) from a reference organ system to determine model parameters for a 3D printed organ system, according to non-limiting embodiments of the present disclosure.

[0124] For example, graph 1210 in FIG. 12A is a three dimensional plot mapping a transport characteristic to a matrix parameter and a channel parameter. Specifically, the transport characteristic in this example is the filtrate produced per unit volume, which is indicated in the Z axis. The matrix parameter (a measurement of a property of the matrix (e.g., the space between fluid networks)) is permeability, scaled logarithmically and plotted along the Y axis. The channel parameter is a size (e.g., cross-sectional area) of a channel of the fluid network, and is plotted along the X axis. As previously discussed in relation to FIG. 8, known transport characteristics of a reference organ system may be used to determine appropriate model parameters for designing an organ system to be 3D printed. For example, based on the known transport characteristics, one may narrow the possibilities for the matrix parameter (e.g., permeability values for the matrix) and channel parameter (e.g., channel sizes for a fluid network).

[0125] Accordingly, graph 1220 in FIG. 12B shows a two dimensional plot mapping the channel parameter (channel size) along the Y axis to the matrix parameter (permeability) along the X axis. Using the fluid network models, which specify a set of channel parameters and other geometries determined for fluid networks using their known flow characteristics (e.g., flow conductance per unit volume (C / V), other model parameters (e.g., matrix properties, unit cell architecture) can bedetermined. For example, using known flow characteristics and determined channel sizes for a given channel, one may use graph 1220 to sweep over or determine possible permeability values for the matrix surrounding the channel.

[0126] Similarly, in some embodiments, using the determined channel parameters and known transport characteristics (e.g., filtrate production per unit volume, mass diffused per unit volume of fluid transported through the fluid network, etc.), simulations of pressure and velocity for various configurations of unit cell architectures can be used to optimize the 2D design of a unit cell and / or a 3D design of the extruded unit cell. The designs and model parameters that allow models of the fluid networks and / or organ system to achieve transport characteristics and flow characteristics matching (or satisfying similarity thresholds) with those of the reference organ system can be used to 3D print the organ system.VI. Generating a 3D Printed Organ System For Selective Transport Across Fluid Networks

[0127] FIG. 13 is a flow diagram showing an example process 1300 for generating a 3D printed organ system for selective transport across fluid networks, according to non-limiting embodiments of the present disclosure. One or more blocks, steps, or methods of process 1300 may be performed by a computing system, such as computing system 100, or a component thereof (e.g., computing device 101, 3D printing apparatus 124, etc.). For ease of explanation, process 1300 is described as being performed by a computing device having a processor. Such a computing device, however, does not necessarily represent a single computing device. For example, such a computing device may include but is not limited to computing device 101 having the processor 102, and 3D printing apparatus 124.

[0128] At block 1302, a computing device may generate an organ system model representing a functional region of a reference organ system. Example embodiments for designing and / or generating the organ system model are described herein (e.g., in relation to FIGS. 7 and 8). For example, in at least some embodiments, generating the organ system model (e.g., such as but not limited to organ system model 110 or 748) may include identifying a transport characteristic between two or more fluid networks within a functional region of the reference organ system. Insome aspects, the computing device may additionally identify flow characteristics of the fluid networks of the reference organ system. The computing device may generate, for each of the two or more fluid networks within the functional region of the reference organ system, a model of the fluid network for the reference organ system (such as but not limited to fluid network models 112 and 734). The fluid network model may include channel parameters for a plurality of channels associated with the fluid network for the reference organ system. Generating the organ system model may further include determining, based on the transport characteristic, a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks of the reference organ system. The computing device may then integrate the models of each of the two or more fluid networks of the reference organ system to generate the organ system model. In some aspects, the organ system model includes at least a representation of the functional region of the reference organ system based on the wall thicknesses between respective channels between the two or more fluid networks of the reference organ system.

[0129] At block 1304, the computing device may generate a tile of the functional region of the organ system to be 3D printed. For example, the computing device may generate a computer-aided design (CAD) of the tile on a simulated build plane for 3D printing, as part of the machine instructions 106 for 3D printing the organ system. Also or alternatively, a computing device or component thereof, such as 3D printing apparatus 124, may generate the tile on a build plane (e.g., build plane 130). The tile may represent a cross-section (e.g., at middle or at a base) of the functional region. For example, the tile may represent a two dimensional array of unit cells, where each unit cell may comprise a tile subunit. In various embodiments, the organ system model representing the functional region may specify the cross-sectional architecture associated with the reference organ system. The cross-sectional architecture may specify a relative location, within a cross-section of a functional region of the reference organ system, of each of the plurality of channels of each fluid network of the two or more fluid networks to each of a plurality of channels of other fluid networks of the two or more fluid networks. The tile may be based on the cross- sectional architecture associated with the reference organ system. A subunit of the tile may be a unit cell of the cross-sectional architecture, as previously discussed herein (e.g., in relation to FIGS. 2, 3, 5, and 6).

[0130] In some embodiments, the cross-sectional architecture may further specify a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks in the functional region. In some aspects, the wall thickness between the channel of one fluid network to the channel of another fluid network may be based on a material property of a medium between the fluid networks (e.g., printed gel), such as but not limited to one or more matrix parameters 742.

[0131] The computing device (e.g., 3D printing apparatus 124) may generate the tile based on the appropriate parameters determined for the tile (e.g., channel parameters, matrix parameters, unit cell architecture, etc.) as specified by the organ system model. For example, a computing device such as but not limited to the 3D printing apparatus 124 can modulate characteristics for various parameters of the matrix (the medium between the fluidic networks) during the printing process. For example, dosing less light in a certain region of the tile may result in a lower extent of polymerization, a higher permeability, and a softer material in that region. This can affect mass transport (e.g., transport characteristics), whether by advection through the gel (e.g., in a filtration application), or by diffusion.

