Polylactides in additive biomanufacturing

ADR-13037; No of Pages 19 Advanced Drug Delivery Reviews xxx (2016) xxx–xxx

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Advanced Drug Delivery Reviews journal homepage: www.elsevier.com/locate/addr

Polylactides in additive biomanufacturing☆ Patrina S.P. Poh a, Mohit P. Chhaya b, Felix M. Wunner b, Elena M. De-Juan-Pardo b, Arndt F. Schilling c,d, Jan-Thorsten Schantz c, Martijn van Griensven a, Dietmar W. Hutmacher b,e,⁎ a

Department of Experimental Trauma Surgery, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia Department of Plastic Surgery and Hand Surgery, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany d Clinic for Trauma Surgery, Orthopaedic Surgery and Plastic Surgery, University Medical Center Göttingen, Göttingen, Germany e Institute for Advanced Study, Technical University of Munich, Garching, Germany b c

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Article history: Received 27 June 2016 Accepted 25 July 2016 Available online xxxx Keywords: Additive manufacturing 3D printing Bioprinting Tissue engineering and regenerative medicine Poly(lactic acids) Computer-aided design Computer-aided engineering Computer-aided manufacturing

a b s t r a c t New advanced manufacturing technologies under the alias of additive biomanufacturing allow the design and fabrication of a range of products from pre-operative models, cutting guides and medical devices to scaffolds. The process of printing in 3 dimensions of cells, extracellular matrix (ECM) and biomaterials (bioinks, powders, etc.) to generate in vitro and/or in vivo tissue analogue structures has been termed bioprinting. To further advance in additive biomanufacturing, there are many aspects that we can learn from the wider additive manufacturing (AM) industry, which have progressed tremendously since its introduction into the manufacturing sector. First, this review gives an overview of additive manufacturing and both industry and academia efforts in addressing specific challenges in the AM technologies to drive toward AM-enabled industrial revolution. After which, considerations of poly(lactides) as a biomaterial in additive biomanufacturing are discussed. Challenges in wider additive biomanufacturing field are discussed in terms of (a) biomaterials; (b) computer-aided design, engineering and manufacturing; (c) AM and additive biomanufacturing printers hardware; and (d) system integration. Finally, the outlook for additive biomanufacturing was discussed. © 2016 Elsevier B.V. All rights reserved.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Moving toward direct manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Aviation and automotive industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Furniture and fashion industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Dental and medical industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Effort to address specific challenges for AM-enable industrial revolution . . . . . . . . . . . . . . . . 3.1. Standards development for AM technologies . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Technology innovations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Electron beam melting (EBM) for stressrelieved metal-printed parts . . . . . . . . . 3.2.2. Multiple-axes 3D printers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3. Convergence of subtractive and additive manufacturing . . . . . . . . . . . . . . . 3.2.4. Continuous liquid interface production (CLIP) technology . . . . . . . . . . . . . . . Additive biomanufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Convergence of additive manufacturing and tissue engineering and regenerative medicine (TERM) 4.2. Poly(lactides) as biomaterial in additive biomanufacturing . . . . . . . . . . . . . . . . . . 4.2.1. Structural composition of PLA . . . . . . . . . . . . . . . . . . . . . . . . . . .

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☆ This review is part of the Advanced Drug Delivery Reviews theme issue on “PLA biodegradable polymers”. ⁎ Corresponding author at: 60 Musk Avenue, Kelvin Grove, QLD 4059, Australia. Fax: +61 7 3138 6030. E-mail addresses: [email protected] (P.S.P. Poh), [email protected] (M.P. Chhaya), [email protected] (F.M. Wunner), [email protected] (E.M. De-Juan-Pardo), [email protected] (A.F. Schilling), [email protected] (J.-T. Schantz), [email protected] (M. van Griensven), [email protected] (D.W. Hutmacher).

http://dx.doi.org/10.1016/j.addr.2016.07.006 0169-409X/© 2016 Elsevier B.V. All rights reserved.

Please cite this article as: P.S.P. Poh, et al., Polylactides in additive biomanufacturing, Adv. Drug Deliv. Rev. (2016), http://dx.doi.org/10.1016/ j.addr.2016.07.006

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Consideration of PLA as biomaterial in additive biomanufacturing 5.1. Print material supply . . . . . . . . . . . . . . . . . 5.2. Storage conditions . . . . . . . . . . . . . . . . . . 5.3. Printing conditions . . . . . . . . . . . . . . . . . . 5.4. Sterilisation . . . . . . . . . . . . . . . . . . . . . 6. Challenges for additive biomanufacturing . . . . . . . . . . . 6.1. Biomaterials . . . . . . . . . . . . . . . . . . . . . 6.2. Computer-aided design, engineering and manufacturing . 6.2.1. Computer-aided design (CAD) . . . . . . . . 6.2.2. Computer-aided engineering (CAE) . . . . . . 6.2.3. Computer-aided manufacturing (CAM) . . . . 6.2.4. CAD/CAE/CAM digital data management . . . . 6.3. AM and additive biomanufacturing hardware . . . . . . 6.3.1. Manufacturing tools . . . . . . . . . . . . . 6.3.2. In-process monitoring tools . . . . . . . . . 6.4. Systems integration . . . . . . . . . . . . . . . . . 7. Future outlook . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction The term additive manufacturing (AM) refers to a broad range of techniques that turn three-dimensional (3D) digital data into physical objects and has been defined by the American Society for Testing and Materials (ASTM) International Committee F42 as the “process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies” [1]. Commonly defined in the consumer market as 3D printing, AM, as defined in the manufacturing industry, is a suite of computer-automated processes that fabricates physical 3D objects layer by layer from computer-aided design (CAD) models using metallic, plastic, ceramic, composite and biological materials. One might argue that the ideation of AM technology can be traced back to almost 150 years ago, arising from topography and photosculpture, which uses a technique which can be viewed as manual “cut and stack” approaches to building a freeform object in a layer-bylayer fashion [2]. However, the development of modern AM techniques did not kick-start until the 1950s, with the patent filed by Munz of a system that features the present day stereolithography (SLA) techniques [2,3]. The process proposed by Munz can selectively expose and fix a transparent photo emulsion in a layer-wise fashion, then manually carved or photochemically etched out the fixed photo emulsion to create a 3D object. Subsequently, in 1968, Swainson proposed and later patented a process to directly fabricate a plastic pattern by selective, three-dimensional polymerisation of a photosensitive polymer at the intersection of two laser beams [4]. However, the first truly successful viable AM process was effectively a powder deposition method with an energy beam proposed by Ciraud in 1972 [2,5]. Since then, AM continued to evolve and blossom into a plethora of processes, including stereolithography (SLA), 3D Printing (3DP), fused deposition modelling (FDM), selective laser sintering (SLS), selective laser melting (SLM), laminated object manufacturing (LOM), laser metal deposition (LMD), inkjet printing, and others [6].

2. Moving toward direct manufacturing At an early stage, AM processes were predominantly used by engineers to present their designs through physical models (also termed prototypes); thus, these technologies in the 1990s got the name “rapid prototyping”. In recent years, the vision of the broader application of AM goes beyond the creation of prototypes, marching into the era of “direct manufacturing”, a term to describe the production of end-use components [7]. This is mainly driven by the various

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emerging AM industry sectors, each taking care of the development of appropriate software, hardware and new materials. The convergence of these AM industry segments greatly improves the machine feasibility and the printed-parts quality. As AM becomes both a disruptive and transforming technology, its impact continues to grow into various industries, i.e., aviation, automotive, electronics, furniture, fashion, medical, and others. A recent report on AM published by Wohler Associates indicated that the global AM industry grew 34.9% in 2013, reaching a total market value of $3.07B. It is projected that the total market value for AM industry will approach $6B by 2017 [8]. 2.1. Aviation and automotive industry AM has a major impact on many industries and is increasingly becoming important as it allows freedom of design and greatly reduced time-to-market. The aviation industry has partially adopted AM technology into their manufacturing processes, as most products are geometrically complex and manufactured in small batch size with high unit costs. For example, GE Aviation (GEA) has successfully developed a fuel nozzle, a component for flight engine fuel delivery system, using AM technology, more specifically, the direct metal laser sintering (DMLS) technique. The AM process enables the manufacturing of the fuel nozzle in one single step as opposed to the traditional manufacturing process, which made the fuel nozzle out of 20 different parts that were later assembled into one single unit. Additionally, the design freedom of AM has enabled the engineers to revise and refine the fuel nozzle design, resulting in a 5 times increased fuel delivery system and 25% weight reduction as compared to its predecessor [9]. While others have introduced small AM parts to their large products, Rolls-Royce has been determined to push the boundaries of AM and has printed a 1.5 m (diameter) titanium front bearing housing for a jet engine [10]. Similarly, AM is also widely spread within the automotive industry, from concept modelling, functional testing, direct manufacturing, to production planning. However, the use of AM is still focused on the manufacture of prototypes during the development stage, and manufacturing is limited to small, complex and non-safety-relevant components within a small series, as process reliability and consistency of products is still limited [7]. 2.2. Furniture and fashion industry The growing complexity of shapes and spaces in contemporary design has driven the furniture and fashion industry into adapting AM



