WO2023233155A1 - Micron-scale 3d objects for the modulation of cell phenotype from pro to anti-inflammatory states - Google Patents

Abstract

The invention provides the use of micro-scale three-dimensional objects on a surface, to influence the extent to which macrophage attachment occurs at the surface and/or the phenotype of macrophage that attaches to the surface. The invention provides a product, such as a healthcare implant, wherein micro- scale three-dimensional objects are provided on a surface of the product.

Description

MICRON-SCALE 3D OBJECTS Field of the Invention The invention relates to the use of surface-mounted micron-scale 3D objects. The total number, size and shape of these objects can be selected to influence whether or not macrophage attachment occurs at the surface and the phenotype of macrophage that attaches to the surface. Background to the Invention Implanted devices are ubiquitous in healthcare, from coronary stents to hip replacements and glucose sensors to surgical meshes ^1-3. A major contributing reason for their significant failure rates is the foreign body response (FBR), often resulting in persistent inflammation and encapsulation of the device with a fibrous capsule and rejection ^4,5. To date, the understanding required to design low FBR implants a priori is missing, and in particular a systematic mapping of the critical relationships is needed to develop the necessary biomaterials ⁶. It is desirable to modulate the behaviour and phenotype of macrophages as key regulators of the immune response to biomedical implants. ^7-9 Macrophages exhibit a functional plasticity which plays a critical role in FBR induced inflammation and then tissue repair and regeneration 10. It is now understood that many physical parameters affect macrophage phenotype, simplified to naïve (M0), pro-inflammatory (M1) or anti-inflammatory (M2) with the last two representing opposite ends of macrophage polarisation spectrum ^11,12. Implanted spheres have been shown to mediate macrophage response and ultimate success or failure in vivo, ¹³ with material-induced cell shape changes shown to modulate macrophage phenotype ^11,12,14-16. Independently, recognition that the choice of material can direct immune response has led to a range of material-based strategies. Early approaches have attempted to dampen undesirable immune response by creating surfaces that resist non-specific protein adsorption ¹⁷, create entropic barriers to adsorption 18, mimic cell membranes 19 or build super hydrophilic barriers to fouling ²⁰. More recent approaches have attempted to steer immune response by conjugating materials with immune stimulatory enzymes ²¹, or using high throughput screening methods to identify materials that reduce the FBR in non-human primates ^22,23 and those that can modulate immune cell instructive responses in vitro and in murine models ¹⁵. There remains a need for routes to modulate immune responses for materials used in healthcare products, such as biomedical implants. WO 2021/161291 Al and WO 2021/161290 Al disclose microtopography patterns formed from repeated micropillars. WO 2012/097879 Al also provides micropillars by using embossing and photolithography techniques. US 2020/0030124 Al discloses a plurality of textures, e.g. cylinders, arranged in a micropattern. In general, therefore, these disclosures pertain to prismatic objects, i.e. those which project above the surface with straight sides. It is noted that when a master is used that has been made using photolithography, the shapes that can be obtained are generally limited to prismatic features. Summary of the Invention The present inventors have determined that the design of the surface architecture, in terms of the total number, size and shape of micro-scale 3D objects mounted on the surface, allows control of the extent of macrophage attachment and the phenotype of the macrophages that attach to the surface. The present inventors have gone beyond the known approaches, to uncover the way macrophages respond to a range of surface-mounted micro-scale objects of different designs, and composed of three immune-instructive polymer chemistries, by utilising advances in additive manufacturing to combine material chemistry and architectural cues. In the examples detailed herein, two photon polymerisation was used to create an array of complex objects with critical dimensions in the range 5 – 120 µm ^22-28, allowing the inventors to efficiently explore the role of object and material chemistry in directing macrophage behaviour. Unexpectedly, the inventors found that macrophage attachment and phenotype can be tuned. For example, it has been determined that vertex/cone angles should be less than 60° in order to induce significant macrophage attachment to an object; the use of vertex/cone angles of 60° or more reduces macrophage attachment to an object. It has also been determined that some objects, such as tetrahedra, can drastically reduce or even eliminate attachment, depending on their size. The primary mechanism governing these interactions is determined to be caveolae-dependent endocytosis. For macrophage polarisation, material identity dominates over architecture, but can be tuned using appropriate choice of shape to elicit strong cell responses. Therefore, the present invention provides a new and useful teaching regarding the number, size and shape of objects that can be attached to a surface to achieve immune instruction. This approach therefore supplements known approaches of immune instruction based on surface chemistry ^{11, 12, 14, 15, 16, 38}. The present invention can also use 3D micro-scale objects in combination with immune instruction based on surface chemistry. The invention provides, in a first aspect, the use of micro-scale three-dimensional objects on a surface, to influence the extent to which macrophage attachment occurs at the surface and/or the phenotype of macrophage that attaches to the surface. The invention also provides, in a second aspect, a product wherein micro-scale three-dimensional objects are provided on a surface of the product. These objects influence the extent to which macrophage attachment occurs at the surface and the phenotype of macrophage that attaches to the surface. The invention can, in particular, be used to provide a product which is a healthcare implant whereby micro-scale three-dimensional objects are provided on a surface of the implant. These micro-scale objects provide a surface architecture that influences the extent to which macrophage attachment occurs at the surface and/or the phenotype of macrophage that attaches to the surface. For example, they may promote low macrophage attachment at the surface or high macrophage attachment at the surface; and/or may influence the phenotype of macrophage that attaches to the surface towards pro-inflammatory (M1) or towards anti-inflammatory (M2). The skilled person will appreciate that reducing attachment of macrophages may often be desirable, because this is useful in reducing implant rejection. Therefore, once an implant has been implanted in the patient’s body, a surface that reduces the attachment of macrophages will reduce the chance of the implant being rejected by the patient’s body. The skilled person will also appreciate that promoting attachment of macrophages which are anti- inflammatory (M2) macrophages may often be desirable, because this is useful in promoting healing. Therefore, once an implant has been implanted in the patient’s body, a surface that promotes the attachment of anti-inflammatory (M2) macrophages will promote healing following the implant surgery. This in turn may promote acceptance of the implant within the patient’s body. The skilled person will, however, also appreciate that in some embodiments promoting attachment of macrophages which are pro-inflammatory (M1) macrophages can be desirable where there is a therapeutic need to trigger an inflammatory response. In addition, the skilled person will also appreciate that in some embodiments promoting attachment of macrophages which are M0 macrophages, or a balance of M2:M1 macrophages that is approximately 1, can be desirable where there is a need to promote tissue homeostasis. In general, therefore, surfaces are provided which are decorated with architectures to augment the performance of implants. The implants of the invention can be considered as immunomodulatory implants, due to their influence on the amount and phenotype of macrophage that becomes attached. The present invention may be found to be particularly useful in relation to situations where an implant interfaces with soft tissue. When the product of the invention is a healthcare implant, this may usefully be any implant used in healthcare, including coronary stents, hip replacements, glucose sensors, cardiac electrodes, and surgical meshes. It may be a medical implant or a cosmetic implant. It will be appreciated that certain types of implants may be used for medical or cosmetic use; for example, breast implants may be used in a medical setting for breast reconstruction following surgery, e.g. in relation to the treatment of breast cancer, or may be used in cosmetic surgery. The invention also provides, in a third aspect, a method of manufacturing a product wherein micro-scale three-dimensional objects are provided on a surface of the product, the method comprising: . providing the product and then applying the micro-scale three-dimensional objects onto a surface of the product, e.g. by embossing, or injection moulding, or blow moulding, or roll to roll processing, or casting; or . manufacturing the product with the micro-scale three-dimensional objects provided on a surface of the product, e.g. by additive manufacturing or injection moulding. As explained further in this disclosure, and in particular the worked examples, the inventors recognised that in order to design effective immunomodulatory implants, innate immune cell interactions at the surface of biomaterials need to be understood. They used the architectural design freedom of two photon polymerisation to produce arrays of geometrically diverse 3D polymer objects. This revealed the importance of the interplaying roles of architecture and material chemistry in determining human macrophage fate in vitro. This identified key structure-function relationships and design rules assisted by machine learning to build a mechanistic understanding of attachment and polarisation state. The inventors found that object shape, vertex/cone angle and size are all key influencers of attachment, that particular shapes heavily modulate pro- or anti-inflammatory cell polarization and that triangular pyramids can drastically reduce or even eliminate attachment. Caveolae-dependent endocytosis is identified as a principal mechanism by which cells respond to objects with low vertex/cone angles. These design rules pave the way for surfaces decorated with architectures to augment implant performance. Detailed Description of the Invention The present invention uses micro-scale three-dimensional objects on a surface to achieve technical benefits. The size and shape of these objects can be selected to influence the extent to which macrophage attachment occurs at the surface and the phenotype of macrophage that attaches to the surface. The present invention is, in particular, foreseen to provide new and useful products in the healthcare field, specifically healthcare implants. The healthcare implants may be medical or cosmetic. They may be permanent or temporary (non-permanent). The present invention may, in particular, use micro-scale three-dimensional objects that have angled faces, as compared to objects that project above the surface with straight sides (90-degree prismatic shapes). Therefore the use of shapes such as tetrahedra and cones, where there is a vertex/cone angle that can be altered, is beneficial. The angles that the faces come together has been identified by the inventors as important, hence their advantage over 90-degree prismatic shapes. As noted above, triangular pyramids can drastically reduce or even eliminate attachment. The inventors hypothesised that the vertex/cone angle in surface bound objects could influence macrophage attachment as they attempt to engulf objects. This was tested by examination of the vertex/cone or polyhedral angle for the array of polyhedrons. Examining the attachment data for polyhedral samples indicated that objects with vertex angles below 60° showed significantly higher cell attachment than objects with vertex angles above 60°. A large range of attachment was observed at a vertex angle = 60°. By examining the cell positions in the microscopy data, it was also noted that cells preferred vertices to faces, with up to 70% of the cells observed on the vertices in some cases. In one embodiment, the implant is selected from permanent implants, such as artificial heart valves, voice prostheses, prosthetic joints including hip replacements, breast implants, implanted artificial lenses, stents (e. g. coronary stents), permanent surgical meshes, and shunts (e.g. hydrocephalus shunts); and non-permanent implants, such as pacemakers and pacemaker leads, drain tubes, endotracheal or gastrointestinal tubes, temporary or trial prosthetic joints, temporary surgical meshes, surgical pins, guidewires, dental and bone implants such as dental screws, surgical staples, chest drains and peritoneal drains, cannulas, subcutaneous or transcutaneous ports, implanted sensors such as implanted glucose sensors, indwelling catheters and catheter connectors, including catheters for continuous ambulatory dialysis, intraocular lenses and contact lenses. The implant could also be a sustained drug delivery implant device, such as the type implanted subcutaneously, e.g. to deliver hormones for contraception or insulin for diabetes, or such as the type implanted intraocularly, e.g. to deliver steroids for ocular inflammatory disorders. The healthcare product could also be a cell encapsulation device, in particular a product whereby cells are encapsulated and immobilized within a polymeric membrane. The membrane may be semi- permeable, such that the cells can be delivered in vivo. Such a cell encapsulation device may be useful for biomolecule delivery and/or for other regenerative purposes. The micro-scale three-dimensional objects provided on a surface of the cell encapsulation device can influence the extent to which macrophage attachment