[0132] At block 1306, the computing device may extrude the tile along an axis perpendicular to the tile to form the functional region for the 3D printed organ system. For example, if the tile, build plane, and / or cross-sectional architecture of the functional region is along an X-Y axis, the tile may be extruded along the Z-axis. In some embodiments, the length of extrusion may be a channel parameter determined during the design of the organ system model. For example, the length of extrusion may be determined as a result of optimization to allow the fluid network to achieve flow characteristics that match or otherwise achieve similarity thresholds with the flow characteristics of the respective fluid network of the reference organ system. In some embodiments, the extrusion may occur as part of a computer-aided design (CAD) on a simulated build plane for 3D printing, as part of the machine instructions 106 for 3D printing the organ system. Also or alternatively, a computing device or component thereof, such as 3D printing apparatus 124, may extrude the tile generated on a build plane (e.g., build plane 130) of the 3D printing apparatus.

[0133] At block 1308, the computing device may plumb the plurality of channels of each fluid network to form a branching region. If plumbed at each end of the functional region, two branchingregions may be formed for the respective ends of the functional region (e.g., as previously described in relation to FIGS. 2 and 3). In some embodiments, the branching region at each end of the functional region may be characterized by an increased branching among the plurality of channels of each fluid network with increasing proximity towards the functional region. For each branching region, the increase in branching may start from a single channel at an end of the branching region that is opposite of the functional region.

[0134] In some embodiments, for at least one fluid network of the two or more fluid networks, and for one or both branching regions corresponding to each end of the functional region, the computing device may fluidically connect the single channel at the end of the branching region to a boundary channel subunit. Each boundary channel subunit may be extruded, thereby forming a boundary channel (e.g., an inlet or outlet) terminating at a boundary of the organ system (e g., an opening). For example, the boundary channel can be one of an afferent channel terminating at an inlet; an efferent channel terminating at an outlet; or a blind network.

[0135] In some embodiments, the aforementioned branching and / or extrusions may occur as part of a computer-aided design (CAD) on a simulated build plane for 3D printing, as part of the machine instructions 106 for 3D printing the organ system. Also or alternatively, a computing device or component thereof, such as 3D printing apparatus 124, may plumb the channels to form the branching regions as described and / or form the extrusions as described.

[0136] At block 1310, the computing device (e.g., 3D printing apparatus 124) may add printing gel exterior to the two or more fluid networks and within a bounding volume for the 3D printed organ system. For example, the computing device may designate, based on the predetermined boundary for the organ system, a bounding volume of the 3D printed organ system. In some embodiments, the printed gel may comprise a hydrogel matrix. Also or alternatively, the printing gel may be modified or modulated to exhibit the matrix parameter determined as most appropriate for facilitating selective transport in accordance with the transport characteristics of the reference organ system. For example, the matrix parameter (e.g., the material property of the printing gel) may be a porosity of the hydrogel matrix.

[0137] In some embodiments, a computing device such as #D printing apparatus 124 may additionally add other materials, as appropriate for the various structures of the 3D printed organ system. For example, in some embodiments, a fluid network (e.g., fluid network 300a and / or 300b) may be configured to carry a cellularized gel. In some embodiments, a fluid network with cellularized gel may refer to a fluid network filled with or configured to be filled with a medium containing biological cells.

[0138] The fluid network may be filled with such a medium containing biological cells through a variety of methodologies. In some embodiments, the fluid network may be filled with the medium by flowing a suspension of cells through the fluid network. This may cause the biological cells to adhere to channel walls of the fluid network. In some embodiments, the fluid network may be filled with the medium by flowing a suspension of cells into the fluid network, stopping the flow, and closing both ends of the fluid network. In some embodiments, the fluid network may be filled with the medium by flowing a suspension of cells into a fluid network having only one port for inlet and outlet (referred to herein as a “blind network” as will be discussed further herein) in a water-permeable gel (e.g., “dead-end seeding”). In such embodiments, the water may be pushed through the gel but the biological cells of the medium can by trapped inside the channels of the blind network and accumulate there. In some embodiments, the fluid network may be filled with the medium by flowing a suspension of the biological cells into the fluidic network and arresting them there by dramatically reducing the viscosity of the suspension. This could be done by making the suspension shear-thinning, changing the temperature, or polymerizing the suspension medium.

[0139] FIG. 14 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on alternating square packed circular channels, according to nonlimiting embodiments of the present disclosure. Various steps of example process may be performed by computing system 100, computing device 101, and / or 3D printing apparatus 124.

[0140] The process may involve determining a design of a unit cell architecture for a functional region of the organ system to be 3D printed. As shown by illustration 1402, an example design for the unit cell architecture may include an arrangement of square packed circular channels, each unit cell having a total of four channels, with half of the channels spaced diagonally from another assigned for a first fluid network (a cellularized chamber) and the other half of the four channelsassigned for a second fluid network (a vasculature). The design of the unit cell architecture may further include but are not limited to: channel parameters (e.g., size, shape, and / or length of each channel), matrix parameters (properties of the matrix between the fluid networks, such as permeability, porosity, charge conductivity, and the like), distances between channels (e.g., wall thickness, pitch, etc.), the size of the unit cell, and the like. Furthermore, the design of the unit cell architecture may be modeled using aforementioned methods and techniques. As previously discussed, the unit cell architecture may be designed based on knowledge about a reference organ system on which the organ system to be 3D printed is modeled on. For example, knowledge about the types of fluid networks involved in the reference organ system, the transport characteristics of the functional region of the reference organ system, boundary conditions, and flow characteristics of each fluid network involved in the functional region may guide various parameters for designing the unit cell architecture based on the methods and techniques described herein (e.g., in relation to FIGS. 8-13). The unit cell architecture may comprise a subunit of a tile, and may thus be used to form the tile by replication the subunit across a designated area of the functional region.

