High throughput methods applied in biomaterial development and discovery

Fungal Attachment-Resistant Polymers for the Additive Manufacture of Medical Devices

This study reports the development of the first copolymer material that (i) is resistant to fungal attachment and hence biofilm formation, (ii) operates via a nonkilling mechanism, i.e., avoids the use of antifungal actives and the emergence of fungal resistance, (iii) exhibits sufficient elasticity for use in flexible medical devices, and (iv) is suitable for 3D printing (3DP), enabling the production of safer, personalized medical devices. Candida albicans (C. albicans) can form biofilms on in-dwelling medical devices, leading to potentially fatal fungal infections in the human host. Poly(dimethylsiloxane) (PDMS) is a common material used for the manufacture of medical devices, such as voice prostheses, but it is prone to microbial attachment. Therefore, to deliver a fungal-resistant polymer with key physical properties similar to PDMS (e.g., flexibility), eight homopolymers and 30 subsequent copolymers with varying glass transition temperatures (Tg) and fungal antiattachment properties were synthesized and their materials/processing properties studied. Of the copolymers produced, triethylene glycol methyl ether methacrylate (TEGMA) copolymerized with (r)-α-acryloyloxy-β,β-dimethyl-γ-butyrolactone (AODMBA) at a 40:60 copolymer ratio was found to be the most promising candidate by meeting all of the above criteria. This included demonstrating the capability to successfully undergo 3DP by material jetting, via the printing of a voice prosthesis valve-flap using the selected copolymer.

Targeting Macrophage Polarization for Reinstating Homeostasis following Tissue Damage

Tissue regeneration and remodeling involve many complex stages. Macrophages are critical in maintaining micro-environmental homeostasis by regulating inflammation and orchestrating wound healing. They display high plasticity in response to various stimuli, showing a spectrum of functional phenotypes that vary from M1 (pro-inflammatory) to M2 (anti-inflammatory) macrophages. While transient inflammation is an essential trigger for tissue healing following an injury, sustained inflammation (e.g., in foreign body response to implants, diabetes or inflammatory diseases) can hinder tissue healing and cause tissue damage. Modulating macrophage polarization has emerged as an effective strategy for enhancing immune-mediated tissue regeneration and promoting better integration of implantable materials in the host. This article provides an overview of macrophages' functional properties followed by discussing different strategies for modulating macrophage polarization. Advances in the use of synthetic and natural biomaterials to fabricate immune-modulatory materials are highlighted. This reveals that the development and clinical application of more effective immunomodulatory systems targeting macrophage polarization under pathological conditions will be driven by a detailed understanding of the factors that regulate macrophage polarization and biological function in order to optimize existing methods and generate novel strategies to control cell phenotype.

Exploring the Performance of Linear and Nonlinear Models of Time-of-Flight Secondary Ion Mass Spectrometry Spectra

Multivariate statistical tools and machine learning (ML) techniques can deconvolute hyperspectral data and control the disparity between the number of samples and features in materials science. Nevertheless, the importance of generating sufficient high-quality sample replicates in training data cannot be overlooked, as it fundamentally affects the performance of ML models. Here, we present a quantitative analysis of time-of-flight secondary ion mass spectrometry (ToF-SIMS) spectra of a simple microarray system of two food dyes using partial least-squares (PLS, linear) and random forest (RF, nonlinear) algorithms. This microarray was generated by a high-throughput sample preparation and analysis workflow for fast and efficient acquisition of quality and reproducible spectra via ToF-SIMS. We drew insights from the bias-variance trade-off, investigated the performances of PLS and RF regression models as a function of training data size, and inferred the amount of data needed to construct accurate and reliable regression models. In addition, we found that the spectral concatenation of positive and negative ToF-SIMS spectra improved the model performances. This study provides an empirical basis for future design of high-throughput microarrays and multicomponent systems, for the purpose of analysis with ToF-SIMS and ML.

Intelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications

Materialomics integrates experiment, theory, and computation in a high-throughput manner, and has changed the paradigm for the research and development of new functional materials. Recently, with the rapid development of high-throughput characterization and machine-learning technologies, the establishment of biomaterialomics that tackles complex physiological behaviors has become accessible. Breakthroughs in the clinical translation of nanoparticle-based therapeutics and vaccines have been observed. Herein, recent advances in biomaterials, including polymers, lipid-like materials, and peptides/proteins, discovered through high-throughput screening or machine learning-assisted methods, are summarized. The molecular design of structure-diversified libraries; high-throughput characterization, screening, and preparation; and, their applications in drug delivery and clinical translation are discussed in detail. Furthermore, the prospects and main challenges in future biomaterialomics and high-throughput screening development are highlighted.

OH End-Capped Silicone as an Effective Nucleating Agent for Polylactide-A Robotizing Method for Evaluating the Mechanical Characteristics of PLA/Silicone Blends

Current research on materials engineering focuses mainly on bio-based materials. One of the most frequently studied materials in this group is polylactide (PLA), which is a polymer derived from starch. PLA does not have a negative impact on the natural environment and additionally, it possesses properties comparable to those of industrial polymers. The aim of the work was to investigate the potential of organosilicon compounds as modifiers of the mechanical and rheological properties of PLA, as well as to develop a new method for conducting mechanical property tests through innovative high-throughput technologies. Precise dosing methods were utilized to create PLA/silicone polymer blends with varying mass contents, allowing for continuous characterization of the produced blends. To automate bending tests and achieve comprehensive characterization of the blends, a self-created workstation setup has been used. The tensile properties of selected blend compositions were tested, and their ability to withstand dynamic loads was studied. The blends were characterized through various methods, including rheological (MFI), X-ray (XRD), spectroscopic (FTIR), and thermal properties analysis (TG, DSC, HDT), and they were evaluated using microscopic methods (MO, SEM) to examine their structures.