occurs at the surface and/or the phenotype of macrophage that attaches to the surface. It may, in particular, be that the implant is one which, in use, interfaces with soft tissue. Preferably, at least the surface of the implant that will, in use, form an interface with the soft tissue is provided with the micro-scale three-dimensional objects. The micro-scale three-dimensional objects may be formed from the same material as the product (e.g. implant) or they may be formed from a different material. In one embodiment they are formed from polymeric material, but the use of other materials such as ceramic or metal or alloys is also foreseen. It may be that the body of the product, e.g. implant, is made from the same or different material to the surface. In one embodiment, the body of the product, the surface of the product and the micro-scale three-dimensional objects are all formed from the same material. In another embodiment, the surface of the product and the micro-scale three-dimensional objects are formed from the same material, but the body of the product is formed from a different material. This present invention supplements known approaches of immune instruction based on surface chemistry ^{11, 12, 14, 15, 16, 38}. The present invention can also use 3D micro-scale objects in combination with immune instruction based on surface chemistry. Therefore, materials can be used for the objects and/or the surface that are known to influence the phenotype of macrophage towards M0, M1 or M2 respectively, as desired. These materials will be referred to as M0 materials, M1 materials and M2 materials respectively. The worked examples of the present application describe screening techniques to identify suitable M0 materials, M1 materials and M2 materials. These can be used by the skilled person to identify materials for the objects and/or the surface that add to or enhance the immune instruction achieved by the present invention. Suitable but non-limiting materials identified in this regard are: poly(glycerol propoxylate triacrylate) (GPOTA) = M0 material; poly(1,4 butanediol diacrylate) (BDDA) = M1 material; and poly(glycerol 1,3 –diglycerolate diacrylate) (GDGDA) = M2 material. The skilled person can also use the teachings of the art to identify polymers that can be used as M0, M1 or M2 materials, to influence the phenotype of macrophage towards M0, M1 or M2 respectively, as desired. See, for example, references 15, 38 and 51. In one embodiment the M0, M1 or M2 materials are polymers. However, other materials with the ability to modulate macrophage phenotype include alginate derivatives (see reference 52) and zwitterionic hydrogels (see reference 53), and these can also be contemplated for use. In general: M0 materials include: poly(glycerol propoxylate triacrylate) (GPOTA); and poly(benzyl acrylate). M1 materials include: poly(1,4 butanediol diacrylate) (BDDA); poly(isobutyl acrylate); poly(hydroxypropyl acrylate); and poly(ethylene glycol phenyl ether methacrylate). Further examples are poly(t-butylcyclohexyl methacrylate) and copolymers of cyclohexyl methacrylate and dimethylamino-ethyl methacrylate, e.g. in a molar ratio of 2:1 M2 materials include: poly(glycerol 1,3–diglycerolate diacrylate) (GDGDA); poly-N- [tris(hydroxymethyl)methyl] acrylamide; poly(methacrylamide); and poly(tridecafluorooctyl acrylate). Further examples are copolymers of phenyl methacrylate and isodecyl methacrylate, e.g. in a molar ratio of 2:1, and copolymers of cyclohexyl methacrylate and isodecyl methacrylate e.g. in a molar ratio of 2:1. In one embodiment, the M0, M1 or M2 material respectively is according to the above list of materials. The objects provided on the surface are micro-scale. This term may be used interchangeably with micro- sized, micron-sized and micron-scale. For example, the maximum dimension (maximum length in any of the X, Y and Z axis) of the 3D objects may each independently be at least 1 µm and up to 1000 µm. In one embodiment, the maximum dimension for each object is in the range of from 1 µm to 500 µm, or from 1 µm to 300 µm, or from 1 µm to 200 µm, or from 1 µm to 150 µm. In one embodiment, the maximum dimension for each object is in the range of from 5 µm to 120 µm. The skilled person will appreciate that the size of the micro-scale objects is controlled during manufacture, e.g., by the design file used for additive manufacturing (3D printing) or by the mould used for injection moulding. Once the product of the invention has been manufactured, scanning electron microscopy (SEM) can be used to verify the size of the micro-scale objects. In one embodiment, the base diameter of the 3D objects may each independently be in the range of at least 1 µm and up to 1000 µm. In one embodiment, the base diameter for each object is in the range of from 1 µm to 500 µm, or from 1 µm to 300 µm, or from 1 µm to 200 µm, or from 1 µm to 150 µm. In one embodiment, the base diameter for each object is in the range of from 5 µm to 120 µm. The base of an object is the bottom region or face of the object that is provided on, and lies on, the surface (e.g. the surface of the implant) that is decorated with the objects. The base diameter is the diameter of this base. The objects may have flat (planar) surfaces and/or may have curved surfaces. Where the objects have curved surfaces, objects with convex surfaces and/or objects with concave surfaces can be contemplated. In one embodiment, the objects have from 1 to 24 faces, such as from 2 to 24 faces or from 3 to 20 faces or from 4 to 20 faces. It may be that the objects are selected from the group consisting of: simple polyhedrons (e.g. cubes, icosahedrons, dodecahedrons, octahedrons and tetrahedrons), stellate polyhedrons such as stellate dodecahedrons, prisms, pillars (e.g. cylinders), cones, prolate spheres, prismatic ovals, hemispheres (which may be decorated with spikes), and grooved hosohedrons. In general, any of the objects may be decorated with spikes or may be provided with non-decorated surfaces. When the objects are polyhedrons, they may be regular or irregular. They may, for example, have from 4 to 24 faces, such as from 4 to 20 faces. For example, cubes, icosahedrons, dodecahedrons, octahedrons and tetrahedrons can be mentioned. In one embodiment, the object is selected from icosahedrons, dodecahedrons, octahedrons and tetrahedrons. When the objects are prisms, they may have a regular or irregular polygon as their cross section. The polygon may, for example, have from 3 to 12 sides, such as from 4 to 8 sides. For example, triangular prisms, rectangular prisms, square prisms, and hexagonal prisms can be mentioned. In one embodiment, the objects are selected from the group consisting of: pillars (e.g. cylinders), polyhedrons (e.g. with from 4 to 20 faces) and hemispheres. In one embodiment, the objects are selected from the group consisting of pillars: (e.g. cylinders), tetrahedrons, cubes, octahedrons, dodecahedrons, icosahedrons and hemispheres. In one embodiment the object is selected from tetrahedrons, octahedrons, icosahedrons, dodecahedrons, hemispheres and cones. In one embodiment, one or more of the following strategies are used to reduce the attachment of macrophages to the surface: . addition of micro-scale three-dimensional objects which are tetrahedra with base diameter greater than 45 µm; . addition of micro-scale three-dimensional objects which are pillars (e.g. cylinders) with base diameter greater than 45 µm; . addition of micro-scale three-dimensional objects which have a low aspect ratio, e.g. cylinders; . addition of micro-scale three-dimensional objects which have a vertex/cone angle of 60° or more. Tetrahedra have been found to have a noticeable influence on reducing macrophage attachment when their base diameter is greater than 45 µm, especially greater than 60 µm, preferably greater than 80 µm, and in particular greater than 100 µm. Highly effective results have been shown for tetrahedra with 120 µm base diameter. The tetrahedra have only one vertex extending above the surface. The vertex angle should be 60° or more in order to reduce macrophage attachment to the object. Where the tetrahedra are regular tetrahedra, the vertex angle is 60°, and therefore regular tetrahedra can beneficially be chosen for use. Pillars (e.g. cylinders) have been found to have a noticeable influence on reducing macrophage attachment when their base diameter is greater than 45 µm, especially greater than 60 µm, preferably greater than 80 µm, and in particular greater than 100 µm. Highly effective results have been shown for pillars with 120 µm base diameter. Pillars can be provided with a range of cross-sectional shapes which are curved closed shapes, e.g. circular or ellipse. For pillars, there has been observed increased cell attachment as the object became less circular. Therefore, to achieve reduced attachment, pillars with a circular cross section are preferred (cylinders). In one embodiment, one or more of the following strategies is used to increase the attachment of macrophages to the surface: . addition of micro-scale three-dimensional objects which have a vertex/cone angle less than 60°; . addition of micro-scale three-dimensional objects which have a base diameter that is 45 µm or less; . addition of micro-scale three-dimensional objects which are spiked, e.g. spiked hemispheres; . addition of micro-scale three-dimensional objects which have a high aspect ratio, e.g. cones and prismatic ovals. Increasing the total number of micro-scale three-dimensional objects which meet any one of more of the above criteria will also increase the attachment of macrophages to the surface. In one embodiment, 50% or more of the area of the surface is covered with micro-scale three-dimensional objects, such as 60% or more, or 70% or more, for example 80% or more, or 90% or more. In one embodiment, the entire surface is covered with micro-scale three-dimensional objects. Objects been found to have a noticeable influence on increasing macrophage attachment when their base diameter is 45 µm or less, especially 40 µm or less, preferably 30 µm or less, and in particular 25 µm or less. Highly effective results in terms of increased attachment have been shown for hemispheres, cones and regular octahedrons, icosahedrons and dodecahedrons with a 15 µm base diameter, especially octahedrons and hemispheres with a 15 µm base diameter. In one embodiment the object is selected from octahedrons, icosahedrons, dodecahedrons, hemispheres and cones. In one embodiment the object is selected from octahedrons and hemispheres. Cones showed significantly higher attachment than equivalent flat surfaces for all materials, with greater attachment to 15 µm base diameter cones compared to 45 µm diameter cones. Significant reduction in attachment was observed with increasing cone angle; therefore, the cone angle should be less than 60°. Similarly, for stellate dodecahedrons, attachment is more suppressed with increasing object size from 15 µm to 45 µm. Interestingly, the present invention has shown that objects with shapes that possess low vertex/cone angles leads to high macrophage attachment, independent of the material chemistry of the surface. The presence of spikes on the surface increased cell attachment per unit area by as much as 3-fold. The length of the spikes tested did not influence attachment, suggesting that the tip of the spike (or vertex) itself is the most important attribute for increased attachment. The linear model formed by the inventors has revealed the importance of the following as positive drivers of macrophage attachment: . the number of objects, e.g. the number of cylinders/pillars – more objects gives higher attachment; . the size of objects – the smaller the size of the objects, the higher the attachment (and the base diameter must be 45 µm or less); . the number of spikes per object - more spikes gives higher attachment; . the vertex/cone angle – a lower angle gives higher attachment (and the angle must be less than 60°); . the aspect ratio - increases in the aspect ratio give higher attachment (e.g. oval cross section rather than circular). In one embodiment, the following strategy is used to increase the M2/M1 phenotype of macrophages attached to the surface: . addition of micro-scale three-dimensional objects which have a base diameter that is 45 µm or less and which have more than 6 vertices. Objects been found to have a noticeable influence on increasing the M2/M1 phenotype when they have more than 6 vertices, e.g.8 or more vertices, and when their base diameter is 45 µm or less, especially 40 µm or less, preferably 30 µm or less, and in particular 25 µm or less. Highly effective results in terms of increased M2/M1 phenotype have been shown for regular octahedrons, icosahedrons and dodecahedrons with a 15 µm base diameter. This effect is in particular seen when the objects are formed from M2 material (e.g. GDGDA). In one embodiment, the following strategy is used to decrease the M2/M1 phenotype of macrophages attached to the surface: . addition of micro-scale three-dimensional objects which are spiked, e.g. spiked hemispheres. Objects been found to have a noticeable influence on decreasing the M2/M1 phenotype when they are provided with spikes, e.g. spikes with a length of from 5 to 25 µm or from 8 to 20 µm, especially from 9 to 18 µm. In one embodiment, hemispheres provided with spikes having a length of 9 µm or more have been shown to achieve attachment of macrophages with a low M2/M1 ratio, i.e. with an increased M1 phenotype. In one embodiment, one or more of the following criteria is controlled in order to affect the extent of macrophage attachment: i. Number of Objects per Array ii. Polyhedral Dihedral Angle (di-interplanar angle) iii. Object Elongation iv. Height of object (µm) v. Size of Spikes (µm) vi. Number of Pillars (e.g. Cylinders) vii. Object Sphericity viii. Vertex/cone angle ix. Number of Spikes per Object x. Space Between Spikes (µm) In one embodiment, one or more of the following criteria is controlled in order to affect the polarisation of the attached macrophages: I. Space Between Spikes (µm) II. Number of Objects per Array III. Object Surface Area (µm2) IV. Use of GDGDA V. Total Number of Faces per Object VI. Object Volume (µm3) VII. Height of object (µm) VIII. Use of BDDA IX. Total Intersected Area (µm2) In one embodiment, the following strategy is used to control the phenotype of macrophages that attach to the surface:

The following table sets out non-limiting examples of polymers that can be used to manufacture the surface-mounted 3D shapes:

GPOTA may be selected to influence the phenotype of macrophage towards M0. It is therefore an example of an M0 material. BDDA may be selected to influence the phenotype of macrophage towards M1. It is therefore an example of an M1 material. GDGDA may be selected to influence the phenotype of macrophage towards M2. It is therefore an example of an M2 material. These base monomers can be used alone or can be combined with one or more further monomers. For example, these base monomers may be combined, where necessary, with pentaerythritol triacrylate (PETA). Print optimisation procedures may also be carried out to achieve reliable print fidelity. Therefore, for example, the M0 material may be 100% GPOTA, the M1 material may be a blend of BDDA and PETA (60:40 w/w), and the M2 material may be a blend of GDGDA and PETA (80:20 w/w). Without being bound by theory, it is believed that the extent of attachment, and the composite consideration of macrophage polarisation and attachment, are influenced by the criteria set out in the tables below with the stated weighting. Therefore, one or more of these criteria can be used to achieve the desired extent of attachment and/or the macrophage polarisation.

Therefore, in one embodiment, the invention provides the use of micro-scale three-dimensional objects on a surface, to influence the extent to which macrophage attachment occurs at the surface wherein one or more of the following criteria is controlled to in turn control the extent to which macrophage attachment occurs at the surface: number of objects per array; polyhedral dihedral angle (di-interplanar angle); object elongation; height (µm); size of spikes (µm); number of pillars (e.g. cylinders); object sphericity; vertex/cone angle; number of spikes per object space between spikes (µm). In another embodiment, the invention provides the use of micro-scale three-dimensional objects on a surface, to influence the extent to which macrophage attachment occurs at the surface and the phenotype of macrophage that attaches to the surface, wherein one or more of the following criteria is controlled to in turn control the extent to which macrophage attachment occurs at the surface and the phenotype of macrophage that attaches to the surface: space between spikes (µm); number of objects per array; object surface area (µm2); use of GDGDA; total number of faces object volume (µm3); height (µm); use of BDDA; total intersected area (µm2). The invention is described in detail with regard to the use of additive manufacturing to make the products with the 3D shapes on the surface; however, the invention is not limited to this method of manufacture. The skilled person will be able to appreciate that other manufacturing techniques can be used, e.g. embossing or roll to roll processing can be used to apply the 3D shapes to the surface of a product that has already been manufactured, or injection moulding could be used to manufacture a product with the 3D shapes on the surface. Both additive manufacturing and moulding have been successfully tested by the inventors. Brief description of the drawings: Figure 1: Design and fabrication of the ChemoArchiChip. (a) schematic of the screening process: I: Materials selection, II: Additive Manufacture, III: Cell seeding, IV: Biofunctional assay. (b) Representative SEM of polyhedrons (in three different sizes; 120, 45 and 15 µm diameter; top, middle and lower panel, respectively) evaluated for cell attachment (left to right; cylinder, tetrahedron, cube, octahedron, dodecahedron, icosahedron and hemisphere). (c) Bar charts of macrophage attachment to prismatic ovals (used to investigate aspect ratio). Data expressed as mean (± standard deviation) number of cells per unit area (µm2 x1000) of each object. Only cells associated with 3D objects were quantified using segmentation of fluorescence data (see Methods). Green bars represent GPOTA(M0), blue bars represent BDDA (M1) substrate materials and orange bars represent GDGDA(M2). (d) Bar chart of macrophage attachment to polyhedrons (object diameter = 15 µm), (e) object diameter = 120 µm; Inset SEM of octahedron from top view. The solid horizontal line indicates the attachment of the flat, planar area. Data represents 5 biologically independent donors and a total of 9 technical repeats (**** <0.0001, ** <0.01). (f) Macrophage attachment per object vs the object size descriptor for each material and all objects, a non-linear best fit curve was fitted; (g) Rank order SHapley Additive exPlanations (SHAP) analysis of linear modelling to determine specific physical features which modulate macrophage attachment to 3D objects. Scale bar 100 µm Figure 2: The role of micro-sized objects on surfaces in controlling macrophage attachment. (a) surface area normalised cell attachment versus vertex/cone angles, separated by material and base diameter of all polyhedrons and (b) percentage of cells associated with vertices per number of vertices versus vertex/cone angle of polyhedrons. Data expressed as mean number of cells per unit area for each individual object (only cells associated with 3D objects were quantified). Green bars represent GPOTA (M0), blue bars represent BDDA (M1) and orange bars represent GDGDA (M2) substrate materials. (c) SEM image of macrophages cultured on a spiked hemisphere (base diameter 120 µm; spike length 9 µm) and (d) quantification of cell attachment as per (b) ‘no spike’ indicates a smooth hemisphere. Data represents 5 biologically independent donors and a total of 9 technical repeats. (e) Higher magnification SEM of macrophages cultured on spiked hemisphere in (c) and (f) Elucidation of the mechanism of the macrophage attachment to spiked hemispheres. Macrophages were pre-treated with the indicated inhibitors for 0.5 h and then cultured on surfaces for a further 72 hrs. Bars indicate mean (± standard deviation) of cell attachment per individual objects. N = 4 biologically independent donors (with a minimum 4 technical repeats per donor) (**** <0.0001, *** <0.001). Figure 3: Controlling macrophage phenotype using 3D object and surface chemistry Polarisation status of macrophages cultured on ChemoArchiChips for 6 days were quantified using surface markers. (a), (b) and (c) 3D view of prolate spheroids (diameter 15 µm, height 15 µm) composed of BDDA, GPOTA and GDGDA respectively, with macrophages expressing calprotectin (M1 marker; red) and mannose receptor (M2 marker; yellow). (d) Rank order SHAP analysis of descriptors that affect changes in macrophage phenotype on all substrates. (e) Polarisation state of macrophages cultured on spiked hemispheres. Data expressed as M2/M1 ratio determined from mean cell fluorescence intensity per cell (± standard deviation). Only cells associated with 3D objects were quantified. N = 5 biologically independent donors. Hatched bar indicates the flat planar area on the array and the horizontal line indicates the value for exogenous cytokine polarisation carried out in parallel. (f), (g) and (h) Top-down view of spiked hemispheres with macrophages expressing calprotectin (M1 marker; red) and mannose receptor (M2 marker; yellow). Scale bar 100 µm. Figure 4: Schematic summarising the design map for surface architecture and material chemistry driven macrophage attachment and phenotype. The figure shows representative shaped objects, classified and shown as large, medium or small, and denoted with four possible colours, where green represents GPOTA (M0), blue represents BDDA (M1) and orange represents GDGDA (M2) substrate materials, and use of grey indicates that all of the three explored materials express the same shown behaviour. Figure 5: Identification of BDDA(M1), GPOTA(M0) and GDGDA (M2) polymers. (a) Screening of polymer library formed using pin printing of monomers followed by UV curing equivalent to that employed in reference 15. M0, M1 and M2 polarising materials identified. Calprotectin and Mannose Receptor (MR) MF (M2/M1) ratios were averaged and analysed using Partition Around Medoids (PAM) clustering algorithm. Prior to cluster analysis, average M2/M1 ratios across 7 donors was calculated for each polymer. Based on their average M2/M1 ratios, polymers were grouped into three clusters: Low polarising (M1), medium (naïve) and high (M2 polarising) clusters. Bar chart of macrophage polarisation after 6-day culture on flat printed polymer film. Data expressed as M2/M1 ratio determined from mean cell fluorescence intensity per cell (+ standard deviation). N = 5 biologically independent donors. (b) Representative greyscale images of macrophage polarisation on different 2PP printed flat surface chemistries using calprotectin (M1 marker) and mannose receptor (M2 marker) plus nuclear stain. GDGDA samples had a tiling effect due to fluorescence from the material. The addition of PETA is not detrimental to macrophage phenotype, as polarisation still points to M1 phenotype (for BDDA) and to M2 (for GDGDA). Scale bar = 100µm. Figure 6: Multiwell Unit (a) Sample holder with 10 multiwell coverslips unit. (b) Single coverslip with 9 wells that can hold 9 ink formulation at a time. (c) Arrays of different structures in different size (d) test printed cubes. (e) test printed hemisphere with spikes. (f) Table of monomers used and optimised printing parameters. Prior polymer library screening analysis has provided this study with three monomers that modulate macrophages (GPOTA (M0), GDGDA (M2) and BDDA (M1)). The monomers were then mixed with different photon initiator ratios (1wt% -5wt%) to determine optimal photoinitiator concentrations. It was found that BDDA (M1) monomer cannot be printed without further reformulation. Therefore, PETA (pentaerythritol triacrylate) was added into BDDA (M1) and GDGDA (M2) in varying concentrations to ensure printability. A multiwell unit was then designed to fast-screen large numbers of chemistries, shown in Fig.1. A standard sample holder of Nanoscribe can hold up to 10 coverslips at a time. A parafilm with 9 wells was applied to a coverslip, enabling a high throughput screen of ink formulations without the need to take out and reload the holder. A digital cutter was used to cut the parafilm and the parafilm-covered coverslips were left on the hotplate at 50oC for 10 minutes. Each well can be loaded with one ink formulation and the whole design is able to screen 90 materials in one run. Figure 7: Printing parameters (a) Printing parameter screening for PETA in terms of laser power and scanning speed. (b) Processing parameter screening in terms of size. A number of printing parameters have to be optimized before any complex structures can be fabricated, for instance, scanning speed, laser power, slicing distance, hatching distance, hatching angle, etc. For each given ink formulation, several printing parameter sweeps were performed. In (a) a printing parameter sweep of laser power and scanning speed were carried out on PETA (PI 2wt%). The laser power increases from 5mW to 50mW and the scanning speed was adjusted from 7000 µm/s to 13000 µm/s. A too high laser power can result in the structure burning while insufficient energy input will result in poor resolution feature. After printing parameters were optimized, a processing parameter screening was then introduced to check whether the physical properties of the topography will have any effect on the optimized printing parameter. In (b) cones were printed in different sizes with the optimized printing parameter to check whether optimized printing parameters are valid in all size variations. Figure 8: Design and fabrication of the ChemoArchiChip. (a) chemical structures for all monomers used for ChemoArchiChip fabrication (see Fig 6f for monomer chemical names and details) and (b) SEM overview for ChemoArchiChip showing the layout of structures and their distribution over the chip, ready for biological screening (GPOTA(M0)) (scale bar = 2 mm). Figure 9: Surface chemistry of complex 3D objects by unsupervised machine learning. Non-negative matrix factorisation (NMF) was utilised as an unsupervised machine learning method. Schematics showing ToF-SIMS measurements of (a) schematic of data matrix and creation of non-negative matrix factorisation (NMF) model, (b) characteristic signal from NMF endmembers for flat samples of pre- treated substrate (grey), GPOTA (M0) (blue), BDDA (M1) (purple) and GDGDA (M2) (green), (c) Application of model to mapping data of complex objects. Intensities per pixel are presented for each compound with respective colours, scale bar = 50 µm. Evaluation of surface cross-contamination in a multi-material ChemoArchiChip by (d) comparison between samples printed isolated or on the same substrate. (e) PCA loadings and (f) scores. Figure 10: (a) SEM images of cubes printed with GPOTA, BDDA and GDGDA for Raman Spectroscopy. (b) Degree of conversion calculated from Raman spectra with their standard deviation for GPOTA, GDGDA and BDDA. (c) Raman spectroscopy spectra of GPOTA (M0), BDDA (M1) and GDGDA (M2) before and after polymerization. Figure 11: AFM determined surface modulus determined in dry and wet conditions to simulate the surface sensed by attached cells. (a) Bar charts of the surface modulus of printed polymer films in wet condition. Data expressed as mean (± standard deviation) surface modulus as determined from 6 technical replicates per polymer film. Unpaired t-test compared to the respective polymer. (b) Table of surface modulus values in dry and wet conditions as used in (a). Figure 12: (a) Scanning electron micrograph of the polyhedron object family in three different sizes; 15, 45 and 120 μm, top, middle and bottom objects respectively (scale bar = 500 μm). Medium panels show computer generated designs for the polyhedron objects are described from left to right as (vertex angles in brackets) (b) hemisphere, (c) icosahedron (60°), (d) dodecahedron (108°), (e) octahedron (60°), (f) cube (90°), (g) tetrahedron (60°) and (h) cylinder. The lower panel shows bar charts of cell attachment to (i) 45μm polyhedrons and (j) 120μm polyhedrons; Data expressed as mean (± standard deviation) number of cells per unit area (1000 µm2) per object. Green bars represent GPOTA (M0), blue bars represent BDDA (M1) and orange bars represent GDGDA (M2) substrate materials. The solid horizontal line indicates the attachment to flat polymer chemistry (averaged from all 3 chemistries). Data represents 5 biologically independent donors and a total of 9 technical repeats. Statistical analysis in (i) and (j) is One Way ANOVA with Dunnett’s multiple comparison test compared to the respective flat area (**** <0.0001, ** <0.001, * <0.05). Figure 13: Representative scanning electron micrograph of the prismatic oval object used to test aspect ratio. The design was based on a