[0141] As shown in illustration 1404, the tile may comprise an array of the unit cell architecture. Furthermore, the tile may represent a base or a cross-section of the functional region of the organ system to be 3D printed. In some embodiments, the area of the tile, which is representative of the area of the functional region of the organ system to be 3D printed, may be based on or modeled after the area of the functional region of the reference organ system. Also or alternatively, the area of the tile may be determined via the organ system model as one that maintains the transport characteristic and flow characteristics representative of the reference organ system.

[0142] As shown in illustration 1406, the tile may be extruded along a z-axis to form a functional region modeled after the functional region of the reference organ system. The length of extrusion may be based on predetermined channel parameters (channel lengths) that maintain the flow characteristics known to be exhibited by the reference organ system. In some embodiments, different channels of a fluid network and / or different fluid networks may be extruded at different lengths. For example, different fluid networks in a reference organ system may be known to have different flow characteristics. The fluid networks in the tile may be extruded differently to achieve the different flow characteristics. In some embodiments, the length of the extrusion of the tile orof one or more channels and / or fluid networks may represent the length of the functional region in the organ system to be 3D printed.

[0143] As shown in illustration 1408, after the extrusion, channels of each fluid network at both ends of the functional region may be plumbed to form branching regions at both ends of the functional region. The plumbing may involve, for each fluid network, an iterative step of joining together two or more channels to form a single channel leading to the two channels via a branch (e.g., bifurcation point). The number of iterations may depend on the number of channels for each fluid network and / or branching design parameters (e.g., determined to achieve the flow characteristics for the fluid network). In some embodiments, the distance of segments of channels in the branching region between branches may be determined based on the branching design parameters. Based on the iterations, there may be lesser and lesser channels for each fluid network as one moves away from the fluid region along each branching region. In the far end of each branching region, each fluid network may stem from a single channel may or may not have a port. For example, for organ systems relying on a compartment or a blind network as a fluid network, the single channel may not be configured to have any port. In such cases, the single channel can merely serve as a connection (e.g., conduit) between two downstream channels that may branch into further channels downstream.

[0144] Alternatively, in embodiments where a fluid network has an input port or an output port, the single channel may branch into two downstream channels at one end, while allowing the other end to form a conduit to an input port or an output port. For example as shown in illustration 1410, both fluid networks may provide, at the ends of both branching regions, a single channel that can be plumbed to form conduits leading to input ports and output ports for the respective fluid networks. In some embodiments, the input port and output ports may be in different ends of the 3D printed organ system. Also or alternatively, a port of one fluid network and a port of another fluid network may be located at different ends or sides of the 3D printed organ system.

[0145] As shown in illustration 1412, a bounding volume may be generated to designate the boundaries of the 3D printed organ system. The bounding volume may encapsulate the fluid networks of the modeled organ system to be 3D printed, the volume for the matrix between the fluid networks intended to facilitate the selective transport between the fluid networks, thefunctional region, the branching regions, as well as the input and / or output ports. In some embodiments, the bounding volume may be automatically generated (e.g., by the computing system 100, computing device 101, and / or 3D printing apparatus 124) based on a 3 dimensional boundary that is predetermined distance beyond the aforementioned contents of the modeled organ system. A non-limiting example of the bounding volume is described further below, in relation to FIG. 15.

[0146] As shown in illustration 1414, a Boolean subtraction may be performed of the fluid networks of the organ system model from the bounding volume. The subtraction may result in a void volume. A printing gel may be filled within at least a portion of the void volume as shown. The printing gel may comprise previously described matrix properties (e.g., permeability, porosity, charge conductivity, etc.) determined to be most optimal for causing the functional region to achieve the transport characteristics of the reference organ system. In some embodiments, the printing gel used to fill space between fluid networks in the functional region (e.g., first printing gel) may be different from or may exhibit different properties from the printing gel used for void space outside of the functional region (e.g., second printing gel). In at least one implementation of such embodiments, a Boolean subtraction (first Boolean subtraction) may be performed of the fluid network from a volume designated for the functional region. The first printing gel may be used to fill the void space resulting from this Boolean subtraction. Another Boolean subtraction (second Boolean subtraction) may be performed of the resulting structure from the bounding volume. The second printing gel may be used to fill the void space resulting from the second Boolean subtraction.

[0147] FIG. 15 is an illustration of an example structure formed using an example bounding volume for generating a 3D printed organ system, according to non-limiting embodiments of the present disclosure. As previously discussed, the bounding volume 1500 may encapsulate the fluid networks 1550 of the modeled organ system to be 3D printed (fluid networks 1550 are not shown to scale next to bounding volume 1500) . The fluid networks can include input and output ports, conduits leading to input and output ports, branching regions, as well as the functional regions. Furthermore, the bounding volume may include the volume for the matrix between the fluid networks intended to facilitate the selective transport between the fluid networks. The boundingvolume can thus be used (e.g., by computing system 100, computing device 101, and / or 3D printing apparatus 124) to determine a void space between the aforementioned contents of the organ system and the bounding volume. The void space may be used (e.g., by the 3D printing apparatus 124) to add a printing gel to provide the structure shown in FIG. 15.

[0148] The distance of the bounding volume 1500 from the aforementioned contents may provide a fixed thickness of external wall 1508 surrounding the aforementioned contents (e.g., internal features of the organ system). Tn some embodiments, the structure may include or may be formed alongside supports 1506 (e.g., FISCHER FOAM supports) configured to facilitate drainage and top-to-bottom printing of the organ system model. As shown by marker 1502, in some aspects, such supports 1506 may be disconnected from other portions of the structure, such as the input and / or output ports (or the conduits thereof). Furthermore, in some embodiments, the structure may have troughs 1504 (e.g., near the input and / or output ports) to facilitate drainage during the 3D printing of the organ system. Thus, the bounding volume and various features formed using the bounding volume may aid in the 3D printing of the organ system (e.g., via digital light processing (DLP) stereolithography).