[11]. Since the safety compliances for the products developed by these industries are less demanding compared to the aviation and automotive industry, AM has been widely adopted, producing design-driven products that would not have been possible to manufacture using traditional machining technologies [7,12]. 2.3. Dental and medical industry Both the dental and the medical industries are adapting AM technologies for the manufacturing of products mainly due to the fact that individualisation and mass customisation are becoming progressively important, as patients expect custom-size fitting products. The dental industry is experiencing a digital revolution at present, moving away from conventional casting and machining methods to digital dental technology with AM at the forefront of the revolution [13,14]. Using AM, the requirements of individual production can be met, and hand-crafted processes become obsolete, slashing the cost of production by almost 50% [15]. This is mainly due to the efficiency and capabilities of the system on production of customised parts, whereby 450 units of crowns and bridges can be produced per day, as opposed to 20 per day using the conventional casting method [16]. In the medical industry, AM technologies are currently utilised for the manufacturing of medical devices such as implants and prosthetics [17,18], as well as planning tools for surgeries [19,20]. Taking metallic orthopaedic implants as an example, the implant's design can be customised to the patient's anatomy, avoiding the need of manual adjustment of the implant during surgery and potentially diminishing the stress shielding effect (reduction in bone density as a result of removal of normal stress from the bone by an implant) [17]. Leveraging on AM technologies, porosity can be introduced into selected regions of the implant, promoting osseointegration (direct structural and functional connection between living bone and the surface of artificial implant) by way of bone growth into the void spaces within the implants. Such implants have been successfully manufactured and marketed by Ala Ortho S.R.L (Italy) and Lima Corporate S.P.A (Italy). The medical prosthetic sector has also adapted AM technologies, as conventionally made prostheses are often expensive; therefore, replacements/upgrades were often avoided. This especially has an impact on younger patients who need prosthetic replacement as their bodies grow. In these cases, AM has been successful in providing affordable plastic-built prosthetic parts while preserving their functionality. In 2013, the e-Nable community was established to provide free 3D printed prosthetic devices to those who reach out to them [21]. Although AM is gradually penetrating the manufacturing process of different industry sectors, there are yet many challenges ahead, which need to be addressed and solved in order to achieve full integration of AM technologies into the modern manufacturing processes, truly heralding the era of direct manufacturing. 3. Effort to address specific challenges for AM-enable industrial revolution The applications of AM techniques for direct manufacturing in the various industry sectors are the result of combined efforts of academia, industry and the international standards development agencies. 3.1. Standards development for AM technologies To help stimulate research and encourage the widespread implementation of technology, international standards for AM are continuously being developed by the ASTM and International Organisation for Standardisation (ISO). These standards define terminology, specify procedures for measuring the performance of different production processes, ensure the quality of the end products and specify procedures for the calibration of additive manufacturing machines. The establishment of an industrial standardised terminology for AM by the ASTM

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International in 2012 has since benefited the research and development efforts in the field of AM. This resulted in the industrial adaptation of AM technologies, initially as a tool for rapid prototyping and now moving toward direct manufacturing. Prior to the introduction of the ASTM F2792 standard, which defined AM terminology, the term additive fabrication, additive processes, additive techniques, additive layer manufacturing, layer manufacturing, rapid prototyping and freeform fabrication were used interchangeably in the literature to describe the technologies which now fall under the canopy of AM. Under the authority of the working group, the ASTM F2792 has unified the field in respect to terminology. Additionally, the ASTM F42 and the ISO/TC 261 (committee for AM standards) has hosted joint planning sessions in 2013, aligning standards roadmaps for AM, aiming to achieve one set of AM standards to be used all over the world by working in partnership. Perhaps the most significant yield from these joint meetings is the establishment of a common structure which defines multiple levels and a hierarchy of AM standards as shown in Fig. 1 [22]. 3.2. Technology innovations 3.2.1. Electron beam melting (EBM) for stressrelieved metal-printed parts One of the major issues that limit the part quality manufactured through AM processes is the build-up of residual stresses in the printed part. Residual stresses are stresses that remain inside a material, when it has reached equilibrium with its environment [23]. In most cases, residual stresses are unwanted since they result in part deformations. Each production process, including conventional subtractive manufacturing process, introduces some degree of residual stress. However, the amount of residual stress that is introduced varies significantly among different production processes [24]. Taking selective laser melting (SLM) (a form of laser-assisted powder-bed fusion AM, whereby a very thin powder layer is distributed and selectively melted by a controlled laser; this procedure is repeated until a complete part is built) as an example, this process inherently creates a large thermal gradient near the laser spot, giving rise to localised compression and tension, resulting in AM parts with significant residual stresses [24]. Additionally, the thermal gradients present during the building process are affected by many process parameters (part size, build time, powderbed temperature, melt pool size, etc.). The build-up of residual stresses can potentially impact the mechanical performance and structural integrity of AM parts, eventually resulting in failure of the AM parts [24]. Effort has been made to understand the effect of and coupling between each component in the SLM parameter-set with residual stress development, which has in turn prompted the development of process modifications aimed to mitigate the problem of residual stress build-up during the fabrication process. In most cases, SLM printed parts underwent secondary processing by heat treatment to reduce or eliminate the residual stresses [25], consequently increasing the manufacturing cost. An innovative solution was presented to enable printing of stress relieved AM parts. This derivative of powder-bed fusion AM is known as electron beam melting (EBM). In contrast to SLM that utilises laser to melt the substrate, EBM utilises a high power electron beam that generates the energy needed to melt the substrate. Additionally, the EBM process takes place in vacuum and at high temperatures, resulting in stressrelieved AM parts [26]. Although EBM, to a certain extent, can mitigate the issue of residual stresses on AM parts, there is still a lack of control and monitoring of the process to ensure better part quality and manufacturing repeatability. In order for the industries to adopt these technologies in the manufacturing workflow, there is a great need to improve the monitoring, control and feedback mechanisms, enabling production of quality assured parts reliably, leading to the manufacturing of ready-to-use products. Research effort is currently underway to improve the capability of printers to allow real-time monitoring and controlling of the building process in a predictive manner, allowing intervention of the build process and spatial adjustment of the printing


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Fig. 1. Structure of AM standards. Modified and adapted from [22].

3.2.2. Multiple-axes 3D printers To date, most AM printers utilised a 3-axes (X, Y and Z) positioning system. Recently, research efforts have been geared toward development of multiple-axes (N4 axes) positioning systems for AM printers to enable added freedom in fabrication of highly complex geometrical structures with shape overhangs without the need of support materials. At present, multiple-axis AM printer is geared toward metal-based laser-assisted AM printers, reaching commercial level [28–30] and fewer for polymer-based AM printers [31–34]. The capability of multiple-axes printing for such an AM printer is achieved through the rotation of the build platform and/or integration of a robotic arm into the printer hardware setup. The potential of a multiple-axes AM printer is enormous and can enable the true realisation of “manufacturing for design”—the unique capability of AM technologies.

the manufacturing of a finished assembly in one streamlined process. Recently, the convergence of additive and subtractive manufacturing technology has been realised by a German/Japanese company, DMG MORI, enabling the AM of full components in finished parts quality using a single piece of machinery. The technology is comprised of a laser-deposition-welding head and a 5-axis milling head that is interchangeable during the building process, allowing for the direct machining of areas that can no longer be accessed on the finished part. In contrast to DMLS, which builds parts using laser melting of metal in a powder bed, this technology features a metal powder feed system with a deposition rate of up to 1 kg/hour, enabling generation of parts 10 times faster than powder-bed AM technology [28]. More recently, hybrid manufacturing technologies has presented the AMBITTM multitask system (patent pending) which can be integrated into most existing CNC machines or robotic platforms, enabling 3D printing of metal as well as secondary processing (cutting, drilling, marking, etc.) just by a simple tool change [36].

