Prospective Design, Rapid Prototyping, and Testing of Smart Dressings, Drug Delivery Patches, and Replacement Body Parts Using Microscopy Aided Design and ManufacturE (MADAME)

Abstract

Natural materials exhibit smart properties including gradients in biophysical properties that engender higher order functions, as well as stimuli-responsive properties which integrate sensor and/or actuator capacities. Elucidation of mechanisms underpinning such smart material properties (i), and translation of that understanding (ii), represent two of the biggest challenges in emulating natural design paradigms for design and manufacture of disruptive materials, parts, and products. Microscopy Aided Design And ManufacturE (MADAME) stands for a computer-aided additive manufacturing platform that incorporates multidimensional (multi-D) printing and computer-controlled weaving. MADAME enables the creation of composite design motifs emulating e.g., patterns of woven protein fibers as well as gradients in different caliber porosities, mechanical, and molecular properties, found in natural tissues, from the skin on bones (periosteum) to tree bark. Insodoing, MADAME provides a means to manufacture a new genre of smart materials, products and replacement body parts that exhibit advantageous properties both under the influence of as well as harnessing dynamic mechanical loads to activate material properties (mechanoactive properties). This Technical Report introduces the MADAME technology platform and its associated machine-based workflow (pipeline), provides basic technical background of the novel technology and its applications, and discusses advantages and disadvantages of the approach in context of current 3 and 4D printing platforms.

Keywords: advanced materials; computational modeling; imaging; medical devices; microscopy-aided design and manufacture; smart materials and systems; translational medicine.

Figure 1

MADAME describes a design and manufacturing process that is applicable for the creation of diverse materials exhibiting unique gradients in mechanical structure. These gradients underpin the remarkable higher order function of such structures. For example, (A) the towering eucalyptus tree that bends like a blade of grass in high winds, (B) the mechanical gradients intrinsic to joint function in insect exoskeletons, and (C) the internal musculoskeletal system of vertebrates are all enabled through prescient distribution of mechanical properties in space and time. Nature provides infinite patterns that provide inspiration for ideation of smart materials. (D) Such mechanical gradient properties can be implemented to harness natural movements (D1, D2) for external (wearables, D3) and internal (implants, D4) applications that harness the movement of the local system e.g., to deliver directional pressure gradients and/or gradients in strain at interfaces. Figure adapted and used with permission (2).

Figure 2

”Pipeline” for microscopy-enabled, scaled-up computer-aided design, and manufacture of composite multifunctional textiles and 3D prints emulating the body's own tissues, on hand from an example mapping, and weaving patterns emulating those of structural proteins, collagen, and elastin, in tissues. “Pipeline” describes the process of acquisition, filtering, and transformation of data, taking the raw data as input, processing it, and producing a final result as the end process in the pipeline. (A–D) Second harmonic generation and two photon microscopy of tissues reveals a spatial map of elastin and collagen, e.g., in the periosteum, a soft, and elastic tissue sheath that bounds all non-articular surfaces of bone. In this example, microscopy is used to map the precise pattern of elastin and collagen in native tissue. As the initial step in the pipeline, the raw microscopy data is thus transformed to patterns of representing material properties, e.g., stiffness. (E) These tissue maps are then rendered using computer-aided design software, where the patterns can be optimized for desired design specifications. This step in the pipeline creates stl files that are input into rapid manufacturing processes including e.g., integrated weaving and/or multi-dimensional printing. (F) Optimized designs thus provide inputs for computer controlled weaving of textiles and combined printing of composites that emulate the tissue studied under the microscope. This end process in the pipeline results in novel composite textiles that can be implemented in multiple fields of use. Figure adapted from (1) and used with permission.

Figure 3

Recursive weaving of advanced materials that emulate Nature's own. (a–e) Example depicting anisotropic mechanical properties of periosteum, the hyperelastic sheath covering all bony surfaces in vertebrates. In the sheep femur (a) strain maps are created during loading in tension using digital image correlation, on sections of periosteum (a–e) cut in either the longitudinal or circumferential direction (a). High resolution strain maps of the entire periosteum of the femur, in situ during stance shift loading, show heterogeneity of mechanical properties in space and time over the course of the loading cycle [(f), still image taken from single frame of digital video over the loading cycle]. (g) Conceptually, a singular solution to recursively weave the tissue fabric of the periosteum tested would be to “unravel” a single strand's mechanical properties that would vary along the entire length of the strand. Many more solutions exist through creation of fiber patterns comprised of elastic and tough fibers such as elastin and collagen using computer-controlled weaving (1, 3, 4). Figure adapted from (, –18) and used with permission.

Figure 4

(A–C). Mapping of the vascular porosity in bone. (A) Fluorescent confocal image. (B) Mask depicting area with vascular pores, area(bone) in the equation (D). (C) Mask depicting area without vascular pores or area(mask) in the equation (D). (D) Equation to calculate vascular porosity. (E,F) Calculation of lacunar porosity in bone, using (E) transmitted light images.

Figure 5

Mapping of the lacunar porosity in bone using transmitted light images (A,B) and mapping of site specific lacunar porosity in bone (C1–5). (A) Mask of bone with lacunae. (B) MaskVolume of bone without lacunae. Based on the calculations, the lacunar porosity is 1.1% for the example shown. (C1) Different colors represent different lacunar porosities in specific sites of the cross section. (C2-5) Color plots depicting regions on different cross sections exhibiting characteristic porosities, e.g., 1.78 and 0.65%.

Figure 6

From high resolution maps of different caliber porosities [vascular, lacunar–(A,B)] to generation of matrices representing imaging data (C,D).

Figure 7

Heat maps are generated from random assessment of areas (A), for lacunar and vascular porosity (B) in this case, and depicted as density gradients (C,D), using hot-warm colors (red, orange, yellow) and low density using cool colors (blue, green). Images adapted from Knothe Tate et al. (14) and used with permission.

Figure 8

Application of MADAME to designer dressings and wearables. Modular designs (A) can be scaled up and tuned e.g., for bespoke bandages with spatial and temporal control of drug delivery. (B–D) Directionality of delivery dots and surrounding areas can be controlled by the architecture of the module. Scale bars depict fluid velocity, with warm colors indicating flow outwards and cool colors, flow inwards; e.g., pushing on the patch (B,C) results in flow out of the delivery dots. (E) Example of large scale, wearable wound dressing for e.g., burn treatment. Images recreated with permission from (14, 17).

Figure 9

Early example of scale up and rapid prototyping of micron scale systems to emulate smart permeability properties in 1,000x scaled up (cm length scale) system. The intrinsic tissue permeability cannot be measured based on microscopy alone (B). 1,000x scaled up physical renderings of the microscopic data are depicted as inverse microscopy data to encode flow around cells and their networks (A). Virtual renderings of single cells enable analysis of the effect of pericellular matrix permeability on bulk pericellular tissue permeability (C). Only through parallel study of virtual, scaled up physical renderings, and virtual in silico modeling based renderings of the system at different length scales, can the interactions between the elements and bulk properties of the tissue be estimated and validated. These studies were the first of their kind and they paved the way for organ to nano scale maps of human tissues and organs using other imaging modalities. Images used with permission after (28).

Figure 10

Coupled experimental mechanics and modeling studies enable determination of the range of strains on the surface of the human arm typical for daily activities. Digital imaging correlation methods and custom computer code developed for mapping strains in situ on the surface of the periosteum (cf. Figure 3) were used to measures strain on the surface of the arms of three subjects, with and without the presence of a compressive dressing. Strains are mapped at one point in time (one frame of digital video) during flexion and compression of the arm. Figure after (33) and used with permission.