[0149] FIG. 16 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on a set of square packed circular cannels belonging to two different fluid networks in a ratio of 3: 1 (“3: 1 ratio square packed circular channels”), according to non-limiting embodiments of the present disclosure. Various steps of the example process may be performed by computing system 100, computing device 101, and / or 3D printing apparatus 124.

[0150] Like the process described in relation to FIG. 14, the example process of FIG. 16 may involve determining a design of a unit cell architecture for a functional region of the organ system to be 3D printed. Here, as shown by illustration 1602, an example design for the unit cell architecture may include an arrangement of square packed circular channels having a total of four channels, with three of the four channels assigned for a first fluid network (a cellularized chamber) and the remaining one of the four channels assigned to a second fluid network (a vasculature). The design of the unit cell architecture may further include but are not limited to: channel parameters (e.g., size, shape, and / or length of each channel), matrix parameters (properties of the matrix between the fluid networks, such as permeability, porosity, charge conductivity, and the like),distances between channels (e.g., wall thickness, pitch, etc.), and the like. Furthermore, the design of the unit cell architecture may be modeled using aforementioned methods and techniques.

[0151] As previously discussed, the unit cell architecture may be designed based on knowledge about a reference organ system on which the organ system to be 3D printed is modeled on (e.g., the types of fluid networks involved in the reference organ system, the transport characteristics of the functional region of the reference organ system, boundary conditions, and flow characteristics of each fluid network involved in the functional region). The unit cell architecture may comprise a subunit of a tile, and may thus be used to form the tile by replication the subunit across a designated area of the functional region. Although the tile subunit used in the example process shown in FIG. 16 (e.g., 3:1 square packed circular channels) is characteristically different than the tile subunit used in the example process shown in FIG. 14 (e.g., 1 :1 square packed circular channels), illustrations 1604, 1606, 1608, 1610, 1612, and 1614 show steps similar to steps 1404, 1406, 1408, 1410, and 1414, respectively, previously described in relation to FIG. 14.

[0152] FIG. 17 is a schematic illustrating an example process for generating a 3D printed organ system using a tile subunit based on hexagonally packed hexagonal annuli, according to nonlimiting embodiments of the present disclosure. Various steps of example process may be performed by computing system 100, computing device 101, and / or 3D printing apparatus 124.

[0153] As previously discussed, designing a model of the 3D printed organ system may involve determining a design of a unit cell architecture for a functional region of the organ system to be 3D printed. Here, as shown by illustration 1702, an example design for the unit cell architecture may include an annular arrangement of channels, specifically a hexagonal annulus where an outer hexagonal ring is a channel assigned to a first fluid network (a cellularized chamber) and a channel within located inside the void formed by the hexagonal ring is assigned to a second fluid network (a vasculature), while leaving space (e.g., matrix) between both fluid networks. The design of the unit cell architecture may further include but are not limited to: channel parameters (e.g., size, shape, and / or length of each channel), matrix parameters (properties of the matrix between the fluid networks, such as permeability, porosity, charge conductivity, and the like), distances between channels (e.g., wall thickness, pitch, etc.), and the like. Furthermore, the design of the unit cell architecture may be modeled using aforementioned methods and techniques. Aspreviously discussed, the unit cell architecture may be designed based on knowledge about a reference organ system on which the organ system to be 3D printed is modeled on. For example, knowledge about the types of fluid networks involved in the reference organ system, the transport characteristics of the functional region of the reference organ system, boundary conditions, and flow characteristics of each fluid network involved in the functional region may guide various parameters for designing the unit cell architecture based on the methods and techniques described herein (e.g., in relation to FIGS. 8-13). The unit cell architecture may comprise a subunit of a tile, and may thus be used to form the tile by replication the subunit across a designated area of the functional region.

[0154] As shown in illustration 1704, the tile may comprise an array of the unit cell architecture, which in the example shown in FIG. 17 is a hexagonal annulus. As previously discussed, the tile may represent a base or a cross-section of the functional region of the organ system to be 3D printed. As shown in illustration 1706, like illustration 1406 in FIG. 14, the tile may be extruded along a z-axis to form a functional region modeled after the functional region of the reference organ system.

[0155] After the extrusion, channels of one or more fluid networks at both ends of the functional region may be plumbed to form branching regions at both ends of the functional region. However, in some embodiments, the matrix between the fluid networks may also be plumbed at both ends of the functional region. In some aspects, the plumbed matrix may form its own branching region situation between the branching regions of the fluid networks. For example, as shown in illustrations 1708 through 1712, a plumbing of a fluid network whose channel is situated inside the hexagonal annulus of the unit cell architecture (e.g., the vasculature as shown in illustration 1708) may be followed by a plumbing of a matrix between the fluid networks (e.g., as shown in illustration 1710), and subsequently followed by the plumbing of the second fluid network whose channels form the hexagonal ring in the unit cell architecture (e.g., the cellularized gel as shown in illustration 1712).

[0156] As previously discussed, the plumbing may involve, for each fluid network, an iterative step of joining together two or more channels to form a single channel leading to the two channels via a branch (e.g., bifurcation point). In annular unit cell architectures (e.g., hexagonal annuli,circular annuli, etc.) where the matrix is situated between a ring formed by a first fluid network and an inner core formed by a second fluid network, the plumbing of the matrix may follow the plumbing of the fluid network forming the inner core (second fluid network) in like fashion. The number of iterations may depend on the number of channels for each fluid network and / or branching design parameters (e.g., determined to achieve the flow characteristics for the fluid network). In some embodiments, the distance of segments of channels in the branching region between branches may be determined based on the branching design parameters. Based on the iterations, there may be lesser and lesser channels for each fluid network as one moves away from the fluid region along each branching region. In the far end of each branching region, each fluid network may stem from a single channel.