3.2.3. Convergence of subtractive and additive manufacturing Although AM technologies offer many advantages over the traditional machining manufacturing technologies (subtractive manufacturing), AM does possess manufacturing limitations. Among these is the need for the AM parts to undergo secondary processing such as machine milling, blasting, polishing, etc., to give the product a smooth finished appearance as AM-produced parts often have a rough surface [35]. This also means that geometrically complex products would need to be printed in multiple parts to enable the secondary processing prior to assembling into the final finished product. This in turn leads to increased production time and cost. Therefore, it is crucial to integrate both the additive and subtractive manufacturing processes, enabling

3.2.4. Continuous liquid interface production (CLIP) technology For AM to be viable in mass production, print speed needs to be increased by at least an order of magnitude while maintaining excellent part accuracy. Carbon3D has recently showcased their innovative technology termed continuous liquid interface production (CLIP), which is essentially a modified and refined form of stereolithography. With CLIP, an object can be printed continuously due to the presence of an oxygen-permeable window below the ultraviolet image projection plane, creating a persistent liquid interface where photo-polymerisation is inhibited between the window and the polymerising part. They have illustrated that CLIP is capable of reducing part fabrication time while maintaining print resolution (b 100 μm) [37].

parameters to ensure compliance is maintained throughout the build process [27].



4. Additive biomanufacturing 4.1. Convergence of additive manufacturing and tissue engineering and regenerative medicine (TERM) AM has converged into almost all sectors of industries (e.g., aviation, automobile, dental, fashion, furniture, implant and prosthetic), gaining market value as the technologies mature with continuous research and development (R&D) efforts and standards development. Additive biomanufacturing is an upcoming niche within the medical industry, more specifically for the tissue engineering and regenerative medicine (TERM) field, whereby various existing AM technologies were modified and refined to fit its applications and needs. In the last decade, AM has emerged as a prominent technology in the TERM field due to its ability to create geometrically complex scaffolds customised to each individual patient using biodegradable thermoplasts or composites, acting as temporary supporting

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structures in the body to guide tissue regeneration at the defect site (Figs. 2 and 3). However, the regenerative abilities of a scaffold made of thermoplasts or composite are limited as thermoplasts lack bioactive factors to cue the regenerative process at the damaged sites. Therefore, post-processing is often required to incorporate various types of cells and bioactive agents into the scaffold to improve its regenerative capabilities [43]. As the field evolved, AM technologies have been adapted, enabling incorporation of bioactive agents into the scaffolds in a one-step fabrication process. This process is often referred to as tissue printing, cell printing, biofabrication, biomanufacturing or bioprinting within the scientific community. These terms are often used inconsistently or interchangeably, underscoring the need for clarifications of terminologies used in this rapidly evolving field as recently pointed out by Chhaya et al. [44] and Groll et al. [45]. Hence, it is proposed that, for applications of AM in the field of the biomedical sciences, the term “additive biomanufacturing” is used as

Fig. 2. Examples of scaffolds fabricated via additive manufacturing technologies used in large pre-clinical animal models for the evaluation of potential for (A–C) bone and (D–H) breast regeneration. (A) Cylindrical medical grade polycaprolactone (mPCL)-based scaffold implanted (reproduced with author's permission [38]) into (B) sheep segmental defect modal (reproduced with author's permission [39]). (C) Three months post-operatively, bone regeneration was more pronounced in recombinant human-bone morphogenetic protein-7 (rhBMP-7) group compared to scaffold-only and scaffold + mesenchymal stromal cells (MSCs) groups (adapted from [40], Copyright permission obtained from The American Association for the Advancement of Science). (D) Hemisphere-shaped mPCL-scaffold implanted subcutaneously into minipigs for a period of six months. (E–H) Haematoxylin and eosin (H&E) staining shows a long-standing regeneration of adipose tissue along with an extensive vascularisation within the scaffold pores (adapted from [41] with author's permission).


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Fig. 3. Example of scaffolds fabricated via additive manufacturing used clinically for the craniofacial reconstruction. (A–C) medical-grade polycaprolactone (mPCL) sheet moulded into the required shape by the surgeon prior to implantation. (D) Picture showing the implantation of moulded scaffold into a patient with orbital floor fractures. (E and F) X-ray images before and after 2.5 years post-surgery, demonstrating complete bone regeneration at the defect site (adapted from [42] with copyright permission from John Wiley and Sons).

an umbrella term to define the various technologies utilised for the assembling of tissue engineered medical products (TEMPs) layer upon layer.

4.2. Poly(lactides) as biomaterial in additive biomanufacturing The material predominantly used in additive biomanufacturing of TEMPs for the purpose of TERM are predominantly biodegradable polymers (either thermoplastic or photopolymeric). Among all, poly(lactides) (PLA), its copolymer and composites thereof are commonly utilised polymers for the fabrication of scaffolds using additive biomanufacturing techniques [46] to aid bone [47–50], cartilage [51] and adipose tissue [44] regeneration.

4.2.1. Structural composition of PLA Poly(lactides) is a thermoplastic aliphatic polyester with a starting compound of lactic acid. Due to the presence of a chiral carbon atom, lactic acid exists in two optically active stereoisoforms, namely, the L (+) and D (−) enantiomers. Cyclisation of two molecules of lactic acids can give rise to homochiral (D-lactide and L-lactide) or heterochiral lactides (meso-lactide) [52] (Fig. 4). Racemic lactide (rac-lactide) is an equimolar mixture of D- and L-lactides. Using lactic acids or lactides as pre-polymer, PLA can be produced by several methods, including direct condensation polymerisation, azeotropic dehydration polymerisation or ring-opening polymerisation (ROP) (Fig. 4). Very recently, Pretula et. al. [52] and Murariu and Dubois [53] have reviewed the methods for synthesising and characterisation of PLA and PLA composites, respectively.

Fig. 4. Polymerisation route for the production of PLA. Modified and adapted from Auras et al. [54].



Generally, the thermal, mechanical and biodegradation properties of PLA are dependent on the choice and distribution of stereoisomers within the polymer chains. For example, the melting temperature (Tm) of the different lactide stereoisomers are as follows: rac-lactide (122–126 °C) N L-lactide = D-lactide (95–98 °C) N meso-lactide (53–54 °C) [55]. Depending on the choice of pre-polymers and route of synthesis, a vast diversity of PLA (Fig. 5) can be achieved resulting in PLA with a broad range of physicochemical properties. The optical composition of PLA significantly affects crystallisation kinetics and the ultimate extent of crystallinity. In turn, the level of crystallinity developed is particularly influential on the PLA glass transition temperature (Tg), Tm and the degradation rate [56]. PLA with higher L-isomer content has higher optical purity and tends to be semi-crystalline with higher Tm

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as compared to amorphous PLA (lower L-isomer and optical purity) [53, 54,57]. Although derivatives of PLA have been widely fabricated into the form of scaffolds to aid the regeneration of tissue, such as bone [58], breast [59], vasculature [60] and nerve [61] or as drug carrier [62], most scaffolds were fabricated through conventional techniques (e.g., casting, porogen leaching). As the general trend of TERM field moved toward additive biomanufacturing, new compositions of PLAbased biomaterial are constantly under development, taking into consideration the specific AM-technologies requirements for scaffold fabrication processes. Table 1 shows a list of PLA-based biomaterials which have been developed and used for fabrication of scaffolds using AM technologies.

Fig. 5. A variety of microstructure of lactides and PLAs. ROP, ring-opening polymerisation. Adapted from Masutani et al. [55].


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Table 1 List of poly(lactides) (PLA)-based biomaterial used for fabrication of scaffolds using additive manufacturing (AM) technologies. AM technology Melt extrusion

Solution extrusion

Selective laser sintering

Stereolithography

PLA-based biomaterial (a) (b) (c) (d) (a) (b) (c) (d) (a) (b) (c) (d) (a) (b) (c) (d)

Potential application

PLA [64,165,166] P(DLLA-co-CL) [72] P(LLA-co-CL) [166,167] PLA/ silver nanoparticles composite [168] P(LLA-co-CL) [169,170] PLGA [171] PLLA/ TCP composite [172] PLGA/ pearl composite [173] PLA [174] PLGA [175] PLLA/hydroxyapatite [176,177] PDLLA/ribonuclease [178] PDLLA 3-FAME/NVP [179] Methacrylate end-functionalised PDLLA [100,180,181] Methacrylate end-functionalised P(DLLA-co-CL) [100] Methacrylate end-functionalised PDLLA/ hydroxyapatite [182]

Breast scaffold [59,72], surgical suture [167]

Bone scaffold [172,173], nerve guide [170]

Bone scaffold [174–177], Protein delivery [178]

Bone scaffold [182]

PLLA: poly(L-lactic acid); PDLLA: poly(D,L-lactic acid); PLGA: poly(L-lactide-co-glycolide); P(DLLA-co-CL): poly(D,L-lactic acid-co-caprolactone); P(LLA-co-CL): poly(L-lactic acid-cocaprolactone); TCP: tricalcium phosphate; FAME: fumaric acid monoethyl ester; NVP: N-vinyl-2-pyrrdidone

5. Consideration of PLA as biomaterial in additive biomanufacturing The consideration for PLA as material for additive biomanufacturing varies dependent on the choice of technology and tissue-specific requirements. Hence, scientists have to take into account machinespecific limitations and the tissue-specific requirements during the design of polymer intended for TERM based on AM approaches. The variations of AM technologies utilised in the field of TERM have been extensively reviewed by Melchels et al. [63]. When using PLA-based biomaterials for the fabrication of scaffolds using AM technologies, many aspects (e.g., print material supply, storage, printing conditions, post-processing) have to be taken into consideration to ensure that the biomaterial properties are preserved as best as possible throughout the scaffold production processes.