cylinder in four different sizes with the minor axis adjusted to create defined elliptical objects. Figure 14: Bar charts of macrophage attachment to (a) cones with a base diameter of 15 or 45 μm and three different angles of slope determined by object height. Data expressed as mean (± 1 standard deviation) number of cells per unit area (1000µm2) per object. (b) Representative scanning electron micrograph of the stellate dodecahedron and (b) cones (scale bar = 200μm). Stellate dodecahedrons were varied in size from 20 – 60 μm and cones had a base diameter of 15 or 45 μm and three different angles of slope determined by object height. Lower panel is zoom image of stellate dodecahedron. Scale bar = 10 μm. (c) bar charts of macrophage attachment to stellate dodecahedrons. Green bars represent GPOTA (M0), blue bars represent BDDA (M1) and orange bars represent GDGDA (M2) substrate materials. In (a) and (c) the solid horizontal line indicates the attachment to flat polymer chemistry (averaged from all 3 chemistries). Data represents 5 biologically independent donors and a total of 9 technical repeats. Statistical analysis in (b)-(e) is One Way ANOVA with Dunnetts multiple comparison test compared to the respective flat area (**** <0.0001, ** <0.001, * <0.05). Figure 15: (a) Representative scanning electron micrograph of the prolate spheroid family in the three different sizes (scale bar = 200µm). (b) Schematic as well as exact base diameter and height of the cross section of the varying prolate spheres as they increase in height. (c) prolate spheres; base diameter 15 µm and (e) prolate spheres; base diameter 45 µm. Data expressed as mean (± standard deviation) number of cells per unit area (µm2 x1000) per object. Green bars represent GPOTA(M0), blue bars represent BDDA(M1) and orange bars represent GDGDA (M2) substrate materials. On (c)-(d) the solid horizontal line indicates the attachment to flat polymer chemistry (averaged from all 3 chemistries). Data represents 5 biologically independent donors and a total of 9 technical repeats. Statistical analysis in (c)-(d) is One Way ANOVA with Dunnetts multiple comparison test compared to the respective flat area (**** <0.0001, ** <0.001, * <0.05). Figure 16: (a) Representative scanning electron micrograph of the spiked hemisphere with different base diameters of (a) 120 (b) 45 and (c) 15 µm (scale bar = 50 µm). Spike angle is 27 degrees for all spikes. (d) macrophage attachment to spiked hemispheres (base diameter 120 μm) and (e) spiked hemispheres (base diameter 45 μm). Data expressed as cell attachment per individual object. Green bars represent GPOTA (M0), blue bars represent BDDA (M1) and orange represents GDGDA (M2) substrate material. Data determined from 5 biologically independent donors and a total of 9 technical repeats. One Way ANOVA with Dunnetts multiple comparison test compared to the respective flat area (**** <0.0001, ** <0.001, * <0.05). Figure 17: (a) Representative scanning electron micrograph of the hosahedron object family and variations in groove number per object (0-14) (scale bar = 200 µm). (b) Representative SEM image of macrophages cultured on a hosohedron (with 10 grooves) and (c) bar chart of quantification of cell attachment to hosohedron with varying numbers of grooves on the surface. Data expressed as mean number of cells (+ standard deviation) per unit area for each individual object (only cells associated with 3D objects were quantified). Green bars represent GPOTA (M0), blue bars represent BDDA (M1) and orange bars represent GDGDA (M2) substrate materials. Figure 18: Multiple linear regression with expectation maximisation results for average attachment to all objects (a) Scatter plot of predicted values compared to measured values; and (b) Linear regression model performance metric results for macrophage attachment. Object descriptors used in this model are described in Table S1. Figure 19: Flat surface attachment. (a) Green bars represent GPOTA (M0), blue bars represent BDDA (M1), and orange represents GDGDA (M2) substrate material. Data determined from 5 biologically independent donors and a total of 9 technical repeats. One Way ANOVA with Dunnetts multiple comparison test compared to the respective flat area (**** <0.0001, ** <0.001, * <0.05). (b) Pearson correlation of donor – donor variation of attachment across 5 biologically independent samples. Correlation coefficient expressed as heatmap; blue to yellow (0.86 – 1; min – max.) Figure 20: Inhibition of macrophage attachment to 3D geometries. Bar charts of cell attachment to (a) spiked hemispheres (base diameter 120µm; spike length 9.39µm) (b) spiked hemispheres (base diameter 45 µm; 9.39µm) (c) stellate dodecahedron (object diameter = 20 µm) (d) cones (base diameter 15 µm; cone angle 60 degrees) and (e) prismatic oval (major axis = 10 µm/minor axis = 5 µm). Macrophages were pre-treated with the indicated inhibitors for 0.5 h and cultured for a further 72 hrs. Data expressed as mean cell attachment (± standard deviation) per individual object. n = 4 biologically independent donors (with a minimum 4 technical repeats per donor) (**** <0.0001, *** <0.001). Figure 21: DMSO control on effect on macrophage viability on TCP. Representative images of Calcein- AM/Ethidium homodimer-1 stained macrophages in untreated, triton X-100 and DMSO treated condition to show DMSO concentration used in inhibitor dilution does not kill macrophages. Figure 22: Macrophage viability after inhibitor treatment on TCP. Representative images of Calcein- AM/Ethidium homodimer-1 stained macrophages after being pre-treated with the mechanism inhibitors. Figure 23: Categories of objects investigated and their synergistic (chemistry/phenotype) macrophage responses. Figure 24: Random Forest regression results for the composite variable (Log M2:M1 × Attachment) for all 3 polymers using gradient boosting regression: (a) Scatter plot for the measured against predicted values; and (b) Regression performance metric results, (c) descriptor importance study ranking the most important descriptors to the model outcome using shap values. Figure 25: Comparison of macrophage phenotype by exogenous cytokine stimulation. (a) Bar chart of macrophage polarisation status after 6-day culture on tissue culture plastic. Macrophages stimulated using cytokines (M1; IFN-γ and GM-CSF, M0; M-CSF and M2; IL-4 and M-CSF). Data expressed as M2/M1 ratio determined from mean cell fluorescence intensity per cell (± standard deviation). N = 5 biologically independent donors. (b) Representative images of macrophage polarisation on different surface chemistries using calprotectin (M1 marker; grey) and mannose receptor (M2 marker; green) plus nuclear stain (magenta). Scale bar = 30µm Figure 26: M2/M1 ratios of macrophages cultured on different object shapes and materials. Polarisation status of macrophages cultured on ChemoArchiChips for 6 days were quantified using surface markers. Green bars represent GPOTA (M0), blue bars represent BDDA (M1) substrate materials and orange bars represent GDGDA (M2). (a) flat, (b) stellate dodecahedron, (c) spiked hemispheres, (d) cones, (e) grooved hosahedrons, (f) prismatic ovals, (g) small polyhedrons, (h) medium polyhedrons, (i) large polyhedrons, (j) small prolate spheres (15μm) and (k) medium prolate spheres (45μm). Cells were stained with macrophages expressing calprotectin (M1 marker) and mannose receptor (M2 marker), respectively. Data expressed as M2/M1 ratio determined from mean cell fluorescence intensity per cell (± standard deviation). Only cells associated with 3D objects were quantified. N = 5 biologically independent donors. Hatched bar indicates the flat planar area on the array and the horizontal line indicates the value for exogenous cytokine polarisation carried out in parallel. Examples General approach: Design and fabrication To achieve structures of relevance to macrophage cell instruction, photocurable monomers were selected for manufacture with two photon polymerisation (2PP) (Fig.1a; Methods) from a high throughput screen of flat homopolymers in microarray format that identified polymers that modulate macrophage phenotype (Fig. 5). Those identified for 2PP were BDDA (1,4 butanediol diacrylate) for ‘M1’: pro- inflammatory, polymer GPOTA (glycerol propoxylate triacrylate) for ‘M0’: immunologically naïve and polymer GDGDA (glycerol 1,3-diglycerolate diacrylate) for ‘M2’: anti-inflammatory. These base monomers were then reformulated by being combined, where necessary, with pentaerythritol triacrylate (PETA), along with a print optimisation procedure to achieve reliable print fidelity (Fig.6 and 7). This resulted in three formulations consisting of GPOTA (M0), a blend of BDDA and PETA (60:40 w/w) referred to as BDDA (M1), and a blend of GDGDA and PETA (80:20 w/w) referred to as GDGDA (M2) (Fig 8). The surface chemistry was confirmed to match that of the intended monomers using time of flight secondary ion mass spectrometry (Fig.9). The addition of PETA as a minor component was not observed to have a significant effect on macrophage polarisation (Fig.5b). Raman spectra showed high level of conversions consistent with polymerisation of di and tri acrylates (Figs.10). AFM experiments additionally determined similar surface modulus for GPOTA (M0) and GDGDA (M2), with BDDA (M1) being softer (Fig.11). Macrophage attachment to 3D objects Topographical modulation of macrophage behaviour is well established on flat surfaces12,24,25 and for spherical and ellipsoid particles13,16. To determine the effect of specific 3D objects at a surface a systematic study of the design space was performed using mathematically describable geometries, generating a rich dataset from which relationships can be mined. This used simple polyhedrons (cubes, icosa-, dodeca-, octa-, and tetrahedron), cylinders, prismatic ovals, cones, prolate spheres, stellate dodecahedrons, hemispheres decorated with spikes and grooved hosohedrons (Figs.12-17). Parameters were varied that determine the object, including heights, base diameters and side lengths, aspect ratios and vertex/cone angles. The cell response to this library of objects was examined by culturing human monocytes on ChemoArchiChips for six days, measuring their attachment to objects, and characterising the monocyte differentiation into macrophages by their polarisation state. Automated confocal Z-stack image acquisition and 3D image analysis protocols were developed to identify and count the cells in contact with the objects. The robustness of donor-donor responses was tested via correlation of attachment data across all 5 donors, showing a minimum r value of 0.86 (Fig. 22b), with flat printed areas all showing similar levels of attachment (Fig.22). The importance of aspect ratio and vertices in controlling macrophage attachment Using the control afforded by the 2PP fabrication process it was possible to explore the influence of subtle changes in object architecture. For pillars, it was noted that the circularity of a series of prismatic ovals (Fig.1b) for which the aspect ratio was systematically varied from circular to oval at a fixed pillar height, increased cell attachment as the object became less circular and as the object minor axis diameter decreased from 80 µm to 10 µm (Fig. 1c). This increased attachment to high aspect ratio objects is consistent with earlier studies of free-floating particles26 that indicated that the angle of the tangent to the particle surface at the cell-material interface is key to the phagocytic outcome. Cell attachment was greatest on octahedrons and hemispheres (all 15 µm diameter, Fig.1d). Across all materials the octahedrons exhibited significantly greater attachment compared to the flat controls and the other objects, with the hemisphere being the second highest (Fig. 1d-e). Plotting macrophage attachment against base diameter for all objects revealed a general preference for smaller objects (Fig. 1f). The inventors hypothesised that the vertex/cone angle in surface bound objects could influence macrophage attachment as they attempt to engulf objects 23,33. This was tested by examination of the vertex/cone or polyhedral angle for the array of polyhedrons (Fig. 1d-e, Table S3). Examining the attachment data for polyhedral samples plotted in Fig.2a indicates that objects with vertex angles below 60° showed significantly higher cell attachment than objects with vertex angles above 60° (Fig.2a). A large range of attachment was observed at a vertex angle = 60°. By examining the cell positions in the microscopy data, also noted that cells preferred vertices to faces, with up to 70% of the cells observed on the vertices in some cases (Fig. 2b). This critical angle is similar to the findings of Champion et al who determined 45° as a threshold for phagocytosis of ellipsoid microparticles23. Interestingly, the largest tetrahedra (with 120 µm base diameter) with only one vertex (angle 60°) eliminated cell attachment for all polymers (Fig. 1e), although the effect was not seen for the 45 µm version of these triangular pyramids (Fig. 11i). Tetrahedron decorated surfaces might therefore be a route to reducing macrophage attachment for implants. Hemispheres attracted similar levels of attachment compared to the flat surfaces for all three polymers, suggesting that they were indistinguishable to the macrophages at the scales employed. Attachment to prolate spheres with varying base diameter and increasing height was raised on the smaller sizes, while larger objects had similar attachment to flat surfaces (Fig.14). Cones showed significantly higher attachment than equivalent flat surfaces for all materials, with greater attachment to 15 µm base diameter cones compared to 45 µm diameter cones. Significant reduction in attachment was observed with increasing cone angle, consistent with tetrahedra (Fig. 2a and 13a), although it was not eliminated, most likely due to the smaller size of the cones compared to the 120 µm base tetrahedra. Similarly, for stellate dodecahedrons attachment is more suppressed with increasing object size from 15 µm, to 45 µm and 120 µm (Fig.13c). Macrophage attachment to more complex 3D geometries Spheres were printed with grooves (hosohedron) to test whether cell confinement and contact guidance observations on flat substrates would translate to 3D environments (Fig. 2a and 3b). The number of grooves (0-14 grooves per structure & 10 µm groove diameter) in a 3D hemispherical hosohedron was sequentially increased across an array of hemispheres and macrophage attachment examined. The presence of grooves in these objects did not increase cell attachment for GPOTA (M0) and BDDA (M1), but a significant increase in attachment was observed for GDGDA (M2) hosohedrons (Fig.16). Notably, in contrast to literature reports of 2D grooves, contact guidance was not observed along the grooved hemispheres