[0157] In the example process of FIG. 17, at either ends of the branching regions, the fluid networks extend through conduits leading to input ports and output ports, as shown in illustration 1714.

[0158] As shown in illustration 1716, like illustration 1412 of FIG. 14, a bounding volume may be generated to designate the boundaries of the 3D printed organ system. The bounding volume may encapsulate the fluid networks of the modeled organ system to be 3D printed, the volume for the matrix between the fluid networks intended to facilitate the selective transport between the fluid networks, the functional region, the branching regions, as well as the input and / or output ports.

[0159] As shown in illustration 1718, like illustration 1414 of FIG. 14, a Boolean subtraction may be performed of the fluid networks of the organ system model from the bounding volume. The subtraction may result in a void volume. A printing gel may be filled within at least a portion of the void volume as shown. The printing gel may comprise previously described matrix properties (e g., permeability, porosity, charge conductivity, etc.) determined to be suitable or most optimal for causing the functional region to achieve the transport characteristics of the reference organ system. In some embodiments, the printing gel used to fill space between fluid networks in the functional region (e.g., first printing gel) may be different from or may exhibit different properties from the printing gel used for void space outside of the functional region (e.g., second printing gel). In at least one implementation of such embodiments, a Boolean subtraction (first Booleansubtraction) may be performed of the fluid network from a volume designated for the functional region. The first printing gel may be used to fill the void space resulting from this Boolean subtraction. Another Boolean subtraction (second Boolean subtraction) may be performed of the resulting structure from the bounding volume. The second printing gel may be used to fill the void space resulting from the second Boolean subtraction.

[0160] FIG. 18 is a schematic illustrating example processes for extrusion and plumbing for generating a 3D printed organ system, according to non-limiting embodiments of the present disclosure. In order to extrude a tile used to generate a functional region for the 3D printed organ system, the unit cell architecture for a unit cell (a subunit of the tile) may need to be determined. As shown in illustration 1802, the unit cell architecture involves alternating square packed circular channels for two fluid networks (like the unit cell architecture of 1402). The design of the unit cell architecture may further include but are not limited to: channel parameters (e.g., size, shape, and / or length of each channel), matrix parameters (properties of the matrix between the fluid networks, such as permeability, porosity, charge conductivity, and the like), distances between channels (e.g., wall thickness, pitch, etc.), a size of the unit cell (D), and the like.

[0161] Furthermore, the design of the unit cell architecture may be modeled using previously discussed methods and techniques based on knowledge (knowns) about a reference organ system on which the organ system to be 3D printed is modeled on. For example, the knowns may include but are not limited to a fluid characteristic of a fluid network (e.g., conductance per volume) and a transport characteristic of the functional region (e.g., fdtrate produced per volume, mass diffused per unit volume, etc.). In some embodiments, the knowns may further include other parameters that may need to be configured to certain values and / or dimensions make the aforementioned knowns (e.g., fluid characteristics and transport characteristics). For example, the knowns may further include but are not limited to matrix parameters (e.g., permeability, porosity, charge conductivity, etc.) for the material or space (collectively referred to herein as “matrix”) between the fluid networks, and parameters for the channels or other features of the unit cell (referred to herein as “channel parameters”) (e.g., size of channel or other unit cell features, channel length, etc.). The knowns may be used to design the aforementioned aspects of the unit cell architecture, such as the shape and arrangement of the fluid networks (e.g., square packed channels, hexagonalpacked channels, square packed annulus, and hexagonal packed annulus, etc.) and the size of the unit cell (£>). Furthermore, the knowns may be used to determine the size of the functional region, which may guide the size of the unit cell array (e.g., the tile forming a base and / or cross-section of the functional region) as well as the length (L) of the extrusion.

[0162] For example, as shown in illustration 1804, the tile may comprise an array of the unit cell architecture, which in the example shown in FIG. 18 is square packed alternating circular channels. However, based on the determined size of the functional region, such as the size of the unit cell array, the unit cell may be replicated (n) times to form the tile. The number of replications (n) of the unit cell times the size of the unit cell may equal to or be within tolerable limits of the size of the unit cell array. As previously discussed, the tile may represent a base or a cross-section of the functional region of the organ system to be 3D printed.

[0163] As shown in illustration 1806, the tile may be extruded along a z-axis to form a functional region modeled after the functional region of the reference organ system. The tile may be extruded to a length (L) that in accordance with the functional region of the reference organ system. Also or alternatively, the length (L) may be determined based on knowledge about the characteristics of reference organ system (e.g., transport characteristics, fluid characteristics), and a determination of channel parameters (e.g., channel length) that help to achieve the characteristics of the reference organ system. In some embodiments, the channels of both fluid networks may be extruded the same length. For example, channels of a first fluid network (e.g., a vasculature) may be extruded the same length as channels of a second fluid network (e.g., cellularized gel). Alternatively, in some embodiments, channels of one fluid network may be extruded to a different length than channels of another fluid network. Also or alternatively, in some embodiments, various portions of the unit cell array may be extruded at different lengths (e.g., to form various three-dimensional shapes for the functional region).

[0164] After the extrusion, channels of the fluid networks at both ends of the functional region are plumbed to form branching regions at both ends of the functional region. In some embodiments, the matrix between the fluid networks may also be plumbed at both ends of the functional region. As previously discussed, the plumbing may involve, for each fluid network, an iterative step of joining together two or more channels to form a single channel leading to the two channels via abranch (e.g., e.g., bifurcation point). The number of iterations may depend on the number of channels for each fluid network and / or branching design parameters (e.g., determined to achieve the flow characteristics for the fluid network). In some embodiments, the distance of segments of channels in the branching region between branches may be determined based on the branching design parameters. Based on the iterations, there may be lesser and lesser channels for each fluid network as one moves away from the fluid region along each branching region. In the far end of each branching region, each fluid network may stem from a single channel.