5.1. Print material supply Poly(lactides) are commodity materials which are widely used for making household products (i.e., disposable cutlery, cups, plates, personal hygiene products), packaging (i.e., food/ cosmetics containers) and medical products (i.e., biodegradable orthopaedic implant, sutures, dialysis media, etc.). Generally, for biomedical applications, it is essential that medical-grade polymers are utilised for the fabrication of scaffolds to avoid harmful leachable substances that can cause unwanted adverse reactions. Medical-grade PLA can be obtained from various commercial sources, which is distinguished from “commodity grade” polymer by a greater degree of purity, extensive in vitro and in vivo testing, manufacturing control and regulatory approval. However, due to the stringent requirements in the production plant for the synthesis of medical-grade polymer, it is associated with a great difference in cost (i.e., 10 to 50 $/kg for industrial grade and ~ 3000 to 5000 $/kg for medical grade). In AM, PLA is a commonly used feedstock material in desktop fused filament fabrication-based 3D printers (i.e., Makerbot, Ultimaker, etc.). The relatively cost efficient of these desktop fused filament fabrication-based 3D printers and the ease of sourcing PLA filaments (non-medical grade) have resulted in its wide adaptations by laboratories within the biomaterials and TERM community. This approach is suitable for proof-of-principle studies [59,64,65], surgical guides and models for preoperative planning as well as for prototypes of medical implants [38] (Fig. 6). However, it is in large neglected by the scientific community that medical-grade PLA must be used for any research which aims toward clinical translation of scaffolds, hydrogels and implants.

In the field of additive biomanufacturing, most PLA-based biomaterials (listed in Table 1) are still at the R&D phase. Hence, the polymer was synthesised in batches relatively small scale batches. Inevitably, there exists batch-to-bath variations (i.e., chemical purity) during the production process. Consequently, this may affect the downstream processes and ultimately influence the scaffold properties (i.e., degradation rate, mechanical properties). For example, the presence of non-polymeric content (i.e., metal catalyst residual) compromises the thermal stability of PLA [69–71], resulting in compromised processability using melt-based extrusion process [72,73]. Hence, the implementation of good laboratory practice (GLP) alongside characterisation of each batch of the synthesised polymer in terms of chemical purity, molecular weight, structure and physical properties are necessary to ensure consistency across the different batches of synthesised polymer. Hence, for the production of PLA-based TEMPs using AM technologies, bioengineers would have to consider the supply chain of the raw material (batch to batch variation) to ensure minimal variation in the end product. 5.2. Storage conditions It is known that PLA has the ability to absorb moisture from the atmosphere, resulting in the hydrolysis and cleavage of the ester linkages [74]. Therefore, to minimise the risk of molecular degradation, it is necessary that the storage conditions are highly controlled. Ideally, PLA-based materials should not be exposed to atmospheric conditions; thus, packages should be kept sealed until ready to use. If not entirely used, it should be promptly dried and resealed. In the case of photopolymer (i.e., PLA formulated for stereolithography), the material should be kept in the dark to prevent cross-linking of reactive groups in the polymer chain. Similarly, upon the completion of the fabrication process, scaffolds should be packaged and stored appropriately, for example, the scaffolds can be packaged using moisture-resistance foil liners and/or in an inert gas atmosphere until further use. 5.3. Printing conditions For the fabrication of scaffolds using AM technologies, the crucial parameters include (a) processing temperature, (b) residence time in melt and (c) ambient conditions. In the fabrication of scaffolds using PLA-based biomaterials, one major problem is the limited thermal stability of PLA during the melt processing. The ester linkages of PLA tend to degrade into smaller fractions when exposed to heat and the degradation rate rapidly increases



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Fig. 6. Biomedical applications of non-medical and medical grade poly(lactides) dependent on the end-use. (A–C) The applicability of AM technologies in the biomedical engineering field. (A) A hip implant prototype made of poly(D,L-lactic acid)(PDLLA) (adapted from [38], open access article). (B) A PDLLA scaffolds used for proof-of-principle study for its potential in adipose tissue regeneration (adapted from [59], with Copyright permission from Elsevier). (C) A custom-made mouse/rat bed for animal restrain during magnetic resonance imaging, demonstrating that PLA can be use for the manufacturing of low-cost laboratory consumables using AM technologies (Adapted from [66], with Copyright permission from Elsevier). (D) The ABSORB BVSTM scaffold (Adapted from [67], open access article) and orthopaedic screws and plate (Adapted from [68], with Copyright permission from Springer) made of medical-grade PLA using conventional manufacturing technologies for clinical applications.

above the melting temperature. A study by Taubner and Shishoo on the influence of melt extrusion processing parameters on poly(L-lactic acid) (PLLA) (Tm: 180–250 °C) demonstrated that the processing temperature must be kept at a low level to minimise polymer thermal degradation. At the processing temperature of 210 °C, the loss in Mn (number average molecular weight) was less dependent on the residence time in melt compared to when processed at 240 °C. Additionally, it was found that presence of moisture in the material contributes further to the degradation process [75]. Since the introduction of AM technologies, PLA has been used as building material, especially for melt-extrusion-based 3D printers with a filament feeder system (e.g., Makerbot, Ultimaker, etc.) due to its good thermoplastic properties, which results in good printability.

However, in a filament feeder system, users are limited in terms of material flexibility, whereby a given material needs to be fabricated into the form of filaments prior to the fabrication process. Additionally, the filaments need to be relatively strong to prevent filament slipping during the fabrication process. Hence, other forms of melt-extrusion-based 3D printers (illustrated in Table 2) have been developed with significant improvements in terms of material flexibility. Besides that, materials can be used in the form as it was synthesised, avoiding any preprocessing of polymer prior to the scaffold fabrication process. However, one downside of the non-filament feeder system is that material is kept at the molten stage for an extended period. This is a major limiting factor for PLA-based biomaterials, as it has been previously shown that increased melt resident time of PLA increases the thermal degradation rate [75].


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Table 2 Material flexibility, cell printing capability and system limitation of various feeder system used in melt-extrusion-based 3D printers. Additionally, high voltage electrical field (i.e., melt electrospinning writing) can be applied during the extrusion process to achieved thinner filaments. Melt-extrusion 3D printer

Feeder system Filament

Pneumatic

Description

Machine extrusion unit consist of a filament holding system. Material is converted into molten form just before it is extruded.

Machine extrusion unit Used of pressurised air/gas for the extrusion comprised of a pushing block which pushed the of materials. materials mechanically or pneumatically.

+ Thermoplastic, composites No Require strong filaments

+++ +++ +++ +++ Thermoplastic, composite, hydrogels Yes Yes Yes Yes Thermoplastic and composite: materials remain in molten form for extended period of time

Material flexibility Type of material Cell printing System limitations

Melt electrospinning writing Piston

Screw Machine extrusion unit comprised of a screw head which pushed the materials by rotational force.

Application of high voltage electrical field to achieve thin filaments (5–30 μm) during extrusion. Typically, pneumatic or piston feeder system are utilised.

Thinner filaments.

During the scaffold fabrication process, the ambient processing conditions should be tightly regulated. Liu et al. [76] and Rasselet et al. [77] have reported that the degradation of poly(D,L-lactic acid) (PDLLA) in its molten form proceeds in a random chain scission mechanism and the presence of oxygen has a promoting effect on the thermal oxidation of PDLLA. Hence, polymer processing of hydrolytically and/or oxidatively sensitive polymers (i.e., PLAs) by extrusion or injection moulding is typically performed under inert gas (e.g., argon, carbon dioxide, nitrogen) to prevent extensive degradation [78]. Therefore, a future printer design that would allow fabrication of scaffolds made of PLA-based biomaterials under an inert gas atmosphere would be a significant improvement.