This suggests differences of cellular responses in 3D likely related to the active cell migration processes 29. The identification of the importance of high aspect ratio shaped objects such as cones, and prismatic ovals, prompted the inventors to investigate the addition of spikes to the hemispheres, which already exhibited a high cell attachment. The inventors developed a range of spiked hemispheres with variation in base diameter and spike length present on the surface (Fig.15). Scanning electron microscopy revealed intimate macrophage attachment with the spiked surfaces with significant cytoskeletal changes and remodelling of cell membrane to conform to the spikes (Fig. 2c and e). The presence of spikes on the surface increased cell attachment per unit area by 3-fold compared to a smooth hemisphere for GPOTA (M0). The length of the spikes tested did not influence attachment, suggesting that the tip of the spike (or vertex) itself was the most important attribute for increased attachment (Fig.2d). This is consistent with the importance of vertices noted earlier in influencing macrophage attachment. Machine learning was used to search for relationships between macrophage attachment and quantitative descriptors of the objects listed in Table S1. The descriptors comprised both properties of the objects such as the surface area, volume or linear dimensions and also quantification of the sub-elements used to construct the objects (defined as primitives), e.g., number of cylinders or spikes. A linear model was formed (Fig 17) and revealed the importance of large numbers of objects (with small object size) or the number of cylinder and spikes per object, as well as vertex angle being positive drivers of macrophage attachment, while increases in aspect ratio increased macrophage attachment, (see Table S1). Inhibition of phagocytic pathways to determine attachment mechanism Given that phagocytic mechanisms appear likely to be responsible for macrophage interactions with objects, a range of inhibitors were employed to interfere selectively with specific pathways to elucidate the underlying attachment mechanism on GPOTA (M0) that supports the naïve (M0) macrophage phenotype with large difference in macrophages attachment on hemispheres with and without spikes. Macrophage attachment to spiked hemispheres was abolished with the addition of cytochalasin-D, dynasore and genistein (Fig. 2f and 20). Similarly, loss of cell attachment was also observed on octahedrons, stellate dodecahedrons, cones and prismatic ovals (Fig. 20). Experiments showed that decreased cell attachment was not due to diminished cell viability (Figs.21-25). This inhibition of cell attachment through genistein suggests caveolae-dependent endocytosis, which is directly mediated through two aspects - preventing actin depolymerization in the local cortical cytoskeleton (inhibited by cytochalasin-D) and the recruitment of dynamin (inhibited by dynasore). The lack of effect of chlorpromazine, which inhibits clathrin dependent pathways, and blebbistatin which inhibits myosin II, which in frustrated phagocytosis will have little utility, provides further support for macrophage phagocytic behaviour being responsible for the significantly increased attachment on spikes as macrophages attempt to engulf these objects (Fig. 2e) ^{30,31 16,32,38}. Prior work on caveolae-mediated endocytosis in nanostructures33,34 has described how high-aspect nanostructures can locally deform the cellular membrane which leads to accumulation of intracellular scaffolding proteins and initiation of endocytosis. Similarly, the addition of spikes with vertices resembling nanopillars, will lead to membrane deformation phagocytosis driven attachment 35,36. Macrophage polarisation: Combinatorial role of 3D object shape and material chemistry Having identified several key object shapes that modulate cell attachment, the inventors sought to understand their effect on macrophage phenotype. A key process in maintaining tissue homeostasis is macrophage polarisation state which is an important determinant in clinical outcome following medical device implantation. Previous studies have shown the ability to harness macrophage polarity through chemistry or topography. Utilising the design freedom and throughput of this methodology, the inventors aimed to further their understanding of the combinatorial role of object shape and substrate chemistry in this biological process. Monocytes were cultured for 6 days, and phenotypic status was approximated using cell surface markers known to be associated with M1 and M2 phenotypes (calprotectin and mannose receptor for M1 and M2, respectively)^15,37,38. To estimate phenotypic responses, the M2/M1 marker expression ratio was calculated for all cells in direct surface contact with printed objects. Culture of macrophages on different material substrates elicited different phenotypic responses (Fig.3a- c and 23). The machine learning Random Forest regressor model in Fig.3d generated an R2 of 0.95 and 0.68 for the phenotype training and test sets respectively (Fig. 24). SHAP values indicate key object features that drive macrophage phenotype such as number of primitives in each object, object surface area, object height, but indicate that phenotype is mainly driven by chemistry (Fig. 24c). Cytokine- polarised macrophages were used as controls (Fig.25). On flat planar surfaces a significant decrease in M2/M1 ratio was observed for cells cultured on BDDA (M1), indicating an increase in a pro-inflammatory phenotype (compared to GPOTA (M0)). GDGDA (M2) had an increased M2/M1 ratio indicating an anti-inflammatory phenotype (Fig.2c). For 3D objects fabricated from BDDA (M1), no change in cell phenotype was noted compared to the flat control indicating that the material identity is the dominant driver in cell phenotype control (Fig.26). However, for the GPOTA (M0) substrate differential polarisation dependent on object geometrical properties was noted, and the inventors created a regression model to describe the differential changes in polarisation. Macrophages cultured on spiked hemispheres in all 3 materials exhibited reduced M2/M1 ratios equivalent to an increased inflammatory phenotype compared to cytokine-polarised controls (Fig.24), with GPOTA (M0) and BDDA (M1) at levels comparable to M1-phenotype and GDGDA (M2) comparable to M0-phenotypes (Fig. 3e). The role of spikes in driving inflammatory responses has previously been reported for titanium particles 39. Given the mechanosensitive activation by spiked microparticles, the inventors hypothesise there is potential overlap in the proposed mechanisms driving inflammatory processes activated by spikes on solid substrates also, which can be further supported by the inventors’ findings of preferential macrophage attachment to objects with smaller vertex angles. Detailed Methods 2PP based high throughput formulation and assessment - To achieve systematic sampling of object shapes at length scales broadly equivalent to those of immune cells, two-photon polymerisation (2PP) (Nanoscribe GT) was used in a high throughput, multi-material screening mode. 2PP provided a high precision 3D array-based platform that allowed structure-function relationships to be probed in a library of micron-scale surface-mounted 3D object. Optimisation of the 2PP formulations for a range of (meth)acrylates is described in detail in Fig.5 and 6. These figures also outline how a multiwell format containing up to 90 different formulations to be used to optimise printing fidelity with a systematic screen of photo-initiator, co-monomers, solvent addition and 2PP system fabrication parameters. ChemoArchiChip –preparation - Glass coverslips (Scientific Laboratory Supplies Ltd) were cleaned using oxygen plasma (P = 0.3 mbar, 100 W, 1 min). They were immediately transferred into dry toluene (500 mL) under argon. The silane adhesion promotor, 3-(trimethoxysilyl) propyl methacrylate (10 mL) was added to the solution, and the reaction mixture heated to 50°C for 24 h. The slides are then cooled to room temperature and washed twice by sonication with 100 mL of toluene. The slides are then dried under vacuum in a silicone-free vacuum oven (50°C) for 24 h. Surface chemistry selection – In the initial screening of polymers for macrophage polarisation study polymer micro-arrays were printed on glass slides using methods previously described. Briefly, printing was done using a XYZ3200 dispensing station (Biodot) and metal pins (946MP3B, Arrayit) at 25oC, with oxygen levels below 2000 ppm and 35% humidity. Monomers used were purchased from Sigma- Aldrich, Scientific Polymers and Polysciences. Polymerisation stock solutions, composed of monomer (50% v/v) in dimethylformamide (DMF) with photo-initiator (2,2-dimethoxy-2-phenylacetophenon) (1% w/v), were printed onto epoxy-coated slides (Xenopore), dip-coated with poly(2-hydroxyethyl methacrylate) (pHEMA; 4% w/v) in ethanol (95% v/v in water).283 homo-polymers were printed on a slide in triplicates. Micro-array slides were kept in the vacuum oven (<50 mTorr) for at least 7 days for extraction of solvent. Slides were then UV sterilised at a wavelength of 245 nm for 20 minutes and washed in tissue culture grade phosphate buffered saline (PBS) before use. Monocytes were seeded on micro-array slides at a density of 1 × 106 cells/ml, with a total medium volume of 5 ml and cultured for six days. Cells were then fixed, stained and imaged for M1 and M2 markers. In this array, cell phenotype was measured as a ratio of surface markers specific for M1 or M2 phenotype, and the average M2/M1 ratio across 7 donors was calculated for 283 homopolymers. Using the Partition Around Medoids (PAM) data clustering algorithm, polymers were separated based on their M2/M1 values into high, medium and low M2/M1 value clusters. Excluding medium clusters, high and low clusters (representing M2 and M1 polarising polymers respectively) were used to train the supervised machine learning models. By encoding different polymer chemistry with molecular fragments that are directly associated to polymer structure, chemically informative models were provided. This was achieved using the least absolute shrinkage and selection operator (LASSO) feature selection method coupled with machine learning methods. Two-class machine learning models were generated using Random Forest, Multilayer Perceptron and Support Vector Machines models. Based on their M2/M1 ratios and their potential reactivity (where the number of vinyl groups was used as a benchmark, i.e., greater the number of vinyl groups the greater the potential reactivity), different candidate monomers were chosen as base materials for fabrication. Monomer solutions of glycerol propoxylate triacrylate (GPOTA) (Sigma-Aldrich), 1,4 butanediol diacrylate (BDDA) (Sigma-Aldrich) and Glycerol 1,3 –diglycerolate diacrylate (GDGDA) (Sigma- Aldrich). Pentaerythritol triacrylate (PETA) (Sigma-Aldrich) was selected as a diluent for BDDA (M1) and GDGDA (M2) to increase printability based on its high polymerisation efficiency. Irgacure 369 (2- benzyl-2-(dimethlamino)-4’ -morpholinobutyrophenone, Sigma-Aldrich) was chosen as a photoinitiator because its absorption peak is within ½ . of the laser beam, which ensures Irgacure 369 can be excited to initiate polymerisation when a 780 nm laser is applied. Microstructure design and fabrication – Computer aided designs (CAD) for microstructures were written (a script language containing a list of coordinates) in the commercially available software, DeScribe. Briefly, the structures are sliced into several layers by choosing an appropriate slicing thickness and each layer is filled with lines by choosing hatching distances, contour count and hatching intervals. A commercial two-photon lithography setup was used for the two-photon fabrication (Nanoscribe GmbH Photonic Professional GT). The system is driven by a NIR fibre laser at 780 nm central wavelength, 80MHz repetition rate and a 120 fs pulse duration. The laser beam was focused by an oil immersion objective lens (1.4 NA, 63 x, 190 µm working distance (WD)). Micro-structures were built by moving the sample position in the XY plane using a galvo mirror and in the Z direction using a piezoelectric actuator to move the objective. The laser power was varied between 0-100% (50 mW full power) and the scan speed was 20,000 µm/s; both optimised for the respective materials printed. Printing inks (comprised of surface chemistry monomer solution and photoinitiator) were loaded onto a coverslip with immersion oil on the other side of the coverslip. The coverslip was the mounted on the sample holder and inserted into the Nanoscribe system. This present system has a capacity of 10 coverslips in the sample holder for multiple sample processing. Post-processing, the sample on the coverslip was developed in propylene glycol monomethyl ether acetate (PGMEA) and 2-propanol to remove unpolymerized monomer. The sample was then dried in air. Finally, the sample was transferred to an argon fdled glovebox (mBraun Acrll-Glovebox) maintaining < 1000 ppm O₂) and irradiated with UV light (2 x 15 W, 365 nm, 15 cm from samples) for 10 minutes.