[0165] In at least one aspect, as shown in illustration 1808, the radius of each generation of branching in the branching regions can be set using Murray’s Law (e.g., the cube of the radius of a branch is equal to the sum of cubes of the radii of the next downstream branch, or n3= n3+ n3) to minimize the resistance of flow in the fluid networks in networks, relative to their total volume. Also or alternatively, the dimensions and arrangement of the branching network channels can be chosen so as to minimize the volume of the device taken up by the branching networks.

[0166] As shown in illustration 1810, after branching regions are formed, inlets and outlets may be plumbed from the branching regions for one or more fluid networks. As used herein, an inlet may refer to a structure comprising the input port and conduit leading from the branching region to the input port; and an outlet may refer to a structure comprising the output port and a conduit leading from the branching region to the output port. In some aspects, the inlet may be plumbed such that the input port is at the boundary of a designated bounding volume; and the outlet may be plumbed such that the output port is at the boundary of the designated bounding volume. As previously discussed, the bounding volume may function as a predetermined boundary of the organ system to be 3D printed. The bounding volume may thus encapsulate, for example, the fluid networks of the modeled organ system to be 3D printed, the volume for the matrix between the fluid networks intended to facilitate the selective transport between the fluid networks, the functional region, the branching regions, as well as the inlets and outlets (with the input and output ports at the end of the bounding volume). In some embodiments, the bounding volume may be automatically generated (e.g., by the computing system 100, computing device 101, and / or 3D printing apparatus 124) based on a 3D boundary that is predetermined distance beyond the aforementioned contents of the modeled organ system.VII. Blind Network

[0167] FIG. 19 is a schematic illustrating an example blind network for a 3D printed organ system, according to non-limiting embodiments of the present disclosure. As previously discussed, in some embodiments, a fluid network of an organ system may not necessarily have an input port and an output port. A blind network, as used herein, may refer to a fluid network that does not have distinguishable input port and output port, and instead has a single port. In some embodiments, the blind network may be merely a distribution network (e.g., to distribute, mass, solutes, heat, or other properties to other fluid network), without any portion serving for collection. This can be useful when contents of the fluid within the blind network is to be exchanged with an external fluid of another fluid network by diffusion or by deforming the entire organ system.

[0168] In some embodiments, the single port may facilitate both the entry and exist of a fluid that the blind network is configured to carry. For example, the human lung can be modeled as shown in FIG. 19. The function of the lung can be recapitulated in an organ system model comprising two fluid networks 1902 and 1904. The first fluid network 1902 is a blind network configured to carry air. The other fluid network 1904 is not a blind network and is configured to carry blood. At the functional region 1906, the first fluid network diffuses contents from the air (e.g., oxygen molecules and / or carriers) into the second fluid network, while receiving contents from the blood (e.g., carbon dioxide molecules and / or carriers). However, the air in the first fluid network flows into the first fluid network and flows out of the first fluid network at the same port 1908.VIII. Conclusion

[0169] Aspects of the present embodiment are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to the embodiment. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0170] These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.

[0171] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0172] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0173] The descriptions of the various embodiments of the present embodiment have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. Theterminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

CLAIMS1. A device for high-efficiency selective transport across fluid networks, the device comprising: a plurality of fluid networks comprising at least a first and a second fluid network, each fluid network having a plurality of channels; a matrix between the plurality of fluid networks, the matrix comprising material configured to facilitate selective transport of a filtrate or a mass from the first fluid network to the second fluid network; and a functional region comprising at least portions of each of the plurality of fluid networks and the matrix, wherein a cross-section of the functional region comprises an array of unit cells, wherein each unit cell has a unit cell architecture characterized by a cross-sectional shape, a channel size, and a relative location for each of: a channel of the first fluid network and a channel of the second fluid network, wherein the unit cell architecture is optimized to achieve a transport characteristic for the functional region characterizing the selective transport, and wherein the transport characteristic for the functional region satisfies a similarity threshold with a predetermined transport characteristic.

2. The device of claim 1, wherein the reference organ system includes a plurality of reference fluid networks comprising at least a first reference and a second reference fluid networks corresponding to the first and second fluid networks, respectively. wherein the first fluid network is configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by the first reference fluid network, wherein the second fluid network is configured to exhibit a flow characteristic that satisfies a similarity threshold with a flow characteristic exhibited by the second reference fluid network.

3. The device of claim 2,wherein the first fluid network is configured to exhibit the flow characteristic based on an optimization of: the channel size of the channel of the first fluid network, and a length of the channel of the first fluid network in the functional region, wherein the second fluid network is configured to exhibit the flow characteristic based on an optimization of: the channel size of the channel of the second fluid network, and a length of the channel of the second fluid network in the functional region.

4. The device of claim 2, wherein the flow characteristics respectively exhibited by the first fluid network, the second fluid network, the first reference fluid network, or the second reference fluid network is at least one of a fluid conductance or a viscosity exhibited by the respective fluid networks.

5. The device of claim 1, wherein the transport characteristic is one of: a filtrate production per unit volume of a fluid network of the plurality of fluid networks; a transport of mass per unit volume of the fluid network; or a transport of heat per unit volume of the fluid network.

6. The device of claim 1, wherein the cross-sectional shape of the channel of the first fluid network is a hexagonal annuli, the cross-sectional shape of the channel of the second fluid network is a hexagon, and the relative location of the channel of the second fluid network is inside an annulus formed by the channel of the first fluid network, wherein the channel of the first fluid network is separated from the channel of the second fluid network by a predetermined wall thickness formed by the matrix.