5.4. Sterilisation All scaffolds need to be sterilised, whether for in vitro or in vivo experiments or surgical implantation to reduce the risk of infections. This can be achieved through various sterilisation methods, including but not limited to ethylene oxide, radiation (i.e., gamma, ultraviolet), steam and ethanol. PLA-based scaffolds, in addition to being susceptible to degradation by moisture and radiation, are heat sensitive because of their thermoplastic nature. Thus, the selection of a suitable sterilisation technique for PLAbased scaffolds is crucial to their physical and mechanical properties, and hence to their overall tissue regeneration performance. Sterilisation using 70% (v/v) ethanol has been widely used in laboratory settings as it is readily available in almost all laboratories with cell culture facilities and easy of use. However, at concentrations of 60 to 80% (v/v), ethanol is classified as a disinfectant rather than a sterilisation agent because of its inability to destroy hydrophilic viruses or bacteria spores [79]. Hence, although it has demonstrated apparent effectiveness in preventing infection in cell culture experiments and has minimal effect on the scaffold's morphological characteristics [80], it cannot be use for in vivo applications of biomedical devices. Steam sterilisation techniques commonly involve high moisture and temperature in excess of 100 °C. Such temperature can approach or exceed the glass transition temperature of PLA-based scaffolds, consequently altering the physical and mechanical properties. It was previously shown that steam sterilisation of PLLA induces a significant change in the polymer molecular weight, which would affect the degradation kinetics of the polymer [81]. Sterilisation by gamma (γ) or ultraviolet (UV) radiation may be used for the sterilisation of PLA-based scaffold. However, one must be careful

with the radiation dosage and duration to avoid non-reversible damage. This is because radiation can initiate polymer cross-linking or breakage of polymer chains leading to substantial change to the polymer properties [82]. Chemical sterilisation by ethylene oxide (EO) is often used for polymers that are sensitive to heat and moisture. This is particularly true for PLA-based scaffolds. However, harmful quantities of EO residues may be trapped within the scaffolds' volume, resulting in non-biocompatibility. The amount of gas absorbed into the polymer is dependent on the equilibrium absorption and diffusion coefficient, which differs depending on the polymer compositions and sterilisation parameters [82]. Hence, it is crucial that PLA-based scaffolds are subjected to adequate degassing or aeration subsequent to EO sterilisation to eliminate the residual EO [83]. Various studies have demonstrated that sterilisation of PLA-based biomaterials, regardless of the sterilisation method, to some extent inflicts structural or molecular changes and consequently alters the material properties (i.e., mechanical properties, degradation rate) [80–82,84, 85]. Hence, the sterilisation method should be adjusted dependent on the polymer composition such that the resultant effects are favourable and not detrimental to the end-use. 6. Challenges for additive biomanufacturing Although AM technology has come a long way since its first introduction in the TERM field, there are still many challenges which need to be addressed to establish a new gold standard for the design, optimisation and fabrication of a tissue-engineered construct (TEC) while ensuring functionality. This is because the complexity of the human body has added another dimension of challenges in adoptation of AM in the TERM field as bioengineers not only have to consider the biophysical and manufacturing requirements, yet also the biological requirements to ensure functionality of the fabricated TEC. To achieve complete adoption of AM processes in the TERM field, the TEC must be fabricated rapidly, efficiently and consistently while meeting all stringent functional requirements and FDA safety compliances. The major challenges in additive biomanufacturing are shown in Fig. 7. 6.1. Biomaterials Among the selection of characterised materials commercially available for the different AM technology platforms, from polymers to



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Fig. 7. Challenges for additive biomanufacturing.

ceramics to metals, there is only a limited subset that is suitable for TERM applications. This is because the requirements differ from other industries' requirements as the materials are anticipated to be in direct contact with human tissue for extended periods of time. The materials have to be (1) biocompatible, whereby it evokes host responses appropriate in a specific application with minimal non-specific activity; (2) bioresorbable, where the degradation rate is proportional to the regenerating rate of the target tissues/organ; and (3) can withstand medical sterilisation procedures to prevent infection. Moreover, to enable AM-driven TERM, biomaterials have to be printable. Over the past two decades, although tremendous efforts have been invested in synthesising and characterising biodegradable materials, including polymers (natural and synthetic) [86], bioceramics [87], bioactive glass [88] and composites [89,90] that are suitable for TERM applications, only a select few are suitable for AM processes. Polymers are ubiquitously used across the different AM technologies as they can be synthetically synthesised and modified to suit the requirements of different AM processes. Polymers currently used in additive biomanufacturing can be loosely classified into thermoplastics and photopolymers. Thermoplastics are commonly used in filament/melt-based extrusion and powder-based fusion AM technology segments, whilst photopolymers are usually used in optical fabrication processes. These polymers have all, with a few exceptions, been modified or synthesised specifically for use with a particular AM technique, enabling fabrication of scaffolds with well-defined architectures with predictable physicochemical properties. While these scaffolds could act as temporary support for cell attachment, migration and growth, they are not conducive for direct inclusion of cells during the printing processes. While there are several AM technology platforms (e.g., extrusion printing, microvalve printing, inkjet printing and laser-assisted printing) that can be utilised for bioprinting, there is a lack of suitable biodegradable polymer that fulfils the bioprinting, physiochemical as well as biological requirements. Melchels et al. [91] have developed a new form of biomaterial, the so called “bioink”, in the form of a hydrogel (gelatin–methacrylamide–gellan gum) that can form high fidelity cellencapsulated matrix using AM processes without compromising cell viability. Despite the effort in developing new polymers for additive biomanufacturing, the TERM community faces the same challenges as other industries, whereby the use of polymers for mass production of consumer products by AM processes is prevented due to the lack of confidence by the manufacturer for the reliable reproduction of quality assured end products. This is due to a knowledge gap in the effect of AM building process on the thermal, optical and rheological properties of a given polymer, which can subsequently impact on product performance, e.g., mechanical behaviour. Despite these drawbacks, polymerbased printers have successfully penetrated the consumer market due to their relatively lower cost compared to metal-based printers, whereby hobbyists can purchase a plastic-based printer at $600 and raw material can be obtained for as low as $30 per kg.

In powder-based fusion printers, it is well established that during the fabrication process the polymer has to be maintained in the metastable thermodynamic region (between the melting and crystallisation temperature). However, the optimal metastable thermodynamic region for most polymers is still not clearly defined; moreover, during the building process, the temperature is hardly controllable. This may induce premature crystallisation of the polymer (a non-visible defect), compromising the mechanical properties of printed parts [92]. Additionally, polymers may also experience shrinkage during the AM processes, resulting in a deviation of the final dimensions of the printed part compared to the original design. This can be partly overcome by using higher molecular weight polymers, but can lead to difficulty in the printing process because of the high viscosity involved [93]. Another consideration when using polymers in AM processes is their thermal degradation over time, which can in turn influence the polymer molecular weight and the AM-printed part quality. Thus, an optimum polymer molecular weight range does exist for AM processes, but it is not easily controllable [93]. Moreover, in bioprinting, inclusion of bioactive agents or cells during the printing process may also influence the biomaterial properties which needs to be identified and characterised to ensure no detrimental effects to the biomaterial properties. Currently, there is an array of biocompatible and bioresorbable materials that can be utilised for production of TE products using AM technologies and scientists are continuously developing new biomaterials. Despite all the newly developed AM-printable biocompatible and biodegradable biomaterials, there is a lack of databases on mechanical properties of AM-fabricated parts and the interaction between materials and process parameters. In metallurgy, it takes about 10 years to develop a new alloy, including the determination of various critical properties such as fatigue strength. This time frame also applies to developing new materials for additive biomanufacturing, which have different requirements dependent on the target tissue to be regenerated. 6.2. Computer-aided design, engineering and manufacturing In TERM, scaffold design, modelling and manufacturing are crucial steps as the internal architecture greatly influences key factors for tissue regeneration, such as nutrients diffusion, cell adhesion and matrix deposition. Additionally, the degradation rate and the mechanical properties of the scaffold vary dependent on the scaffold's internal architecture. Therefore, scaffolds intended for TERM applications have to be carefully designed, keeping in mind the case-specific mechanical, mass transport and biological requirements. However, designing a scaffold that fulfils such conflicting requirements, such as the biological and mechanical ones, still remains a challenging issue. If AM is employed to overcome these complex design challenges, it becomes important to not only identify the specific manufacturing capabilities of AM, but also the technological challenges. Although these capabilities and constraints vary depending upon the AM process being used, there is one manufacturing constraint common to all extrusion-based AM


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Fig. 8. Digital product development workflow.