A facile one step route that introduces functionality to polymer powders for laser sintering

Laser Sintering (LS) is a type of Additive Manufacturing (AM) exploiting laser processing of polymeric particles to produce 3D objects. Because of its ease of processability and thermo-physical properties, polyamide-12 (PA-12) represents ~95% of the polymeric materials used in LS. This constrains the functionality of the items produced, including limited available colours. Moreover, PA-12 objects tend to biofoul in wet environments. Therefore, a key challenge is to develop an inexpensive route to introduce desirable functionality to PA-12. We report a facile, clean, and scalable approach to modification of PA-12, exploiting supercritical carbon dioxide (scCO2) and free radical polymerizations to yield functionalised PA-12 materials. These can be easily printed using commercial apparatus. We demonstrate the potential by creating coloured PA-12 materials and show that the same approach can be utilized to create anti-biofouling objects. Our approach to functionalise materials could open significant new applications for AM.

Beyond Encapsulation: Exploring Macrophage-Fibroblast Cross Talk in Implant-Induced Fibrosis

The foreign body response (FBR) and organ fibrosis are complex biological processes involving the interaction between macrophages and fibroblasts. Understanding the molecular mechanisms underlying macrophage-fibroblast cross talk is crucial for developing strategies to mitigate implant encapsulation, a major cause of implant failure. This article reviews the current knowledge on the role of macrophages and fibroblasts in the FBR and organ fibrosis, highlighting the similarities between these processes. The FBR is characterized by the formation of a fibrotic tissue capsule around the implant, leading to functional impairment. Various factors, including material properties such as surface chemistry, stiffness, and topography, influence the degree of encapsulation. Cross talk between macrophages and fibroblasts plays a critical role in both the FBR and organ fibrosis. However, the precise molecular mechanisms remain poorly understood. Macrophages secrete a wide range of cytokines that modulate fibroblast behavior such as abundant collagen deposition and myofibroblast differentiation. However, the heterogeneity of macrophages and fibroblasts and their dynamic behavior in different tissue environments add complexity to this cross talk. Experimental evidence from in vitro studies demonstrates the impact of material properties on macrophage cytokine secretion and fibroblast physiology. However, the correlation between in vitro response and in vivo encapsulation outcomes is not robust. Adverse outcome pathways (AOPs) offer a potential framework to understand and predict process complexity. AOPs describe causal relationships between measurable events leading to adverse outcomes, providing mechanistic insights for in vitro testing and predictive modeling. However, the development of an AOP for the FBR does require a comprehensive understanding of the molecular initiating events and key event relationships to identify which events are essential. In this article, we describe the current knowledge on macrophage-fibroblast cross talk in the FBR and discuss how targeted research can help build an AOP for implant-related fibrosis.

Merging Modular Molecular Design with High Throughput Screening of Cell Adhesion on Antimicrobial Supramolecular Biomaterials

A polymer microarray based on the supramolecular ureido-pyrimidinone (UPy) moiety is fabricated to screen antimicrobial materials for their ability to support cell adhesion. UPy-functionalized additives, either cell-adhesive, antimicrobial or control peptides, are used, and investigated in different combinations at different concentrations, resulting in a library of 194 spots. These are characterized on composition and morphology to evaluate the microarray fabrication. Normal human dermal fibroblasts are cultured on the microarrays and cell adhesion to the spots is systematically analyzed. Results demonstrate enhanced cell adhesion on spots with combinations including the antimicrobial peptides. This study clearly proves the power of the high throughput approach in combination with supramolecular molecules, to screen additive libraries for desired biological response.

Transient stimulated Raman scattering spectroscopy and imaging

Stimulated Raman scattering (SRS) has been developed as an essential quantitative contrast for chemical imaging in recent years. However, while spectral lines near the natural linewidth limit can be routinely achieved by state-of-the-art spontaneous Raman microscopes, spectral broadening is inevitable for current mainstream SRS imaging methods. This is because those SRS signals are all measured in the frequency domain. There is a compromise between sensitivity and spectral resolution: as the nonlinear process benefits from pulsed excitations, the fundamental time-energy uncertainty limits the spectral resolution. Besides, the spectral range and acquisition speed are mutually restricted. Here we report transient stimulated Raman scattering (T-SRS), an alternative time-domain strategy that bypasses all these fundamental conjugations. T-SRS is achieved by quantum coherence manipulation: we encode the vibrational oscillations in the stimulated Raman loss (SRL) signal by femtosecond pulse-pair sequence excited vibrational wave packet interference. The Raman spectrum was then achieved by Fourier transform of the time-domain SRL signal. Since all Raman modes are impulsively and simultaneously excited, T-SRS features the natural-linewidth-limit spectral line shapes, laser-bandwidth-determined spectral range, and improved sensitivity. With ~150-fs laser pulses, we boost the sensitivity of typical Raman modes to the sub-mM level. With all-plane-mirror high-speed time-delay scanning, we further demonstrated hyperspectral SRS imaging of live-cell metabolism and high-density multiplexed imaging with the natural-linewidth-limit spectral resolution. T-SRS shall find valuable applications for advanced Raman imaging.