7. The device of claim 1, wherein the cross-sectional shape of the channel of the first fluid network is a square annuli, the cross-sectional shape of the channel of the second fluid network is a square, and the relative location of the channel of the second fluid network is inside an annulus formed by the channel of the first fluid network, wherein the channel of the first fluid network is respectively separated from the channel of the second fluid network by a predetermined wall thickness formed by the matrix.

8. The device of claim 1, wherein the cross-sectional shape of each of the channel of the first fluid network and the channel of the second fluid network is a hexagon, wherein any channel of the first fluid network or the second fluid network is separated from any other channel of the first fluid network or the second fluid network by a predetermined wall thickness formed by the matrix.

9. The device of claim 1, wherein the cross-sectional shape of each of the channel of the first fluid network and the channel of the second fluid network is a circle, wherein any channel of the first fluid network or the second fluid network is separated from any other channel of the first fluid network or the second fluid network by a predetermined wall thickness formed by the matrix.

10. The device of claim 1, further comprising: a branching region on each end of the functional region, wherein each branching region is characterized by an increased branching among the plurality of channels of each fluid network with increasing proximity towards the functional region, the increased branching starting from a single channel at an end of the branching region that is opposite of the functional region.

11. The device of claim 10, further comprising: an inlet and an outlet for the first fluid network, wherein the inlet and the outlet are respectively attached from the respective single channels at the ends of the respective branching regions; and12. The device of claim 11, further comprising: one or both of an inlet and an outlet for the second fluid network.

13. The device of claim 1, wherein the first and second fluid networks are fluidically independent.

14. The device of claim 1, wherein the first and second fluid networks are entangled in the functional region.

15. The device of claim 1, wherein, in each unit cell, the channel of the first fluid network and the channel of second fluid network fluid network are separated by a predetermined wall thickness formed by the matrix, wherein the predetermined wall thickness is based on a matrix parameter of the matrix.

16. The device of claim 15, wherein the matrix parameter is one or more of: a permeability of the matrix; a porosity of the matrix; or a charge conductivity of the matrix.

17. The device of claim 1, wherein the matrix comprises a printing gel.

18. The device of claim 17, wherein the printing gel comprises a hydrogel.

19. A device for facilitating selective transport across fluid networks, the device comprising: two or more fluid networks comprising at least a first fluid network and a second fluid network, each fluid network comprising a plurality of channels, each fluid network spanning an afferent distribution network, an efferent collection network, and a functional region between the afferent distribution network and the efferent collection network; and wherein the functional region is configured to cause a selective transport of a filtrate or a mass from the first fluid network to the second fluid network according to a transport characteristic of a reference organ system; wherein a cross-section of the functional region comprises an array of unit cells sharing a unit cell architecture; and wherein the unit cell architecture is characterized by a cross-sectional shape, a channel size, and a relative location for each of: a channel of the first fluid network and a channel of the second fluid network, and wherein the unit cell architecture is optimized to cause the functional region to achieve the transport characteristic of the reference organ system.

20. The device of claim 19, further comprising a matrix forming a wall between the first fluid network and the second fluid network in the functional region, wherein a thickness of the wall and a property of the matrix are optimized to cause the functional region to achieve the transport characteristic of the reference organ system.

21. The device of claim 20, wherein the property of the matrix is one or more of: a permeability of the matrix; a porosity of the matrix; or a charge conductivity of the matrix.

22. The device of claim 19, wherein the transport characteristic is one of: a filtrate production per unit volume of a fluid network of the two or more fluid networks; a transport of mass per unit volume of the fluid network; or a transport of heat per unit volume of the fluid network.

23. The device of claim 19, further comprising, for each fluid network, an inlet fluidly connected to and configured to deliver fluid to the afferent distribution network, and outlet fluidly connected to the and configured to receive fluid from the efferent collection network; wherein the inlet and outlet are exposed to one or more boundary conditions for the device; wherein the unit cell architecture is further optimized, based on the one or more boundary conditions, to allow the functional region to cause the selective transport according to the transport characteristic of the reference organ system.

24. The device of claim 19, wherein the afferent distribution network is characterized by an increased branching among the plurality of channels of each fluid network with increasing proximity towards the functional region, the increased branching starting from an inlet at an end of the afferent distribution network that is opposite of the functional region, wherein the efferent collection network is characterized by a decreased branching among the plurality of channels of each fluid network with increasing distance away from the functional region.

25. The device of claim 24, wherein the efferent collection network is connected to and configured to deliver fluid to an outlet.

26. The device of claim 19, wherein the cross-sectional shape is one or more of a hexagon or a hexagonal annulus.

27. The device of claim 19, wherein the cross-sectional shape is one or more of a circle or a circular annulus.

28. A method of designing an architecture for selective transport across fluid networks for a 3D printed organ system, the method comprising: identifying, by a computing device having a processor, two or more fluid networks associated with a reference organ system; identifying, by the computing device, a transport characteristic between the two or more fluid networks within a functional region of the reference organ system; generating, by the computing device, for each of the two or more fluid networks, a model of the fluid network, wherein the model includes channel parameters for a plurality of channels associated with the fluid network; determining, by the computing device, based on the transport characteristic, a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks; and integrating, based on the computing device, the models of each of the two or more fluid networks to generate an organ system model, wherein the organ system model includes at least a representation of the functional region based on the wall thicknesses between respective channels between the two or more fluid networks.

29. The method of claim 28, further comprising: generating the 3D printed organ system based on the organ system model.

30. The method of claim 28, wherein the representation of the functional region further includes a representation of a tile of the functional region, the tile comprising subunits for theplurality of channels of each of the two or more fluid networks within the functional region, wherein generating the 3D printed organ system comprises: generating, on a build plane, the tile of the functional region; extruding the tile along an axis perpendicular to the tile to form the functional region for the 3D printed organ system; and plumbing, at each end of the functional region, the plurality of channels of each fluid network to form a branching region.