Scanning Electron-Microscopy - Samples were air dried, mounted to SEM stubs affixed with carbon tabs and gold coated via a polaron E5175 sputter coater at 2.2 Kv for 90 seconds. Samples were loaded into and imaged with a JEOL6490LV SEM at lOKv with a 10 mm working distance under high vacuum.

Raman spectroscopy - The amount of reacted acrylate groups (RAG) during polymerisation was analysed by Raman Spectroscopy (Horiba-Jobin-Yvon LabRAM). In the crosslinking of acrylate monomers or macromers taking place while printing, the carbon double bonds (C=C) turn into carboncarbon single bonds (C-C) while the carbon-oxygen double bond (C=O) remains unchanged as it does not participate in the reaction. C=C and C=O bonds give different Raman peaks at 1635 and 1723 cm |, respectively. By comparing the unpolymerised formulation and the polymerised structures under Raman, a drop in the intensity of the C=C peaks can be observed as they form C-C bonds while the intensity of the C=O peak remains the same as before. Therefore, the percentage of RAG can be calculated using the area under the peaks mentioned before with the following equation: RAG = 1 - [ Ac=c/Ac=o/ A’c=c/A’c=o] , where AC=C/AC=O are the areas under the peaks in polymerised structures and A’C=C/A’C=O are the peak areas of unpolymerised formulation.

ToF-SIMS analysis - time-of-flight secondary ion mass spectrometry (ToF-SIMS) mapping of complex objects was carried out using a 3D OrbiSIMS (Hybrid SIMS) instrument from IONTOF GmbH. The ToF-SIMS data were acquired in positive ion polarity mode in delayed extraction mode by raster scanning a 30 keV Bi₃ ⁺ primary ion beam (delivering 0.08 pA) of 100 x 100 pm². The ToF analyser was set with 200 μs cycle time, resulting in a mass range between 0 and 2233 mass units. All ToF-SIMS intensity maps were produced using the simsMVA software''- .