Unlocking Bio-Instructive Polymers: A Novel Multi-Well Screening Platform Based on Secretome Sampling

Biomaterials are designed to interact with biological systems to replace, support, enhance, or monitor their function. However, there are challenges associated with traditional biomaterials' development due to the lack of underlying theory governing cell response to materials' chemistry. This leads to the time-consuming process of testing different materials plus the adverse reactions in the body such as cytotoxicity and foreign body response. High-throughput screening (HTS) offers a solution to these challenges by enabling rapid and simultaneous testing of a large number of materials to determine their bio-interactions and biocompatibility. Secreted proteins regulate many physiological functions and determine the success of implanted biomaterials through directing cell behaviour. However, the majority of biomaterials' HTS platforms are suitable for microscopic analyses of cell behaviour and not for investigating non-adherent cells or measuring cell secretions. Here, we describe a multi-well platform adaptable to robotic printing of polymers and suitable for secretome profiling of both adherent and non-adherent cells. We detail the platform's development steps, encompassing the preparation of individual cell culture chambers, polymer printing, and the culture environment, as well as examples to demonstrate surface chemical characterisation and biological assessments of secreted mediators. Such platforms will no doubt facilitate the discovery of novel biomaterials and broaden their scope by adapting wider arrays of cell types and incorporating assessments of both secretome and cell-bound interactions. Key features • Detailed protocols for preparation of substrate for contact printing of acrylate-based polymers including O2 plasma etching, functionalisation process, and Poly(2-hydroxyethyl methacrylate) (pHEMA) dip coating. • Preparations of 7 mm × 7 mm polymers employing pin printing system. • Provision of confined area for each polymer using ProPlate® multi-well chambers. • Compatibility of this platform was validated using adherent cells [primary human monocyte-derived macrophages (MDMs)) and non-adherent cells (primary human monocyte-derived dendritic cells (moDCs)]. • Examples of the adaptability of the platform for secretome analysis including five different cytokines using enzyme-linked immunosorbent assay (ELISA, DuoSet®). Graphical overview.

Universal Biomaterial-on-Chip: a versatile platform for evaluating cellular responses on diverse biomaterial substrates

Microfluidics has emerged as a promising approach for assessing cellular behavior in vitro, providing more physiologically relevant cell culture environments with dynamic flow and shear stresses. This study introduces the Universal Biomaterial-on-Chip (UBoC) device, which enables the evaluation of cell response on diverse biomaterial substrates in a 3D-printed microfluidic device. The UBoC platform offers mechanical stimulation of the cells and monitoring of their response on diverse biomaterials, enabling qualitative and quantitative in vitro analysis both on- and off-chip. Cell adhesion and proliferation were assessed to evaluate the biocompatibility of materials with different physical properties, while mechanical stimulation was performed to investigate shear-dependent calcium signaling in pre-osteoblasts. Moreover, the applicability of the UBoC platform in creating more complex in vitro models by culturing multiple cell types was demonstrated, establishing a dynamic multicellular environment to investigate cellular interfaces and their significance in biological processes. Overall, the UBoC presents an adaptable tool for in vitro evaluation of cellular behavior, offering opportunities for studying various biomaterials and cell interactions in microfluidic environments.

A potential alternative to fungicides using actives-free (meth)acrylate polymers for protection of wheat crops from fungal attachment and infection

Fungicidal compounds are actives widely used for crop protection from fungal infection, but they can also kill beneficial organisms, enter the food chain and promote resistant pathogen strains from overuse. Here we report the first field crop trial of homopolymer materials that prevent fungal attachment, showing successful crop protection via an actives-free approach. In the trial, formulations containing two candidate polymers were applied to young wheat plants that were subject to natural infection with the wheat pathogen Zymoseptoria tritici. A formulation containing one of the candidate polymers, poly(di(ethylene glycol) ethyl ether acrylate) (abbreviated DEGEEA), produced a significant reduction (26%) in infection of the crop by Z. tritici, delivering protection against fungal infection that compared favourably with three different commercially established fungicide programmes tested in parallel. Furthermore, the sprayed polymers did not negatively affect wheat growth. The two lead polymer candidates were initially identified by bio-performance testing using in vitro microplate- and leaf-based assays and were taken forward successfully into a programme to optimize and scale-up their synthesis and compound them into a spray formulation. Therefore, the positive field trial outcome has also established the validity of the smaller-scale, laboratory-based bioassay data and scale-up methodologies used. Because fungal attachment to plant surfaces is a first step in many crop infections, this non-eluting polymer: (i) now offers significant potential to deliver protection against fungal attack, while (ii) addressing the fourth and aligning with the eleventh principles of green chemistry by using chemical products designed to preserve efficacy of function while reducing toxicity. A future focus should be to develop the material properties for this and other applications including other fungal pathogens.

Discovery of a polymer resistant to bacterial biofilm, swarming, and encrustation

Innovative approaches to prevent catheter-associated urinary tract infections (CAUTIs) are urgently required. Here, we describe the discovery of an acrylate copolymer capable of resisting single- and multispecies bacterial biofilm formation, swarming, encrustation, and host protein deposition, which are major challenges associated with preventing CAUTIs. After screening ~400 acrylate polymers, poly(tert-butyl cyclohexyl acrylate) was selected for its biofilm- and encrustation-resistant properties. When combined with the swarming inhibitory poly(2-hydroxy-3-phenoxypropyl acrylate), the copolymer retained the bioinstructive properties of the respective homopolymers when challenged with Proteus mirabilis, Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli. Urinary tract catheterization causes the release of host proteins that are exploited by pathogens to colonize catheters. After preconditioning the copolymer with urine collected from patients before and after catheterization, reduced host fibrinogen deposition was observed, and resistance to diverse uropathogens was maintained. These data highlight the potential of the copolymer as a urinary catheter coating for preventing CAUTIs.

Direct 3D printed biocompatible microfluidics: assessment of human mesenchymal stem cell differentiation and cytotoxic drug screening in a dynamic culture system

BACKGROUND

In vivo-mimicking conditions are critical in in vitro cell analysis to obtain clinically relevant results. The required conditions, comparable to those prevalent in nature, can be provided by microfluidic dynamic cell cultures. Microfluidics can be used to fabricate and test the functionality and biocompatibility of newly developed nanosystems or to apply micro- and nanoelectromechanical systems embedded in a microfluidic system. However, the use of microfluidic systems is often hampered by their accessibility, acquisition cost, or customization, especially for scientists whose primary research focus is not microfluidics.