31. The method of claim 29, wherein generating the 3D printed organ system comprises: designating a bounding volume for the 3D printed organ system, wherein the bounding volume includes at least the two or more fluid networks; and adding printing gel in at least a portion of a void volume resulting from a Boolean subtraction of the two or more fluid networks from the bounding volume.

32. The method of claim 28, wherein the channel parameters for the plurality of channels associated with the fluid network includes a channel size and a channel extrusion length for the fluid network.

33. The method of claim 28, further comprising: identifying a cross-sectional architecture associated with a reference organ system, wherein the cross-sectional architecture specifies a relative location, within a cross-section of a functional region of the reference organ system, of each of the plurality of channels of each fluid network of the two or more fluid networks to each of a plurality of channels of other fluid networks of the two or more fluid networks wherein the representation of the functional region is further based on the cross-sectional architecture.

34. The method of claim 28, further comprising, for each of the two or more fluid networks, prior to generating the model of the fluid network: determining one or more flow characteristics of fluid transported through the fluid network; andidentifying one or more boundary conditions for the fluid network, wherein the model of the fluid network is generated using the one or more flow characteristics and the one or more boundary conditions.

35. The method of claim 34, wherein the one or more flow characteristics comprises at least one of a conductance per unit or a viscosity of fluid across the plurality of channels of the fluid network within the functional region.

36. The method of claim 34, wherein the one or more boundary conditions of the fluid network comprises one or more of a pressure, an oxygen level, a tension, or an analyte concentration at a boundary of the fluid network.

37. The method of claim 28, wherein the transport characteristic between the two or more fluid networks at the functional region comprises one or more of a filtrate production per unit volume of at least one of the two or more fluid networks or a mass diffusion per unit volume of at least one of the two or more fluid networks.

38. The method of claim 28, wherein each fluid network is fluidically independent of each other.

39. The method of claim 28, wherein each fluid network corresponds to a vascular network, a duct, an airway, or a cell chamber.

40. The method of claim 28, further comprising: generating, based on the organ system model, machine readable instructions for 3D printing an organ system corresponding to the reference organ system.

41. The method of claim 40, wherein the machine readable instructions comprises: generating, on a build plane, a tile subunit of the functional region; extruding the tile subunit along a z-axis to form the functional region for the 3D printed organ system; andplumbing, at each end of the functional region, the plurality of channels of each fluid network to form a branching region.

42. The method of claim 40, wherein the machine readable instructions comprises: designating a bounding volume for the 3D printed organ system, wherein the bounding volume includes at least the one or more fluid networks; and adding printing gel in at least a portion of a void volume resulting from a Boolean subtraction of the one or more fluid networks from the bounding volume.

43. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform the method of any of claims 1-42.

44. A system comprising: a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform the method of any of claims 1-42.

45. A method of generating a 3D printed organ system for selective transport across fluid networks, the method comprising: generating, by a computing device having a processor, an organ system model representing at least a functional region of a reference organ system, the functional region characterized by two or more fluid networks and a transport characteristic between the two or more fluid networks, each fluid network having a plurality of channels; generating, on a build plane, using the organ system model, and based on a cross-sectional architecture of the functional region, a tile of the functional region; extruding the tile along an axis perpendicular to the tile to form the functional region for the 3D printed organ system; plumbing, at each end of the functional region, the plurality of channels of each fluid network to form a branching region; andadding printing gel exterior to the two or more fluid networks and within a bounding volume for the 3D printed organ system.

46. The method of claim 45, wherein the organ system model representing the functional region specifies the cross-sectional architecture associated with the reference organ system, wherein the cross-sectional architecture specifies a relative location, within a cross-section of a functional region of the reference organ system, of each of the plurality of channels of each fluid network of the two or more fluid networks to each of a plurality of channels of other fluid networks of the two or more fluid networks.

47. The method of claim 45, wherein the branching region at each end of the functional region is characterized by an increased branching among the plurality of channels of each fluid network with increasing proximity towards the functional region, the increased branching starting from a single channel at an end of the branching region that is opposite of the functional region.

48. The method of claim 46, further comprising: designating, based on the designated bounding volume of the 3D printed region, a number of branches for each branching region.

49. The method of claim 47, further comprising, for at least one fluid network of the two or more fluid networks: for one or both branching regions corresponding to each end of the functional region, fluidically connecting the single channel at the end of the branching region to a boundary channel subunit; and extruding each boundary channel subunit, thereby forming a boundary channel terminating at an opening.

50. The method of claim 49, wherein the boundary channel is one of: an afferent channel terminating at an inlet; an efferent channel terminating at an outlet; or a blind network.

51. The method of claim 45, wherein the cross-sectional architecture specifies a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks in the functional region.

52. The method of claim 51, wherein the wall thickness between the channel of one fluid network to the channel of another fluid network is based on a material property of the printed gel.

53. The method of claim 52, wherein the printed gel comprises a hydrogel matrix.

54. The method of claim 53, wherein the material property is a porosity of the hydrogel matrix.

55. The method of claim 45, wherein generating the organ system model comprises: identifying, by the computing device, a transport characteristic between two or more fluid networks within a functional region of a reference organ system; generating, by the computing device, for each of the two or more fluid networks within the functional region of the reference organ system, a model of the fluid network for the reference organ system, wherein the model includes channel parameters for a plurality of channels associated with the fluid network for the reference organ system; determining, by the computing device, based on the transport characteristic, a wall thickness between a channel of one fluid network, to a channel of another fluid network, for each of the two or more fluid networks of the reference organ system; and integrating, based on the computing device, the models of each of the two or more fluid networks of the reference organ system to generate the organ system model, wherein the organ system model includes at least a representation of the functional region of the reference organ system based on the wall thicknesses between respective channels between the two or more fluid networks of the reference organ system.

56. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform the method of any of claims 45-55.

57. A system comprising: a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform the method of any of claims 45-55.

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