processes, that is, the deposition nozzle must remain normal to the build surface. This results in accessibility constraints as collisions with the part being printed must be avoided at all costs. Moreover, this limitation also prevents the fabrication of highly complex free-form structures without the use of sacrificial support structures. In order for the fabrication of scaffolds/TECs, first, a digital representation of the scaffold/ TEC has to be established. Fig. 8 shows a digital product development workflow that could be adapted for additive biomanufacturing. Generally, the acquisition of 3D models from 2D clinical scan data is a well-established method that can be achieved using specific computer software (i.e., InVesalius or Mimics), resulting in the growing clinical use of customised metallic implants [18,94]. Detailed methodology for the conversion of 2D clinical scans data to 3D model using InVesalius (open-source) is presented by Jardini et al. [18]. 6.2.1. Computer-aided design (CAD) Currently, there are 2 major classes of CAD tools—Parametric Modelling and Boundary representation (B-rep) modelling. Parametric modelling (e.g., Solidworks and Autodesk Inventor) use parameters such as model dimensions, features and material density to describe a 3D model [95]. Such parameters can be modified later, which causes the entire model to be updated automatically. In such software, features describe a part, while an assembly is described by a collection of parts. On the other hand, B-rep modelling (e.g., Rhino3D) generally represents solid models as a watertight shell of zero-thickness surfaces [96]. If the model is not watertight, the software has difficulty with distinguishing the “inside” of the solid model from the “outside”. While both these approaches are elegant methods to represent conventional products or components, they do not allow for fabrication of complex lattice-based networks that can typically be manufactured using AM. A single strut in a lattice-network may easily be represented as a small extruded feature (parametric) or a few surfaces (B-rep), but even a moderately sized lattice structure composed of thousands of such struts becomes so computationally demanding that it renders the use of such approaches unfeasible. Especially in case of B-rep software, such a large number of struts increases the probability of non-manifold errors occurring (e.g., gaps between polygons or self-intersecting structures), which compromise the watertight boundary. Therefore, in additive biomanufacturing, parametric or B-rep modelling can be useful in setting the overall-shaped (macro-architecture) of the scaffold/TECs but may limit the design of the scaffold's internal geometry (micro-architecture), which is crucial for determining the scaffold/TECs' mechanical and mass transport capabilities and ultimately the tissue regeneration capability. Generative design methods, whereby a design is generated by a set of rules or an algorithm, are commonly used in the fields of sound engineering, animation, communication design and architectural modelling [97]. Natural design processes such as through genetic mutations and crossovers can also inspire such generative designs by using a genetic

algorithm [98,99]. Often, building on the parametric or B-rep modelling concepts, generative design transforms the computer from a modelling assistant to a generator through the use of a defined set of rules or an algorithm. Making small modifications in the values fed into these equations radically alter the entire geometry of the 3D model, allowing for rapid generation of an entire family of designs, which can be tested either computationally or mechanically to choose the optimum design candidate. Indeed, the last few years have seen the emergence of a multitude of scripting and modelling tools that allow for generative design approaches (e.g., Grasshopper Plugin for Rhino3D, Processing, Quartz Composer, etc.). Although such software have made it relatively easy for non-programmers to implement their ideas, a generative designbased CAD modelling software, specifically designed for complex additive biomanufacturing remains elusive. Indeed, in the field of additive biomanufacturing, generative design methods have been adapted [100,101] to enable better control over the micro-architecture design of a scaffold and/or a TEC. However, the implementation of generative design method in CAD modeller software for generation of the scaffolds' internal micro-architecture requires high computational power. Additionally, fitting a series of unit cells along an anatomical-shaped contour can be mathematically challenging and exponentially increase the computational power required. Therefore, repeating unit cells that make up the micro-architecture of a scaffold is usually “filled” into the overall scaffold's macro-architecture using Boolean operations, producing a scaffold CAD model with the desired micro-architecture [102–106]. Another shortcoming of current CAD tools is the lack of integration with interactive design tools that can help designers to visually conceptualise the design in an environment closely mimicking the real world situation. Interactive design tools such as augmented reality (AR) and virtual reality (VR) can greatly enhance the human-computer interface in product design [107,108]. Currently, in the medical sector, such AR and VR technologies are being explored for simulation-based medical education [109] and as aid for surgeons in pre-operative planning [110,111]. In the context of additive biomanufacturing, AR and VR can aid in the scaffold design process, whereby bioengineers with a minimal knowledge of human anatomy can superimpose the scaffold CAD model to an anatomical relevant site (defect site) thus helping bioengineers in visualising the practicality of the scaffold overall geometric design in a real world application. 6.2.2. Computer-aided engineering (CAE) For the past decades, “trial-and-error” approaches have been used to study different scaffold architectures by conducting in vitro and in vivo experiments. The cost (labour, time, money) involved in this approach is rather inefficient, thereby driving the field toward adaptation of computer-aided engineering (CAE) into the scaffolds/TECs manufacturing workflow to enable optimisation of the scaffold design in silico, identifying the most suitable configuration of scaffolds for the replacement of a desired tissue.



Among the in silico strategies, finite element analysis (FEA) has enabled the simulation of the mechanical behaviour of a given scaffold design. Using the simulation result, bioengineers and scientists can make changes to the scaffold design to achieve the required mechanical properties. Currently, FEA can be done using the scaffold CAD model or a 3D model obtained from microCT reconstruction of additively manufactured scaffolds. Several studies have demonstrated that the theoretical prediction of the porous scaffold's mechanical behaviour using the CAD-based approach is comparable to the experimental results [100,112,113]. Despite this, there is still a standing debate on the accuracy of CAD-based modelling due to the discrepancies between the intended design and the final shapes of the additively manufactured objects. These discrepancies arise during the fabrication process. They include unplanned surface roughness, micropores, residual stresses, etc., which are still poorly understood [114]. As a consequence, some have opted for the scaffold 3D model obtained from microCTreconstruction for simulation of the scaffold mechanical behaviour [115,116]. Another consideration from a design point of view is the mass transport properties of the scaffolds. Bioengineers aim to compute and model the effective diffusivity of a given scaffold design as illustrated by Jung et al. [117]. However, the prediction of the scaffold's permeability is not adequate, as it does not take into consideration the fluid dynamics within and around the scaffold. For example, when culturing cells on large-sized scaffolds and/or TECs, bioreactors are needed to aid the perfusion of media (nutrients and waste) through the core of the scaffolds and/or TECs to ensure cell viability. Consequently, this could create a gradient of shear rate throughout the scaffold length that could positively or negatively impact cellular behaviour. To account for the dynamic fluid movement around and within the scaffold, computational fluid dynamics (CFD) has been applied to study the shear stress distribution across the scaffold [118–120]. However, to date, only a few studies have found a correlation between CFD results and scaffold internal architecture [121] or cell behaviour [122]. Computation simulation in the field of TERM is slowly moving toward the integration of scaffold performance over time during the tissue regeneration processes, which can be 2 to 3 months in the case of skin regeneration and 6 to 9 months in the case of bone regeneration [123–125]. With the simulated result, one can adjust the design to obtain an optimal scaffold architecture corresponding to the tissue regeneration rate. Since the effect of vascular supply also plays a crucial role in tissue regeneration, a computational model based on mechanical environment and local vascularity has also been developed [126], and there are a number of approaches to integrate the engineering of perfusable vascular networks inside the TEC to improve the early connection to the circulation [127]. Although various simulation models have been established to validate of the scaffold capabilities in silico, most of the proposed models have not been validated with experimental results. This is most likely due to limiting factor such as printer availability and printability of the proposed scaffold design. To enable adaptation of a specific simulation model into the scaffold/TECs design workflow, the simulation model has to be validated with extensive in vitro and in vivo experiments to ensure the theoretical assumptions of the model correlate well with the physiological conditions. As previously mentioned, conflicting requirements have to be simultaneously addressed in the design of scaffold and/or TECs, e.g., high porosity is preferable for increased mass transport, yet, as porosity increases, the scaffolds' mechanical properties lowered. To overcome this challenge, design strategies capable of finding the optimal trade-off between these two opposite requirements has been proposed by Hollister's group [128–130] and Almeida and Bartolo [131]. Going beyond the computational prediction of scaffold properties (mechanical and mass transport), they combined in silico modelling with topological optimisation to enable better automation of the design process by taking into account the functional requirements. With their approach, the