RESULTS

Here we present a method for 3D printing that can be applied without special prior knowledge and sophisticated equipment to produce various ready-to-use microfluidic components with a size of 100 µm. Compared to other available methods, 3D printing using fused deposition modeling (FDM) offers several advantages, such as time-reduction and avoidance of sophisticated equipment (e.g., photolithography), as well as excellent biocompatibility and avoidance of toxic, leaching chemicals or post-processing (e.g., stereolithography). We further demonstrate the ease of use of the method for two relevant applications: a cytotoxicity screening system and an osteoblastic differentiation assay. To our knowledge, this is the first time an application including treatment, long-term cell culture and analysis on one chip has been demonstrated in a directly 3D-printed microfluidic chip.

CONCLUSION

The direct 3D printing method is tested and validated for various microfluidic components that can be combined on a chip depending on the specific requirements of the experiment. The ease of use and production opens up the potential of microfluidics to a wide range of users, especially in biomedical research. Our demonstration of its use as a cytotoxicity screening system and as an assay for osteoblastic differentiation shows the methods potential in the development of novel biomedical applications. With the presented method, we aim to disseminate microfluidics as a standard method in biomedical research, thus improving the reproducibility and transferability of results to clinical applications.

Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis?

Despite rapid advances in molecular biology, particularly in site-specific genome editing technologies, such as CRISPR/Cas9 and base editing, financial and logistical challenges hinder a broad population from accessing and benefiting from gene therapy. To improve the affordability and scalability of gene therapy, we need to deploy chemically defined, economical, and scalable materials, such as synthetic polymers. For polymers to deliver nucleic acids efficaciously to targeted cells, they must optimally combine design attributes, such as architecture, length, composition, spatial distribution of monomers, basicity, hydrophilic-hydrophobic phase balance, or protonation degree. Designing polymeric vectors for specific nucleic acid payloads is a multivariate optimization problem wherein even minuscule deviations from the optimum are poorly tolerated. To explore the multivariate polymer design space rapidly, efficiently, and fruitfully, we must integrate parallelized polymer synthesis, high-throughput biological screening, and statistical modeling. Although materiomics approaches promise to streamline polymeric vector development, several methodological ambiguities must be resolved. For instance, establishing a flexible polymer ontology that accommodates recent synthetic advances, enforcing uniform polymer characterization and data reporting standards, and implementing multiplexed in vitro and in vivo screening studies require considerable planning, coordination, and effort. This contribution will acquaint readers with the challenges associated with materiomics approaches to polymeric gene delivery and offers guidelines for overcoming these challenges. Here, we summarize recent developments in combinatorial polymer synthesis, high-throughput screening of polymeric vectors, omics-based approaches to polymer design, barcoding schemes for pooled in vitro and in vivo screening, and identify materiomics-inspired research directions that will realize the long-unfulfilled clinical potential of polymeric carriers in gene therapy.

Biopolymer: A Sustainable Material for Food and Medical Applications

Biopolymers are a leading class of functional material suitable for high-value applications and are of great interest to researchers and professionals across various disciplines. Interdisciplinary research is important to understand the basic and applied aspects of biopolymers to address several complex problems associated with good health and well-being. To reduce the environmental impact and dependence on fossil fuels, a lot of effort has gone into replacing synthetic polymers with biodegradable materials, especially those derived from natural resources. In this regard, many types of natural or biopolymers have been developed to meet the needs of ever-expanding applications. These biopolymers are currently used in food applications and are expanding their use in the pharmaceutical and medical industries due to their unique properties. This review focuses on the various uses of biopolymers in the food and medical industry and provides a future outlook for the biopolymer industry.

Machine Learning-Driven Biomaterials Evolution

Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been hampered by the relatively long development period required. In recent years, driven by the need to accelerate materials development, the applications of machine learning in materials science has progressed in leaps and bounds. The combination of machine learning with high-throughput theoretical predictions and high-throughput experiments (HTE) has shifted the traditional Edisonian (trial and error) paradigm to a data-driven paradigm. In this review, each type of biomaterial and their key properties and use cases are systematically discussed, followed by how machine learning can be applied in the development and design process. The discussions are classified according to various types of materials used including polymers, metals, ceramics, and nanomaterials, and implants using additive manufacturing. Last, the current gaps and potential of machine learning to further aid biomaterials discovery and application are also discussed.

Clever Experimental Designs: Shortcuts for Better iPSC Differentiation

For practical use of pluripotent stem cells (PSCs) for disease modelling, drug screening, and regenerative medicine, the cell differentiation process needs to be properly refined to generate end products with consistent and high quality. To construct and optimize a robust cell-induction process, a myriad of cell culture conditions should be considered. In contrast to inefficient brute-force screening, statistical design of experiments (DOE) approaches, such as factorial design, orthogonal array design, response surface methodology (RSM), definitive screening design (DSD), and mixture design, enable efficient and strategic screening of conditions in smaller experimental runs through multifactorial screening and/or quantitative modeling. Although DOE has become routinely utilized in the bioengineering and pharmaceutical fields, the imminent need of more detailed cell-lineage specification, complex organoid construction, and a stable supply of qualified cell-derived material requires expedition of DOE utilization in stem cell bioprocessing. This review summarizes DOE-based cell culture optimizations of PSCs, mesenchymal stem cells (MSCs), hematopoietic stem cells (HSCs), and Chinese hamster ovary (CHO) cells, which guide effective research and development of PSC-derived materials for academic and industrial applications.