Surface ToF-SIMS for the cross-contamination tests was carried out using a ToF-SIMS IV instrument (IONTOF GmbH). Secondary ion mass spectra were acquired in positive ion polarity mode using a 25 keV Bis⁺ primary ion beam delivering 0.3 pA. The primary ion beam was raster scanned over different areas with the total ion dose kept under the static limit of 10¹³ ions/cm². The ToF analyser was set with 200 µs cycle time, resulting in a mass range between 0 and 3492 mass units and a low-energy (20 eV) electron flood gun employed to neutralise charge build up. Unsupervised machine learning for all datasets was carried out using secondary ion masses as the variables and mapping pixels as observations. For each dataset, Surface Lab 7.1 (IONTOF GmbH) was used to perform an automated peak search on the total spectra restricted only to peaks with intensity higher than 100 counts and masses between 30 u and 300 u. Dead-time corrected peak areas were then exported for each observation. Principal component analysis (PCA) and Non-negative matrix factorisation (NMF) were performed using the simsMVA software42. Prior to PCA and NMF, data was Poisson scaled to account for heteroscedasticity. To create the NMF model from the signal of flat samples, repeat spectra were acquired for all three GPOTA (M0), GDGDA (M2) and BDDA (M1) formulations as well as for the pre-treated substrate (example reference spectra are in Figure 7). The data was arranged in a matrix M₁ with peak intensities in columns and repeats in rows. NMF with 3 endmembers (each representing a “pure” compound) was achieved using a Poisson-based multiplicative update rule algorithm (Fig.7) ^43,44: M1 = W1H + e where e is an error matrix, W1 contains relative endmember intensity per observation and H contains the relative secondary ion peak intensities for each endmember. Upon confirmation that matrix W1 separated the repeats of reference samples, the pseudo inverse of matrix H was used to obtain the relative endmember intensities W2 for the mapping data of complex objects (arranged in a matrix M2 with pixels in rows and peak intensities in columns): W2 = M2H(HTH) Atomic Force Microscopy - MFP-3D Standalone Atomic Force Microscope (AFM) (Oxford Instruments, Asylum Research Inc., CA) was used to obtain force-displacement curves of the polymer samples in air (dry) and in water (wet) conditions for Young’s modulus (E) calculation. An AFM silicon nitride probe RTESPA-300 (Bruker Nano Inc., CA) was used. The tip half-conical angle was characterised by measurement of a polystyrene film standard sample (E = 2.7 GPa), with a value of 20.4º±0.2, whilst thermal tuning was used to define the effective spring constant of the cantilever at 82.75 nN/nm. Derjaguin-Muller-Toporov mathematical model was used to fit the slope of the retracting curve using least squares regression line for E calculation. Monocyte isolation - Buffy coats from healthy donors were obtained from the National Blood Service (National Blood Service, Sheffield, UK) following ethics committee approval (2009/D055). Peripheral blood mononuclear cells (PBMCs) were isolated from heparinised blood by Histopaque-1077 (Sigma- Aldrich) density gradient centrifugation. Monocytes were isolated from PBMCs using the MACS magnetic cell separation system (positive selection with CD14 MicroBeads and LS columns, Miltenyi Biotec) as described previously.38,45 Cell culture - Purified monocytes were suspended in RPMI-1640 medium supplemented with 10% foetal bovine serum (FBS), 2 mM L-glutamine, 100 U/ml penicillin, and 100 μg/ml streptomycin (all from Sigma-Aldrich) (henceforth referred to as “complete medium”) and cultured at 300,000 cells cm-1 in 6-well polystyrene plates (Corning Life Sciences). Immunocytochemistry - For fluorescence analysis, cells cultured on ChemoArchiChips were immunostained using standard procedures. Adherent cells on coverslips were fixed with 4% paraformaldehyde (Bio-Rad) in PBS for 10 min. Fixation and all subsequent steps in this procedure were carried out at room temperature; all washes were carried out with 0.2% Tween 10 (Sigma-Aldrich) in PBS (5 min per wash) except where stated. Following fixation, cells were washed three times, blocked with 1% (w/v) glycine (Fisher Scientific) and 3% (v/v) bovine serum albumin (BSA, Sigma-Aldrich) in PBS for 30 min. Subsequently, cells were washed twice and incubated for 30 min with 5% (v/v) goat serum (Sigma-Aldrich) in PBS to block non-specific antibody binding. Cells were stained with anti- human calprotectin and anti-human mannose receptor incubated for 1 h, washed 3 times, and then incubated for 1 h with the appropriate secondary antibody at room temperature (for all antibody information see Table S2). Finally, all cells were stained with SYTOX Deep Red nuclear stain as per manufacturer’s instructions, washed 3 times with PBS, once with dH20 and then mounted with anti-fade medium (Pro-Long Gold), on a standard microscope slide followed by imaging using an automated fluorescent confocal microscope (Zeiss). Image acquisition - Images were acquired with a Zeiss LSM710 microscope (Carl Zeiss GmbH) with a 20x plan-Apochromat/0.8NA (M27) DIC objective. Zen 2012 software (v6.0; Carl Zeiss GmbH) was used to capture images and for image stacks, slices were captured at 1 micron intervals. All data was processed using Image J (version 1.52p; Java 1.8.0_172 (64 bit)) and ZEN Zeiss LSM 700 imaging software. 3D Image analysis - A custom ImageJ macro was developed to identify and measure cells attached to the 3D printed objects and the phenotype of those cells determined by fluorescence intensity. The processing and analysis was carried out following the steps: 1) raw tiff images exported from Zen were imported into ImageJ FIJI, 2) a maximum intensity projection was created of all fluorescence channels, 3) background subtraction was carried out (using rolling ball of 20 px), 4) the default thresholding method was used to distinguish the objects and cell signal from the background- thresholding setting a minimum and maximum pixel intensity range on the selected image that groups all pixels falling within this range and excluding the background, 5) to quantify cells on objects, after application of a threshold the image from the blue channel (405 nm excitation) was used to determine the Object ROI’ using the native autofluorescence and exclude cells not on the 3D printed objects. This ROI was dilated 4 times to ensure peripheral cell attachment was also counted.6) After application of a threshold the image of cell nuclei was then combined with the Object ROI’ and subjected to particle analysis to quantify cells only associated within the boundary of the printed object. 7) An outline of the identified cell nuclei within the Object ROI was automatically exported as tiff so that it could be compared to the original images, 8) To quantify cell phenotype fluorescence measurements, the identified cell nuclei ROI was dilated 4 times and then redirected to the green (488 nm; M2; mannose receptor) and red channels (561 nm; M1; calprotectin) independently. Particle analysis was carried out in each channel to generate area, standard deviation, mean and median grey values. Due to material autofluorescence by GDGDA (M2) objects an initial step was added, consisting of a ML based annotation and segmentation tool called APEER (Zeiss). Example images were first annotated for both cell nuclei and object, and then applied for all GDGDA (M2) images and segmented into a cell nuclei and background masks. The cell nuclei mask was then referred to during step 4 in the aforementioned custom ImageJ macro. All data sets were run through batch analysis and results were automatically exported as a text file. Data were exported to Microsoft Excel and data was visualised using GraphPad Prism Software v 9.0.2 (64 bit) (https://www.graphpad.com). Data modelling and correlations Design parameters as well as radiomics descriptors provided a total of 44 descriptors used for computational modelling. Radiomics descriptors were obtained by converting the computer-aided design (CAD) files for the objects into nearly raw raster data (nrrd) file formats, which were processed by the pyradiomics Python package (version 3.0.1). Table S1 shows the full list of descriptors obtained. Multiple linear regression with expectation maximisation (MLREM) and random forest regression (from package scikit-learn with default parameters) using bootstrapping (50 sample sets without replacement) implemented in Python were used to identify linear and non-linear structure activity relationships for macrophage attachment, polarisation (Log(M2/M1) and polarisation in synergy with attachment (using a composite variable Log(M2/M1) × Attachment). The performance of the linear regression model for macrophage attachment is shown in Figure 16. Strong correlations between the linear model predictions compared to the measured values in the test sets, with average R2 =0.80±0.05 and root mean square error (RMSE) = 12.49±1.50 (Figures 16a and S16b). There were no strong linear relationships for the polarisation for the composite polarisation variable Log(M2/M1) × Attachment. A non-linear relationship was identified using extreme gradient boosting machine learning method, with an R2 = 0.95±0.00 and RMSE = 6.10±0.30 for the test set. Attachment inhibition - To elucidate the mechanism that underlies the macrophage attachment on GPOTA (M0) printed ChemoArchiChips several inhibitors - cytochalasin D (2μM) which prevents caveolae and clathrin mediated endocytosis by blocking actin polymerisation, dynasore (80μM) which inhibits dynamin dependent endocytosis, genistein (80μM) which inhibits caveolae mediated endocytosis, chlorpromazine (80μM) which inhibits clathrin mediated endocytosis by preventing the assembly and disassembly of clathrin lattices on cell surfaces and on endosomes and blebbistatin (50μM) which inhibits myosin II in vesicle fission - were added to the culture of macrophages 0.5h prior to culture on Chemo ArchiChips for a further 72hrs. Cell attachment was quantified using the high throughput confocal imaging and analysis method described above. Statistics and reproducibility – Unpaired t-test was used to analyse the difference between two groups, and a one-way analysis of variance (ANOVA) among multiple groups with a minimum confidence interval of 95%. All the data are presented as the mean ± standard deviation (s.d.) as indicated in the experiments. P values were calculated by PRISM software (GraphPad) and regarded significant if less than 0.05. Further testing To guarantee that the high throughput printing of multiple objects and materials on the same chip did not have any cross-contamination, ToF-SIMS was carried out on the surface of samples of GPOTA (M0), BDDA (M1) and PETA printed isolated in individual substrate and mixed in a chip. Several repeats of each sample were measured and principal component analysis (PCA) of the results was done to check for any surface chemistry difference between materials printed together (cross) or isolated. Details of the experiment and data processing are described in Methods. PC 1 separates ethylene glycol from propylene glycol type of ions and PC 2 separates tryacrylates from diacrylates characteristic ions [47]. The results show that the surface chemistry of samples printed with all 3 materials have not changed when they were printed as part of the same chip using the method described in the main text, which confirms that there is no detectable cross-contamination between samples. Chemical analysis Chemical analysis of the bulk was achieved using Raman spectroscopy to evaluate polymerisation of monomer. GPOTA (M0), BDDA (M1) and GDGDA (M2) were found to have an alkene group reaction of 56%, 54% and 51%, respectively (Fig.11 and Raman spectra Fig.9). This relatively low alkene group conversion is likely because of steric inhibition in these di- and tri-functional monomers where polymerisation was achieved through just over 50 % of the alkenes, with the remainder locked into the polymer network but unable to react further, which is consistent with previous observations46. Time-of- flight secondary ion mass spectrometry (ToF-SIMS) was used to assess the surface chemistry of the complex 3D objects. Despite the similarity in chemical structure between GPOTA (M0) and PETA, the challenge of primary ion beam shadowing and low signal from these complex 3D objects, the unsupervised machine learning method non-negative matrix factorisation (NMF) allowed differentiation of the two polymers using a selection of secondary ions for each material. The model was created using data from flat samples and then applied to ToF-SIMS imaging data from the 3D objects (Fig. 7). This showed that the surface chemistry of flat samples is reproduced in the 2PP manufactured complex 3D objects and localised to the object and not the space in between. (Figs.1b and 9, 7). The exception to this is around some objects for the GDGDA (M2) material. A surface contamination C₄H₁₂N+ (m/z=74.09) was notable in the GDGDA (M2) which had an amine component in 2PP-objects. Comparison to the micro array indicated that was also present and therefore is attributed to a low-level bulk contaminant in the GDGDA (M2) monomer as-received, that segregates to the surface and contributes significantly to the chemistry. The surface modulus in wet conditions simulating cell culture was determined by AFM to be highest on BDDA (M1) (3.4 + 0.5 GPa) compared to similar lower values for GPOTA (M0) (1.9 + 0.03 GPa) and GDGDA (M2) (2.2. + 0.2 GPa) in Figure 18. Discussion The extraction of design rules for immune instruction using surface architecture and material chemistry is possible from this rich data set which is summarised with a schematic in Fig.4. Reducing the size of objects generally results in an increase in cell attachment (Fig. 1f). This is consistent with previous reports of macrophage phagocytosis of suspensions of particles and their attachment to supported 2D topographies.13,14 Attachment was also found to be strongly dependent on vertex/cone angle, with 60° representing the threshold below which macrophage attachment was significantly increased (Fig. 2a). This has parallels in observations of particle phagocytosis where a study of polystyrene ellipsoids revealed a critical angle in that context.23 Internalisation only occurred when macrophages attempted to phagocytose particles which were spheres or when they approached elliptical spheroids end-on, other approach directions resulted only in spreading. Whilst the attachment that was observed is very different to internalisation of particle, the inventors view the coincidence of a critical angle below which cell response changes as being significant; hence critical angles arise for both engulfment and for attachment. For objects with vertex/cone angles below 60° a majority of cells on objects were associated with vertices compared to elsewhere on the objects (Fig.2b). The general favoured adherence to vertices can additionally be linked to phagocytosis driven attachment, as vertices will deform the membrane, similarly to when they encounter microbes26 or high-aspect nanostructures35,36. Previously it has been found that different chemistries adsorb proteins differentially in quantity and quality, with protein adsorption identified as a prime driver of macrophage polarisation15. At the same time, it has been found that while chemistry has greater influence over macrophage polarisation, topographical shape can have synergistic/agonistic effects on this polarisation40,41, which can be seen here with GDGDA (M2) as differential polarisation was observed depending on the specific architecture they were cultured on. A majority of objects induced an M0 or M1 phenotype, while certain objects shapes were driving a M2 phenotype. Specifically, GDGDA (M2) stellates, larger cones and hosohedrons with higher groove numbers exhibited increased M2/M1 ratios (Figure 26d and 26e). For macrophages to exert their functions they initially need to attach to an implant/material. Design rules highlighted in this research are that attachment can be driven by decreasing object size (with 15 µm sized octahedron showing preferential attachment for all 3 polarising materials) and vertex/cone angles < 60° increase attachment. (Fig.1d,f and Fig.2a and b, e). Across all objects, the machine learning model revealed that attachment is influenced by the following within a particular array of a given architecture: large number of objects (which all have small object sizes), number of cylinders and spikes primitives making up a given object, as well as object flatness and vertex angle (positively), and object elongation (negatively) (Fig. 1g and 15). Generally, most objects investigated were shown to drive M2/M1 ratios downwards compared to flat surfaces with a few exceptions (Table S4). These observations have led the inventors to present a series of design rules for achieving a specific macrophage phenotype in Table S5. The inventors found that while chemistry was the main driver of macrophage phenotype, surface bound objects can have synergistic/agonistic effect on the phenotype as well. Cells cultured on BDDA (M1) were generally found to be rendered less receptive to topographical cues, while cells cultured on GPOTA (M0) and GDGDA (M2) were usually still receptive to manipulation by objects (e.g., judicious use of spikes can lead to a more M1-dominant macrophage population). Therefore, a complete design process must combine the rules for both attachment and polarisation using combination of object and chemistry to maximise any desired effect. The fact that the phenotype of macrophages cultured on BDDA (M1) remains nearly unchanged, even though macrophages are so plastic and receptive to environmental cues, is an interesting observation relevant for future study. In summary, the inventors have identified key relationships between geometry, materials chemistry, and macrophage behaviour using the ChemoArchiChip, illustrating its utility as a new platform for interrogating biological structure-function relationships. From a range of polymer candidates, those which preferentially steer macrophages towards characteristic phenotypes on planar surfaces were chosen for printing with a high-resolution additive manufacturing technique to create previously inaccessible geometries, allowing the inventors to probe the macrophage attachment/phenotype-object- material relationships. The experiments showed how it is possible to improve cell attachment, e.g., objects with shapes that possessed low vertex/cone angles led to high macrophage attachment independent of materials chemistry, a function which was mediated by caveolae-dependent endocytosis. This has allowed a determination of how to drive macrophages to particular phenotypes. Materials chemistry is a dominant driver for phenotype, but, unexpectedly, certain shaped objects - such as tetrahedrons - can be used to manipulate attachment or enhance the phenotypic drive of the materials.