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design process is partially automated, whereby the unit cell/architecture is introduced into the scaffold to attain the desired properties based on given constraints. 6.2.3. Computer-aided manufacturing (CAM) The use of computer systems in a non-design activity but in the manufacturing process is called computer-aided manufacturing (CAM) [132]. Typically, a CAM system acts as an interface between CAD and the manufacturing machine. The complex drawing created by CAD tools is “translated” into code of letters, numbers and special characters (e.g., G-code) that is recognisable by the machine. As the digital technologies evolve rapidly, today's CAM systems utilised by conventional subtractive machining-based manufacturing industries are capable of planning, scheduling, monitoring, decision making and generally managing all the aspects of the manufacturing procedure, even to “think” and adapt to changes automatically. This advanced CAM system capability is yet to be integrated into the AM-based manufacturing lifecycle. The inherent complex interaction of the AM process parameters (e.g., stage and print head travel speed, translation path, material feed rate, pressure, temperature, laser power, etc.) and the resultant physical phenomena (e.g., melting/solidification of material, heat and mass transfer, moving heat source, etc.) complicate the development of process-property relationships and appropriate process control. Thus, an effective in-process simulation model will be very useful for preassessing the impact of process parameters and predicting optimised process conditions. It can decrease the need for real world testing of technologies and processes and give product designers a predictive capability. Models are also the bases for developing the required control technologies (hardware and software) for AM production processes. They will also provide support for standards development as qualification and certification methods [133]. For the development of an accurate in-process simulation model, comprehensive and validated data on materials and processes are mandatory, as well as an excellent understanding of the fundamental processes and physical phenomena that underlay AM feedstock inputs, approaches and technologies. The adoption of AM in the aviation and automotive industry has pushed for development of in-process simulation models to achieve an optimised trade-off between fast processing time and relatively stress-free structures with good microstructural and mechanical integrity. As the aviation and automotive industries predominantly use powder-fusion-based AM technology, most of the simulation models are performed for the printing of metallic parts. Currently, various process and material models have been proposed, addressing phenomena such as heat transfer [134], melting/solidification phase change [134, 135], free-surface flow [135] and residual stresses [136,137], which are closely related to the mechanical properties of the final AM printed-part. Martukanitz et al. [138] has described the AM process for metallic materials by integrating two computational simulation modules using an “uncoupled” approach, which allows each submodule to be independently developed (as long as a consistent data exchange format and consistent units and scaling are used). Such an approach can be intertwined with the existing workflow of fabricating AM products, starting from the commonly performed CAD model slicing technique to generate the layer geometries. Martukanitz's model proposes using the motion of the extruder head (or laser source in case of direct metal laser sintering) as the primary heat source and mapping the motion of the extruder head to perform the thermo-mechanical simulation of the rapidly changing conditions within the AM machine. The output file of such an operation will include, in addition to the movement coordinates of the extruder, head, time, temperature, displacement and stress for each computational node/element within the model. This exported file, referred as “TTSP” (time, temperature and stress at position), can be fed directly into another microstructural simulation submodule, which tracks the evolution of the plastic/metal microstructure at positions of interest within the build. The authors also propose sophisticated process models and material models. However, discussions of these fall beyond the


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scope of this report. Interested readers are advised to refer to the original source [138] for further information. Despite the efforts in developing an accurate simulation model for the entire AM fabrication process, most existing models lack the capabilities to couple AM design, materials selection and manufacturing processes. It is of desire for the development of dynamic and “intelligent” simulation models that can obtain in situ measurements during the AM building process, predicting structural properties and detecting potential structural defects, which in turn provides real-time feedback for process control. In order for the realisation of such a dynamic model, it is crucial to develop a technology that can enable accurate and reliable in-process measurements and non-destructive inspection methods. Moreover, to better support effective development of modelling and simulation tools for AM processes, standards need to be established to support consistent data input due to the diversity of AM equipment and process types. 6.2.4. CAD/CAE/CAM digital data management At this point, it becomes important to discuss the file format that allows the digital exchange of information among CAD, CAE and CAM systems. The first-ever vendor neutral standard on computer graphics exchange was the initial graphics exchange specification (IGES), championed by the United States Air Force (USAF) Integrated Computer-Aided Manufacturing (ICAM) project to integrate all operations in aerospace manufacturing in order to close the gap between parts design and manufacturing. A serious issue, at the time, was the incompatibility of the data produced by the CAD software with the numerically controlled (NC) machine tools used to manufacture the parts. IGES solved this problem by introducing a common file format through which two seemingly disparate computer systems could communicate with each other. IGES has since been replaced with ISO 10303 Standards for the Exchange of Product (STEP) model data. IGES was developed primarily for the exchange of pure geometric data between CAD and NC machine, whereas STEP is intended to handle a much wider range of product-related data covering the entire life cycle of a product [139]. Although the STEP standard has been in continuous development since 1984 as a successor to IGES, it has mainly been designed to work with specific CAD software (parametric and B-rep) and CAE software. Consequently, it does not adequately support complex 3D surfaces, materials, lattices and tessellation that are hallmark features of the additive biomanufacturing technology. Furthermore, modern AM machines do not natively support slicing of STEP files into machine tool paths. On the other hand, the newly emergent Additive Manufacturing File Format (AMF) (ISO/ASTM 52915:2013 standard [140]) does contain all of these features. However, it is not compatible with complex CAE modelling systems such as ANSYS, Abaqus, Hypermesh, etc. The authors therefore advocate a merging of STEP and AMF standards to create a standard file format appropriate for the entire workflow of AM-based CAD to CAE to CAM. Throughout the digital product development workflow, computational simulation plays a major role, from CAD to CAE to CAM. A recent review by Mourtzis et al. [108] gives a good overview of the various simulation methods and tools to product and production lifecycles. Among which augmented reality (AR) and virtual reality (VR) technologies seem to be an interesting avenue that is yet to be explored in the additive biomanufacturing field. 6.3. AM and additive biomanufacturing hardware Over the years, scaffold-based TERM approaches have evolved into three general trends: scaffold fabrication, cell printing or a combination of both. As opposed to scaffold fabrication, cell printing involves additional complexities, such as the choice of cell types, growth factors and the sensitivities of cell or growth factors to the fabrication process. The current trend in the field is a multiphasic scaffold design which is based on the accumulated knowledge from studying relevant scaffold

literature and implementing key design parameters into the build of an architecture and morphology, which allows cell migration, proliferation and subsequently vascularised tissue formation. 6.3.1. Manufacturing tools After over two decades of intense R&D in the field of AM technologies, it can be concluded that the hardware design of most AM printers has reached a certain maturity. Additive biomanufacturing of scaffolds can be achieved through the various AM technology segments, each with their respective pros and cons. These have been extensively described and discussed in the review articles by Murphy and Atala [141], Melchels et al. [63], Mota et al. [142] and Bártolo et al. [143]. Dependent on the availability of the desired biomaterials and the intended application, one particular AM system may be better than the others. From the perspective of additive biomanufacturing on a research scale, one major disadvantage of most commercial AM printers is the lack of flexibility in adapting for variety of biomaterials (i.e., new formulation of polymer as candidate biomaterials). Moreover, most AM printers require a relatively large quantity of biomaterial to be loaded on the printers' feeder/material chamber in a specific form (filament, powder or photo-cross-linkable solution) to enable scaffold fabrication. During the fabrication process, biomaterials may undergo thermal or oxidative degradation; therefore, reuse of biomaterial is not permitted as it may have detrimental effects on the scaffold's quality and performance, leading to unnecessary wastage of expensive or rare biomaterials. Therefore, existing AM printers are being modified to facilitate also additive biomanufacturing. For example, feeding system using a syringe-like design [144] or ink jet methodology [145,146], instead of a filament feeding system. Such systems allow for fabrication of scaffolds with relative freedom of choice of biomaterials to be used. Additionally, the estimated necessary volume of the biomaterial can be loaded into the feeder, eradicating biomaterial wastage in large. In terms of cell printing, the main technologies used are inkjet, microextrusion and laser-assisted printing systems, which have been described by Murphy and Atala [141]. When designing parts for cell printing, engineers have to take into consideration the biological requirements, whereby the environment has to be precisely controlled under good manufacturing practices (i.e., temperature, humidity and sterility). As an example, the temperature has to be maintained at physiological temperature to minimise the risk of cell death during the fabrication process since any temperature fluctuation may have detrimental effects on the cell viability. During the construction of scaffold/cell constructs, the spatial distribution of cells and biomolecules across the architecture is crucial to better mimic the complex structure of tissues and organs, which consist of multiple types of cells with distinct hierarchical arrangements. Various research groups have proven the capabilities of bioprinters to deliver constructs with defined placement of cells and biomaterials [147–149]. Although bioprinters theoretically permit the printing of complex, multi-material biological constructs, there is one common downfall across all the bioprinters—the print speed. In bioprinting, time is crucial, as prolonged printing time may exponentially increase the risk of cell death. Thus, to date, cell printing is still limited to fabrication of constructs with relatively small dimensions. Therefore, to further advance bioprinting, innovative solutions in terms of hardware design are necessary. One obvious way to further advance cell printing is to significantly improve the print speed while not compromising the resolution. Alternatively, engineers have to come up with innovative hardware design solutions that converge bioprinting with bioreactor technologies to enable printing of large size constructs while maintaining the nutrients and waste transport across the architecture to ensure cell survival through the prolonged fabrication period. 6.3.2. In-process monitoring tools The AM machine itself and the process variability during the fabrication process can negatively impact the quality of the printed part. This



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Table 3 Comparison of pyrometers and thermocouples as tools for in-situ temperature measurement. Summarised from [151].