Ink-jet 3D printing as a strategy for developing bespoke non-eluting biofilm resistant medical devices

Chronic infection as a result of bacterial biofilm formation on implanted medical devices is a major global healthcare problem requiring new biocompatible, biofilm-resistant materials. Here we demonstrate how bespoke devices can be manufactured through ink-jet-based 3D printing using bacterial biofilm inhibiting formulations without the need for eluting antibiotics or coatings. Candidate monomers were formulated and their processability and reliability demonstrated. Formulations for in vivo evaluation of the 3D printed structures were selected on the basis of their in vitro bacterial biofilm inhibitory properties and lack of mammalian cell cytotoxicity. In vivo in a mouse implant infection model, Pseudomonas aeruginosa biofilm formation on poly-TCDMDA was reduced by ~99% when compared with medical grade silicone. Whole mouse bioluminescence imaging and tissue immunohistochemistry revealed the ability of the printed device to modulate host immune responses as well as preventing biofilm formation on the device and infection of the surrounding tissues. Since 3D printing can be used to manufacture devices for both prototyping and clinical use, the versatility of ink-jet based 3D-printing to create personalised functional medical devices is demonstrated by the biofilm resistance of both a finger joint prosthetic and a prostatic stent printed in poly-TCDMDA towards P. aeruginosa and Staphylococcus aureus.

Generation and Characterization of a Library of Novel Biologically Active Functional Surfactants (Surfmers) Using Combined High-Throughput Methods

We report the first successful combination of three distinct high-throughput techniques to deliver the accelerated design, synthesis, and property screening of a library of novel, bio-instructive, polymeric, comb-graft surfactants. These three-dimensional, surface-active materials were successfully used to control the surface properties of particles by forming a unimolecular deep layer on the surface of the particles via microfluidic processing. This strategy deliberately utilizes the surfactant to both create the stable particles and deliver a desired cell-instructive behavior. Therefore, these specifically designed, highly functional surfactants are critical to promoting a desired cell response. This library contained surfactants constructed from 20 molecularly distinct (meth)acrylic monomers, which had been pre-identified by HT screening to exhibit specific, varied, and desirable bacterial biofilm inhibitory responses. The surfactant's self-assembly properties in water were assessed by developing a novel, fully automated, HT method to determine the critical aggregation concentration. These values were used as the input data to a computational-based evaluation of the key molecular descriptors that dictated aggregation behavior. Thus, this combination of HT techniques facilitated the rapid design, generation, and evaluation of further novel, highly functional, cell-instructive surfaces by application of designed surfactants possessing complex molecular architectures.

Biomaterials by design: Harnessing data for future development

Biomaterials is an interdisciplinary field of research to achieve desired biological responses from new materials, regardless of material type. There have been many exciting innovations in this discipline, but commercialization suffers from a lengthy discovery to product pipeline, with many failures along the way. Success can be greatly accelerated by harnessing machine learning techniques to comb through large amounts of data. There are many potential benefits of moving from an unstructured empirical approach to a development strategy that is entrenched in data. Here, we discuss the recent work on the use of machine learning in the discovery and design of biomaterials, including new polymeric, metallic, ceramics, and nanomaterials, and how machine learning can interface with emerging use cases of 3D printing. We discuss the steps for closer integration of machine learning to make this exciting possibility a reality.

High-Throughput and Combinatorial Approaches for the Development of Multifunctional Polymers

High-throughput (HT) development of new multifunctional polymers is accomplished by the combination of different HT tools established in polymer sciences in the last decade. Important advances are robotic/HT synthesis of polymer libraries, the HT characterization of polymers, and the application of spatially resolved polymer library formats, explicitly microarray and gradient libraries. HT polymer synthesis enables the generation of material libraries with combinatorial design motifs. Polymer composition, molecular weight, macromolecular architecture, etc. may be varied in a systematic, fine-graded manner to obtain libraries with high chemical diversity and sufficient compositional resolution as model systems for the screening of these materials for the functions aimed. HT characterization allows a fast assessment of complementary properties, which are employed to decipher quantitative structure-properties relationships. Moreover, these methods facilitate the HT determination of important surface parameters by spatially resolved characterization methods, including time-of-flight secondary ion mass spectrometry and X-ray photoelectron spectroscopy. Here current methods for the high-throughput robotic synthesis of multifunctional polymers as well as their characterization are presented and advantages as well as present limitations are discussed.

High-Throughput Routes to Biomaterials Discovery

Many existing clinical treatments are limited in their ability to completely restore decreased or lost tissue and organ function, an unenviable situation only further exacerbated by a globally aging population. As a result, the demand for new medical interventions has increased substantially over the past 20 years, with the burgeoning fields of gene therapy, tissue engineering, and regenerative medicine showing promise to offer solutions for full repair or replacement of damaged or aging tissues. Success in these fields, however, inherently relies on biomaterials that are engendered with the ability to provide the necessary biological cues mimicking native extracellular matrixes that support cell fate. Accelerating the development of such "directive" biomaterials requires a shift in current design practices toward those that enable rapid synthesis and characterization of polymeric materials and the coupling of these processes with techniques that enable similarly rapid quantification and optimization of the interactions between these new material systems and target cells and tissues. This manuscript reviews recent advances in combinatorial and high-throughput (HT) technologies applied to polymeric biomaterial synthesis, fabrication, and chemical, physical, and biological screening with targeted end-point applications in the fields of gene therapy, tissue engineering, and regenerative medicine. Limitations of, and future opportunities for, the further application of these research tools and methodologies are also discussed.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Discovery of a Novel Polymer for Xeno-Free, Long-Term Culture of Human Pluripotent Stem Cell Expansion

Human pluripotent stem cells (hPSCs) can be expanded and differentiated in vitro into almost any adult tissue cell type, and thus have great potential as a source for cell therapies with biomedical application. In this study, a fully-defined polymer synthetic substrate is identified for hPSC culture in completely defined, xenogenic (xeno)-free conditions. This system can overcome the cost, scalability, and reproducibility limitations of current hPSC culture strategies, and facilitate large-scale production. A high-throughput, multi-generational polymer microarray platform approach is used to test over 600 unique polymers and rapidly assess hPSC-polymer interactions in combination with the fully defined xeno-free medium, Essential 8 (E8). This study identifies a novel nanoscale phase separated blend of poly(tricyclodecane-dimethanol diacrylate) and poly(butyl acrylate) (2:1 v/v), which supports long-term expansion of hPSCs and can be readily coated onto standard cultureware. Analysis of cell-polymer interface interactions through mass spectrometry and integrin blocking studies provides novel mechanistic insight into the role of the E8 proteins in promoting integrin-mediated hPSC attachment and maintaining hPSC signaling, including ability to undergo multi-lineage differentiation. This study therefore identifies a novel substrate for long-term serial passaging of hPSCs in serum-free, commercial chemically-defined E8, which provides a promising and economic hPSC expansion platform for clinical-scale application.