ids and hemispheres)

λleast are the lengths of the largest and smallest t, sphere-like) and 0 (a flat object, or single-slice using the physical coordinates of the voxel centresoes not make use of the object mesh. eld the smallest axis length of the ROI-enclosingnt λleast. In case of a 2D segmentation, this valueng the physical coordinates of the voxel centresoes not make use of the object mesh. . This feature yield the largest axis length of theipal component λmajor. The principal componentoxel centres defining the ROI. It therefore takes . rwise Euclidean distance between object surface Euclidean distance between object surface mesh Euclidean distance between object surface mesh uclidean distance between object surface mesh

. For each face in the mesh, defined by y that face and the origin of the image ^_^^ × (^_^^ × ^_^^) ^_^ = 6 must be consistently defined as either otal volume of the ROI is obtained as: ^_{^ ^ =} ^{^(} _^^ ⁾ ^^^ Object Minor Axis Length Major axis is calculated as 4 times the squared root of λmajor. This descriptor yields the second-largest axis length of the ROI-enclosing ellipsoid and is calculated using the largest principal component λminor. The principal component analysis is performed using the physical coordinates of the voxel centers defining the ROI. It therefore takes spacing into account but does not make use of the object mesh. Object Sphericity Sphericity is the ratio of the perimeter of the object to the perimeter of a circle with the same surface area as the object and therefore a measure of the roundness of the object region relative to a circle. It is a dimensionless measure, independent of scale and orientation. The value range is 0<sphericity≤10<sphericity≤1, where a value of 1 indicates a perfect circle (a circle has the smallest possible perimeter for a given surface area, compared to other objects). he mesh is calculated: 1 ^_^ = |._^._^ × ..| 2 _{^ ^}

ulated sub-areas: olume (A/V) mber of voxels in the ROI by the volume of e and is not used in subsequent descriptors.ation of other object descriptors.e 10th percentile of X.

e 90th percentile of X. A larger value implies a greater sum of the ^{^} rom the package for the experiments. ⁾ + .⁾^

Table S2 - Antibodies used in this study.

Table S3 Geometric object angles.

Table S4: Exceptions to physical shape influences on phenotype.

Table S5: Target phenotype strategies.

Further testing Further experimental work has been carried out in relation to the provision of micro-scale three- dimensional objects on a surface. In this regard, silicone rubber tetrahedra have been successfully moulded onto a surface. The desired three-dimensional tetrahedral shapes were moulded onto the surface by using masters that had been produced by 3D printing. The tetrahedra had a maximum dimension of about 100 µm. The silicone rubber was flexible, and the master was more rigid; therefore it can be appreciated that this approach allowed items having different mechanical properties to be textured. Therefore it has been shown that the invention can be implemented using moulding techniques as well as additive manufacturing techniques.

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Claims

CLAIMS 1. The use of micro-scale three-dimensional objects on a surface, to influence the extent to which macrophage attachment occurs at the surface and/or the phenotype of macrophage that attaches to the surface.

2. The use of claim 1, wherein the micro-scale three-dimensional objects are used to: (a) promote low macrophage attachment at the surface, or high macrophage attachment at the surface; and/or (b) influence the phenotype of macrophage that attaches to the surface towards pro-inflammatory (M1) or towards anti-inflammatory (M2).

3. A product wherein micro-scale three-dimensional objects are provided on a surface of the product.

4. The product of claim 3, which is a healthcare implant whereby micro-scale three-dimensional objects are provided on a surface of the implant.

5. The product of claim 4, which is an implant selected from permanent implants, such as artificial heart valves, voice prostheses, prosthetic joints including hip replacements, breast implants, implanted artificial lenses, stents (e. g. coronary stents), permanent surgical meshes, and shunts (e.g. hydrocephalus shunts); and non-permanent implants, such as pacemakers and pacemaker leads, drain tubes, endotracheal or gastrointestinal tubes, temporary or trial prosthetic joints, temporary surgical meshes, surgical pins, guidewires, dental and bone implants such as dental screws, surgical staples, chest drains and peritoneal drains, cannulas, subcutaneous or transcutaneous ports, implanted sensors such as implanted glucose sensors, indwelling catheters and catheter connectors, including catheters for continuous ambulatory dialysis, intraocular lenses and contact lenses, sustained drug delivery implant devices, such as the type implanted subcutaneously or intraocularly (e.g. to deliver hormones for contraception, or insulin for diabetes, or steroids for ocular inflammatory disorders), and cell encapsulation devices.

6. The product of claim 4 or claim 5, wherein the implant is configured to, in use, interface with soft tissue and wherein at least the surface of the implant that will, in use, form an interface with the soft tissue is provided with the micro-scale three-dimensional objects.

7. A method of manufacturing a product wherein micro-scale three-dimensional objects are provided on a surface of the product, the method comprising: . providing the product and then applying the micro-scale three-dimensional objects onto a surface of the product, e.g. by embossing, or injection moulding, or blow moulding, or roll to roll processing, or casting; or . manufacturing the product with the micro-scale three-dimensional objects provided on a surface of the product, e.g. by additive manufacturing or injection moulding.

8. The invention of any one of the preceding claims, wherein the maximum dimension of the objects is: (a) in the range of from 1 µm to 500 µm; (b) in the range of from 1 µm to 300 µm; (c) in the range of from 1 µm to 200 µm; or (d) in the range of from 5 µm to 120 µm.

9. The invention of any one of the preceding claims, wherein the objects are selected from the group consisting of: (a) simple polyhedrons (e.g. cubes, icosahedrons, dodecahedrons, octahedrons and tetrahedrons), stellate polyhedrons such as stellate dodecahedrons, prisms, pillars (e.g. cylinders), cones, prismatic ovals, prolate spheres, hemispheres (which may be decorated with spikes), and grooved hosohedrons; or (b) tetrahedrons, octahedrons, icosahedrons, dodecahedrons, hemispheres and cones.

10. The invention of any one of the preceding claims, wherein one or more of the following strategies are used to reduce the attachment of macrophages to the surface: . addition of micro-scale three-dimensional objects which are tetrahedra with base diameter greater than 45 µm; . addition of micro-scale three-dimensional objects which are pillars with base diameter greater than 45 µm; . addition of micro-scale three-dimensional objects which have a low aspect ratio, e.g. cylinders; . addition of micro-scale three-dimensional objects which have a vertex/cone angle of 60° or more.

11. The invention of any one of the preceding claims, wherein the objects are tetrahedra having a vertex angle of 60° or more and having a base diameter: (a) greater than 45 µm, (b) greater than 60 µm, (c) greater than 80 µm, or (d) greater than 100 µm.

12. The invention of any one of claims 1 to 9, wherein one or more of the following strategies are used to increase the attachment of macrophages to the surface: . addition of micro-scale three-dimensional objects which have a vertex/cone angle less than 60°; . addition of micro-scale three-dimensional objects which have a base diameter that is 45 µm or less; . addition of micro-scale three-dimensional objects which are spiked, e.g. spiked hemispheres; . addition of micro-scale three-dimensional objects which have a high aspect ratio, e.g. cones and prismatic ovals.

13. The invention of any one of claims 1 to 9 and 12, wherein the object is selected from octahedrons, icosahedrons, dodecahedrons, hemispheres and cones, each of which is optionally spiked, and which have a vertex/cone angle less than 60° and having a base diameter: (a) 45 µm or less, (b) 40 µm or less, (c) 30 µm or less, or (d) 25 µm or less.

14. The invention of any one of the preceding claims, wherein the following strategy is used to increase the M2/M1 phenotype of macrophages attached to the surface: . addition of micro-scale three-dimensional objects which have a base diameter that is 45 µm or less and which have more than 6 vertices.

15. The invention of any one of the preceding claims, wherein the object has 8 or more vertices and a base diameter that is: (a) 45 µm or less, (b) 40 µm or less, (c) 30 µm or less, or (d) 25 µm or less.

16. The invention of claim 14 or claim 15, wherein the objects are formed from a polymer which is an M2 material, e.g., comprising poly(glycerol 1,3–diglycerolate diacrylate); poly-N- [tris(hydroxymethyl)methyl] acrylamide; poly(methacrylamide); or poly(tridecafluorooctyl acrylate).

17. The invention of any one of claims 1 to 13, wherein the following strategy is used to decrease the M2/M1 phenotype of macrophages attached to the surface: . addition of micro-scale three-dimensional objects which are spiked, e.g. spiked hemispheres.

18. The invention of any one of the preceding claims, wherein one or more of the following criteria is controlled in order to affect the extent of macrophage attachment: i. Number of Objects per Array ii. Polyhedral Dihedral Angle (di-interplanar angle) iii. Object Elongation iv. Height of object (µm) v. Size of Spikes (µm) vi. Number of Pillars (e.g. Cylinders) vii. Object Sphericity viii. Vertex/cone angle ix. Number of Spikes per Object x. Space Between Spikes (µm) 19. The invention of any one of the preceding claims, wherein one or more of the following criteria is controlled in order to affect the polarisation of the attached macrophages: I. Space Between Spikes (µm) II. Number of Objects per Array III. Object Surface Area (µm2) IV. Use of GDGDA (poly(glycerol 1,3–diglycerolate diacrylate)) V. Total Number of Faces per Object VI. Object Volume (µm3) VII. Height of object (µm) VIII. Use of BDDA (poly(1,4 butanediol diacrylate)) IX. Total Intersected Area (µm2). 20. The invention of any one of the preceding claims, wherein the object has an angled face, thereby providing a vertex/cone angle. 21. The invention of any one of the preceding claims, wherein the object is selected from tetrahedrons, octahedrons, icosahedrons, dodecahedrons, and cones. 22. The invention of claim 21, wherein the object is selected from tetrahedrons and cones.