Advantage

Disadvantage

Pyrometers

Thermocouples

• • • • • • • •

• • • • • •

Contact-free measurement Capable of detecting radiation emitted by moving object within focus boundary Permit high spatial and temporal resolution measurement Temperature range: 0–2000 °C Expensive Large size Difficulty in determining the radiation emissivity of monitored object Require high computational power for data processing

means that qualification and certification are significant challenges for widespread adoption of AM. Recently, numerous industry reports have called for real-time, close-loop process controls and sensors to ensure quality, consistency and reproducibility across AM machines [150]. The overall goal is to achieve a robust layer-by-layer quality assessment that will eliminate post-build inspection, achieving a state of certify-as-youbuild with AM technologies. At present, the development of in-process monitoring tools emphasises on temperature monitoring with a dominant focus on metal-based additive manufacturing [151–153]. Pyrometers and thermocouples are generally used for temperature monitoring. Pyrometer is a broad term describing contactless sensor devices that measure temperature of a body based upon its emitted thermal radiation (e.g., photodetectors, digital cameras with charged-coupled device or complementary metal-oxide semiconductor technologies) [151]. On the other hand, thermocouples take contact temperature measurements. Thermocouple consists of two wires connected together at one end with a voltage measurement device connected across the free ends. The working principle is that electric current flows in a closed loop of two dissimilar metals when their junctions are at two different temperatures. Hence, when the connected junction (point of contact for measurement) is at a specific temperature, a voltage difference (or electromotive force) dependent on the temperature at the joint is created between the free ends of the wires [154]. The respective advantages and disadvantages for use of pyrometer and thermocouple for temperature measurement are listed in Table 3. Besides temperature measurement, a pyrometer device equipped with CCD-based digital camera has also been used for monitoring layer height during the AM process [155–157]. Another form of sensor

Less expensive compared to pyrometers Do not require external power source Small size Temperature range: 0–1450 °C Contact measurement Delayed reaction time in detecting temperature fluctuation

used for monitoring layer height during the AM fabrication process is the displacement sensor (also commonly known as distance or proximity sensor) [158,159], a device that detects presence of objects without physical contact. It consists of two parts: a transmitter that sends a laser signal and a receiver that collects this signal. Its operating principle is measuring the time it takes the signal to be sent, hit the monitored surface and return to the receiver. Next, it translates this into a distance between the sensor and the surface it is intended to measure [151]. To date, almost all research efforts in developing in-process monitoring tools are focused on simple geometries, which override one of the most powerful aspects of AM—the freedom of design geometries. Thus, more R&D needs to be planned and executed toward monitoring and control of geometrically complex structures, i.e., lattice structure—that is predominant in TERM applications. To date, very few research groups have looked into relatively more complex geometries for in-process monitoring and control [160,161]. Moreover, there is a lack of R&D effort in developing in process monitoring and control for polymer-based AM technologies. 6.4. Systems integration Systems integration, when introduced into the AM industry, has the potential to replicate physical transformation process with standardised computer models and simulations – reducing cost, ensuring material quality, dimensional attributes, developing process metrics and product acceptance [138,162]. Indeed, the creation of a part by means of AM is quite intricate. During the AM process, different sub-processes are necessary and the boundaries that define these sub-processes may differ

Table 4 Technological Issues in additive manufacturing. Materials

Design

Computation modelling

Sensing and control

• • • • •

Development of new materials for AM processes Methods for materials mixing and formation to achieve the desired composition (e.g., composite, viscosity) and forms (e.g., powder, ink, slurry, filament) Understand the interaction between materials and processes. Development multi-functional design methods and tools to ease the design of part with complex geometries (macro-architecture) Enable inclusion of specific features (micro-architecture) (e.g., unit cells structures, gradient porosity/ pore sizes) and other design variations (e.g., multiple and gradient materials). • Establishment of mathematical computational models for: (a) temperature, stress, and composition history for understanding transport phenomena in AM processes (e.g., melting and recrystallisation behaviour of polymers) (b) prediction of microstructures and fatigue properties resulting from fibre reinforced design (c) multi-scale modelling for more accurate prediction of complex process-structure-property relationships (d) modelling of layer-to-layer bonding between homogeneous and heterogeneous materials, and (e) reduction of complex process models to lower-order models for the purpose of real-time control of AM processes. • Development of real-time in-process sensing tools, which include but not limited to: (a) optical measurement of geometric dimensions and surface quality of finished layers, (b) in-process multi-band spectroscopic analysis of AM by-products

Process innovation System integration

• • • • • •

Understanding the correlation between computational model predictions and AM processes (temperature, humidity, residual stresses, etc.) Integration of real-time sensing and closed-loop control of AM processes. Establishment of a streamline digital product manufacturing workflow Improve the AM material deposition rate by orders of magnitude for fabrication of large-scale and/or large volume parts. Integration of interdisciplinary knowledge rooted in fundamental sciences for AM system development Establishment of cyberspace-enabled and cloud-based sharing of AM and other innovative manufacturing resources.


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depending on the perspective taken. To enable production of scaffold and/or TEC by mean of additive biomanufacturing, the sub-processes must be well integrated in order to fulfil the scaffold and/or TECs performance requirements. Witherell's group at the National Institute of Standards and Technology has identified six key areas for the development of information system architecture tailored for AM [163], including (1) “Design information- design intent, design rationale, material selection and performance requirements/constraints”, (2) “Geometry information- the preservation of shape and features (including GD&T) during designto-product transformations”, (3) “Process information- how in situ measurements can be fed back into the digital thread for validation and verification”, (4) “Material information- the role of material information and material properties in an overall AM systems architecture”, (5) “ Traceability- the information requirements necessary to verify and validate an AM part throughout design-to-product transformations” and (6) “Disruptive technologies- the information challenges/ opportunities in developing technologies, including topological optimization and part regeneration”. The efforts by the group also support the information requirements for verification and validation techniques, complementing design rules currently covered under ASTM F42 [163]. Recently, the group has proposed a workflow for AM digital information management to enable efficient and consistent digital thread transitions through the AM sub-processes—from design-to-product. The improved information management will allow for more transparent information exchange between the different AM sub-processes, ultimately supporting the notion of quality control throughout the development, manufacture and qualification of an AM part [164].

7. Future outlook From the broader AM technologies perspective, future research should focus on issues listed in Table 4 to enable translational research in AM technologies to real world applications. In the field of additive biomanufacturing, in addition to the technological barriers listed in Table 4, greater research efforts are needed to expedite the transformation from simple fabrication of scaffolds toward cell printing using bioinks. For fabrication of scaffold for TERM purposes, the research programme should focus on Designification & Scaffoldnification, which includes (a) biophysical requirements—scaffolds should inherit a sculpturous structural design, strength stability, degradation and cell-specific microarchitecture (e.g., pore shape, size and porosity); (b) biological requirements—cell loading density and spatial distribution, as well as cell attachment, growth and new tissue formation; (c) mass transport considerations—pore size, porosity, pores interconnectivity; (d) anatomical requirements – anatomical compatibility and geometry fitting; and (e) manufacturability requirements – process ability (e.g., biomaterial availability, printing feasibility, etc.) and process effects on the final printed part (e.g., residual stresses, material shrinkage, etc.). On the other hand, cell printing research should focus on (a) the development of a new generation of biomaterials in the form of bioink that can simultaneously act as cell delivery matrix, cell support and biomolecule to guide cell functionality; (b) converging the expertise from the field of developmental biology and biomechanical engineering to fill the biological knowledge gap; (c) expand the commercialisation of either the individual bioprinting tools or the entire additive technology platform to accelerate the maturation of the additive biomanufacturing field, enabling the fabrication of 3D heterogeneous structure in a viable, reliable and reproducible manner; and (d) explore four-dimensional (4D) bioprinting models (embedded time into the 3D bioprinting models) to include cells with controlled release of biomolecules for complex tissues, organs, cellular machines and human-on-a-chip devices.

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