Challenges in Bone Tissue Regeneration: Stem Cell Therapy, Biofunctionality and Antimicrobial Properties of Novel Materials and Its Evolution

An aging population leads to increasing demand for sustained quality of life with the aid of novel implants. Patients expect fast healing and few complications after surgery. Increased biofunctionality and antimicrobial behavior of implants, in combination with supportive stem cell therapy, can meet these expectations. Recent research in the field of bone implants and the implementation of autologous mesenchymal stem cells in the treatment of bone defects is outlined and evaluated in this review. The article highlights several advantages, limitations and advances for metal-, ceramic- and polymer-based implants and discusses the future need for high-throughput screening systems used in the evaluation of novel developed materials and stem cell therapies. Automated cell culture systems, microarray assays or microfluidic devices are required to efficiently analyze the increasing number of new materials and stem cell-assisted therapies. Approaches described in the literature to improve biocompatibility, biofunctionality and stem cell differentiation efficiencies of implants range from the design of drug-laden nanoparticles to chemical modification and the selection of materials that mimic the natural tissue. Combining suitable implants with mesenchymal stem cell treatment promises to shorten healing time and increase treatment success. Most research studies focus on creating antibacterial materials or modifying implants with antibacterial coatings in order to address the increasing number of complications after surgeries that are mostly caused by bacterial infections. Moreover, treatment of multiresistant pathogens will pose even bigger challenges in hospitals in the future, according to the World Health Organization (WHO). These antibacterial materials will help to reduce infections after surgery and the number of antibiotic treatments that contribute to the emergence of new multiresistant pathogens, whilst the antibacterial implants will help reduce the amount of antibiotics used in clinical treatment.

Controlling Experimental Parameters to Improve Characterization of Biomaterial Fouling

Uncontrolled protein adsorption and cell binding to biomaterial surfaces may lead to degradation, implant failure, infection, and deleterious inflammatory and immune responses. The accurate characterization of biofouling is therefore crucial for the optimization of biomaterials and devices that interface with complex biological environments composed of macromolecules, fluids, and cells. Currently, a diverse array of experimental conditions and characterization techniques are utilized, making it difficult to compare reported fouling values between similar or different biomaterials. This review aims to help scientists and engineers appreciate current limitations and conduct fouling experiments to facilitate the comparison of reported values and expedite the development of low-fouling materials. Recent advancements in the understanding of protein-interface interactions and fouling variability due to experiment conditions will be highlighted to discuss protein adsorption and cell adhesion and activation on biomaterial surfaces.

Polymer microarrays rapidly identify competitive adsorbents of virus-like particles

The emergence of SARS-CoV-2 highlights the global need for platform technologies to enable the rapid development of diagnostics, vaccines, treatments, and personal protective equipment (PPE). However, many current technologies require the detailed mechanistic knowledge of specific material-virion interactions before they can be employed, for example, to aid in the purification of vaccine components or in the design of a more effective PPE. Here, we show that an adaption of a polymer microarray method for screening bacterial-surface interactions allows for the screening of polymers for desirable material-virion interactions. Nonpathogenic virus-like particles including fluorophores are exposed to the arrays in an aqueous buffer as a simple model of virions carried to the surface in saliva/sputum. Competitive binding of Lassa and Rubella virus-like particles is measured to probe the relative binding properties of a selection of copolymers. This provides the first step in the development of a method for the discovery of novel materials with promise for viral binding, with the next being development of this method to assess absolute viral adsorption and assessment of the attenuation of the activity of live virus, which we propose would be part of a material scale up step carried out in high containment facilities, alongside the use of more complex media to represent biological fluids.

Discovery of hemocompatible bacterial biofilm-resistant copolymers

Blood-contacting medical devices play an important role within healthcare and are required to be biocompatible, hemocompatible and resistant to microbial colonization. Here we describe a high throughput screen for copolymers with these specific properties. A series of weakly amphiphilic monomers are combinatorially polymerized with acrylate glycol monomers of varying chain lengths to create a library of 645 multi-functional candidate materials containing multiple chemical moieties that impart anti-biofilm, hemo- and immuno-compatible properties. These materials are screened in over 15,000 individual biological assays, targeting two bacterial species, one Gram negative (Pseudomonas aeruginosa) and one Gram positive (Staphylococcus aureus) commonly associated with central venous catheter infections, using 5 different measures of hemocompatibility and 6 measures of immunocompatibililty. Selected copolymers reduce platelet activation, platelet loss and leukocyte activation compared with the standard comparator PTFE as well as reducing bacterial biofilm formation in vitro by more than 82% compared with silicone. Poly(isobornyl acrylate-co-triethylene glycol methacrylate) (75:25) is identified as the optimal material across all these measures reducing P. aeruginosa biofilm formation by up to 86% in vivo in a murine foreign body infection model compared with uncoated silicone.

A hydrogel-based optical fibre fluorescent pH sensor for observing lung tumor tissue acidity

Technologies for measuring physiological parameters in vivo offer the possibility of the detection of disease and its progression due to the resulting changes in tissue pH, or temperature, etc.. Here, a compact hydrogel-based optical fibre pH sensor was fabricated, in which polymer microarrays were utilized for the high-throughput discovery of an optimal matrix for pH indicator immobilization. The fabricated hydrogel-based probe responded rapidly to pH changes and demonstrated a good linear correlation within the physiological pH range (from 5.5 to 8.0) with a precision of 0.10 pH units. This miniature probe was validated by measuring pH across a whole ovine lung and allowed discrimination of tumorous and normal tissue, thus offering the potential for the rapid and accurate observation of tissue pH changes.

Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval

We develop an automatic peak fitting algorithm using the Bayesian information criterion (BIC) fitting method with confidence-interval estimation in spectral decomposition. First, spectral decomposition is carried out by adopting the Bayesian exchange Monte Carlo method for various artificial spectral data, and the confidence interval of fitting parameters is evaluated. From the results, an approximated model formula that expresses the confidence interval of parameters and the relationship between the peak-to-peak distance and the signal-to-noise ratio is derived. Next, for real spectral data, we compare the confidence interval of each peak parameter obtained using the Bayesian exchange Monte Carlo method with the confidence interval obtained from the BIC-fitting with the model selection function and the proposed approximated formula. We thus confirm that the parameter confidence intervals obtained using the two methods agree well. It is therefore possible to not only simply estimate the appropriate number of peaks by BIC-fitting but also obtain the confidence interval of fitting parameters.

The Overview of Porous, Bioactive Scaffolds as Instructive Biomaterials for Tissue Regeneration and Their Clinical Translation

Porous scaffolds have been employed for decades in the biomedical field where researchers have been seeking to produce an environment which could approach one of the extracellular matrixes supporting cells in natural tissues. Such three-dimensional systems offer many degrees of freedom to modulate cell activity, ranging from the chemistry of the structure and the architectural properties such as the porosity, the pore, and interconnection size. All these features can be exploited synergistically to tailor the cell-material interactions, and further, the tissue growth within the voids of the scaffold. Herein, an overview of the materials employed to generate porous scaffolds as well as the various techniques that are used to process them is supplied. Furthermore, scaffold parameters which modulate cell behavior are identified under distinct aspects: the architecture of inert scaffolds (i.e., pore and interconnection size, porosity, mechanical properties, etc.) alone on cell functions followed by comparison with bioactive scaffolds to grasp the most relevant features driving tissue regeneration. Finally, in vivo outcomes are highlighted comparing the accordance between in vitro and in vivo results in order to tackle the future translational challenges in tissue repair and regeneration.

QSAR without borders

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.

ToF-SIMS and Machine Learning for Single-Pixel Molecular Discrimination of an Acrylate Polymer Microarray

Combinatorial approaches to materials discovery offer promising potential for the rapid development of novel polymer systems. Polymer microarrays enable the high-throughput comparison of material physical and chemical properties-such as surface chemistry and properties like cell attachment or protein adsorption-in order to identify correlations that can progress materials development. A challenge for this approach is to accurately discriminate between highly similar polymer chemistries or identify heterogeneities within individual polymer spots. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) offers unique potential in this regard, capable of describing the chemistry associated with the outermost layer of a sample with high spatial resolution and chemical sensitivity. However, this comes at the cost of generating large scale, complex hyperspectral imaging data sets. We have demonstrated previously that machine learning is a powerful tool for interpreting ToF-SIMS images, describing a method for color-tagging the output of a self-organizing map (SOM). This reduces the entire hyperspectral data set to a single reconstructed color similarity map, in which the spectral similarity between pixels is represented by color similarity in the map. Here, we apply the same methodology to a ToF-SIMS image of a printed polymer microarray for the first time. We report complete, single-pixel molecular discrimination of the 70 unique homopolymer spots on the array while also identifying intraspot heterogeneities thought to be related to intermixing of the polymer and the pHEMA coating. In this way, we show that the SOM can identify layers of similarity and clusters in the data, both with respect to polymer backbone structures and their individual side groups. Finally, we relate the output of the SOM analysis with fluorescence data from polymer-protein adsorption studies, highlighting how polymer performance can be visualized within the context of the global topology of the data set.

High-Throughput Synthesis and Screening of Rapidly Degrading Polyanhydride Nanoparticles

Combinatorial techniques can accelerate the discovery and development of polymeric nanodelivery devices by pairing high-throughput synthesis with rapid materials characterization. Biodegradable polyanhydrides demonstrate tunable release, high cellular internalization, and dose sparing properties when used as nanodelivery devices. This nanoparticle platform shows promising potential for small molecule drug delivery, but the pace of understanding and rational design of these nanomedicines is limited by the low throughput of conventional characterization. This study reports the use of a high-throughput method to synthesize libraries of a newly synthesized, rapidly eroding polyanhydride copolymer based on 1,8-bis(p-carboxyphenoxy)-3,6-dioxaoctane (CPTEG) and sebacic acid (SA) monomers. The high-throughput method enabled efficient screening of copolymer microstructure, revealing weak block-type and alternating architectures. The high-throughput method was adapted to synthesize nanoparticle libraries encapsulating hydrophobic model drugs. Drug release from these nanoparticles was rapid, with a majority of the payload released within 3 days. Drug release was dramatically slowed at acidic pH, which could be useful for oral drug delivery. Rhodamine B (RhoB) release kinetics generally followed patterns of polymer erosion kinetics, while Coomassie brilliant blue (CBB) released the fastest from the slowest degrading polymer chemistry and vice versa. These differences in trends between copolymer chemistry and release kinetics were hypothesized to arise from differences in mixing thermodynamics. A high-throughput method was developed to synthesize polymer-drug film libraries and characterize mixing thermodynamics by melting point depression. Rhodamine B had a negative χ for all copolymers with <30 mol % CPTEG tested, indicating a tendency toward miscibility. By contrast, CBB χ increased, eventually becoming positive near 15:85 CPTEG:SA, with increasing CPTEG content. This indicates an increasing tendency toward phase separation in CPTEG-rich copolymers. These in vitro results screening polymer-drug interactions showed good agreement with in silico predictions from Hansen solubility parameter estimation and were able to explain the observed differences in model drug release trends.

Synthetic Polymers Provide a Robust Substrate for Functional Neuron Culture

Substrates for neuron culture and implantation are required to be both biocompatible and display surface compositions that support cell attachment, growth, differentiation, and neural activity. Laminin, a naturally occurring extracellular matrix protein is the most widely used substrate for neuron culture and fulfills some of these requirements, however, it is expensive, unstable (compared to synthetic materials), and prone to batch-to-batch variation. This study uses a high-throughput polymer screening approach to identify synthetic polymers that supports the in vitro culture of primary mouse cerebellar neurons. This allows the identification of materials that enable primary cell attachment with high viability even under "serum-free" conditions, with materials that support both primary cells and neural progenitor cell attachment with high levels of neuronal biomarker expression, while promoting progenitor cell maturation to neurons.

High-Throughput Identification and Screening of Single Microbial Cells by Nanobowl Array

High-throughput screening and fast identification of single bacterial cells are crucial for clinical diagnosis, bioengineering, and fermentation engineering. Although single-cell technologies have been developed extensively in recent years, the single-cell technologies for bacteria still need further exploration. In this study, we demonstrate an identification and screening technology for single bacterial cells based on a large-scale nanobowl array, which is well-ordered and size-adjustable for use with different kinds of bacteria. When the culture medium with monodispersed bacteria was placed on the nanobowl array, it successfully enabled loading of single bacterium into a single nanobowl. Because of the limitative size and depth of the nanobowls, mixture of different bacteria species could be screened according to their sizes. In addition, with the help of a low electrical current, the bacteria can be further screened according to their intrinsic surface charges. If combined with micromanipulation technology, high-throughput single bacterial selection can be achieved in future.

Polymer Microarrays for the Discovery and Optimization of Robust Optical-Fiber-Based pH Sensors

Polymer microarrays were utilized for the high-throughput screening and discovery of optimal polymeric substrates capable of trapping functional ratiometric fluorescence-based pH sensors. This led to the identification of poly(methyl methacrylate- co-2-(dimethylamino) ethyl acrylate) (PA101), which allowed, via dip coating, the attachment of fluorescent pH sensors onto the tips of optical fibers, resulting in robust, rapid, and reproducible sensing of physiological pHs.

A soft 3D polyacrylate hydrogel recapitulates the cartilage niche and allows growth-factor free tissue engineering of human articular cartilage

Cartilage degeneration or damage treatment is still a challenge, but, tissue engineering strategies, which combine cell therapy strategies, which combine cell therapy and scaffolds, and have emerged as a promising new approach. In this regard, polyurethanes and polyacrylates polymers have been shown to have clinical potential to treat osteochondral injuries. Here, we have used polymer microarrays technology to screen 380 different polyurethanes and polyacrylates polymers. The top polymers with potential to maintain chondrocyte viability were selected, with scale-up studies performed to evaluate their ability to support chondrocyte proliferation during long-term culture, while maintaining their characteristic phenotype. Among the selected polymers, poly (methylmethacrylate-co-methacrylic acid), showed the highest level of chondrogenic potential and was used to create a 3D hydrogel. Ultrastructural morphology, microstructure and mechanical testing of this novel hydrogel revealed robust characteristics to support chondrocyte growth. Furthermore, in vitro and in vivo biological assays demonstrated that chondrocytes cultured on the hydrogel had the capacity to produce extracellular matrix similar to hyaline cartilage, as shown by increased expression of collagen type II, aggrecan and Sox9, and the reduced expression of the fibrotic marker's collagen type I. In conclusion, hydrogels generated from poly (methylmethacrylate-co-methacrylic acid) created the appropriate niche for chondrocyte growth and phenotype maintenance and might be an optimal candidate for cartilage tissue-engineering applications. SIGNIFICANCE STATEMENT: Articular cartilage has limited self-repair ability due to its avascular nature, therefore tissue engineering strategies have emerged as a promising new approach. Synthetic polymers displaygreat potential and are widely used in the clinical setting. In our study, using the polymer microarray technique a novel type of synthetic polyacrylate was identified, that was converted into hydrogels for articular cartilage regeneration studies. The hydrogel based on poly (methylmethacrylate-co-methacrylic acid-co-PEG-diacrylate) had a controlable ultrastructural morphology, microstructure (porosity) and mechanical properties (stiffness) appropriate for cartilage engineering. Our hydrogel created the optimal niche for chondrocyte growth and phenotype maintenance for long-term culture, producing a hyaline-like cartilage extracellular matrix. We propose that this novel polyacrylate hydrogel could be an appropriate support to help in the treatment efficient cartilage regeneration.

Methodology for the synthesis of methacrylate monomers using designed single mode microwave applicators

A novel single-well prototype high throughput microwave reactor geometry has been produced and shown to be capable of synthesizing an array of non-commercially available methacrylate monomers.

Biomolecular Assemblies: Moving from Observation to Predictive Design

Biomolecular assembly is a key driving force in nearly all life processes, providing structure, information storage, and communication within cells and at the whole organism level. These assembly processes rely on precise interactions between functional groups on nucleic acids, proteins, carbohydrates, and small molecules, and can be fine-tuned to span a range of time, length, and complexity scales. Recognizing the power of these motifs, researchers have sought to emulate and engineer biomolecular assemblies in the laboratory, with goals ranging from modulating cellular function to the creation of new polymeric materials. In most cases, engineering efforts are inspired or informed by understanding the structure and properties of naturally occurring assemblies, which has in turn fueled the development of predictive models that enable computational design of novel assemblies. This Review will focus on selected examples of protein assemblies, highlighting the story arc from initial discovery of an assembly, through initial engineering attempts, toward the ultimate goal of predictive design. The aim of this Review is to highlight areas where significant progress has been made, as well as to outline remaining challenges, as solving these challenges will be the key that unlocks the full power of biomolecules for advances in technology and medicine.