Additive manufacturing (AM) of metals and alloys opens tremendous opportunities in production of parts with complex shapes and geometries. One of the main challenges is formation of residual stress during fabrication processes which substantially affects service life of engineering components. This paper provides a brief introduction to different types, formation mechanisms, and measurement techniques of the residual stress in metals produced by AM technology. The highlight of this study is to propose a novel quantitative model to estimate residual stress in 3D printed metallic components using micromechanical analysis. Finally, the validity of the proposed model is examined by comparison with the experimental data available in literature.

Additive manufacturing (AM) or 3D printing is an ideal technology for building flexible, complex, monolithic devices. Organs-on-chips (OOCs) are biomimetic microsystems that recapitulate the crucial structures and functions of human organs. Organ-level activities, mechanics and physiological response can be stimulated and investigated in OOCs. Convergence of AM technology along with OOCs offers a more efficient route for creating complex organ or tissue structures with precise 3D cell patterning, biomaterial heterogeneity and specific functionalities. Here, we focus on the recent advances in the field, specifically in the fabrication modalities, materials and characterization methods, which are commonly employed for OOCs based on 3D bioprinting. We also discuss the most significant potential applications from integrating 3D bioprinting with OOCs, aiming to provide future strategies for more efficient, automated, modularly integrated, and customizable OOCs.

The chemical industry makes extensive use of solvents, especially for chemical reactions and separations. When considering the large number of existing solvents and the necessity for finding new and alternative ones, systematic methods for the optimal selection and molecular design of solvents become significant for efficient and sustainable chemical manufacturing. During the past decade, a substantial number of contributions have been made in this area. This article summarizes property models for predicting solvent effects and introduces theoretical methods for solvent selection and design. Recent developments in computer-aided solvent selection/design for four selected application areas including reaction rate acceleration, carbon capture, extractive desulfurization, and homogeneous catalyst recovery are briefly reviewed. To conclude, several remaining challenges and possible future directions are discussed.

Chemical industry is continuously looking for opportunities to manufacture the necessary commodity chemicals as well as to convert them into higher value-added chemicals-based products. Development of these chemicals-based products involves not only their design and/or selection but also their sustainable manufacturing through an appropriate chemical process, its marketing and its disposal as waste. This perspective paper considers mainly computer-aided methods and tools suitable for chemicals-based product development. The advantage of computer-aided design methods and tools is that it is possible to quickly identify promising candidates that can be further investigated and verified through focused experiment-based techniques to obtain the final optimal design. The disadvantage of using these models and/or data-based approaches is that their application ranges are limited to the available models, data and knowledge related to the currently known products. Another complexity that needs to be considered is the multiscale and multidisciplinary nature of chemicals-based product design problems. Therefore, to find new and innovative chemicals-based products, systematic computer-aided methods and tools, capable of managing this complexity are needed. In this paper, the frontiers of model and/or data-based methods for systematic chemical product design and application are presented. Various computer-aided design methods and tools including experiment-based, knowledge-based, rule-based and model-based approaches are briefly reviewed. Perspectives including challenges and opportunities in computer-aided chemicals-based product design are discussed.

This review paper presents some of the topics discussed at the 2018 ‘Chemical process development trends’ seminar organized by the Swiss Process and Chemical Engineers Society in Basel, Switzerland. The first subject covers the use of computer aided tools for systematic reaction route selection, the second one addresses the recent development in the field of process intensification with a focus on reactive distillation and dividing wall column technology, and the third topic highlights recent developments in the field of continuous filtration in the pharmaceutical industry.

Process intensification (PI) has been gaining increasing momentum in the chemical engineering research community and the chemical/energy industry. While many PI alternative technologies and their conventional counterparts exist, systematic approaches and tools to decide on the most promising intensified process solutions are currently rather lacking. Process Systems Engineering (PSE) can contribute uniquely to this challenge by leveraging process synthesis, design, analysis, and optimization tools. However, key open questions in this area still remain, including: (i) how to efficiently address the combinatorial design space and systematically deliver intensified designs, and (ii) how to ensure the operablility performances of the derived intensified structures at an early design stage. This paper provides a brief review of recent progress towards the synthesis of operable process intensification systems, highlights major challenges, and discusses future research opportunities.

Process intensification (PI) is a branch of process synthesis that encompasses and impacts a number of process technologies. Research in PI has recently gained considerable attention due to challenges related to energy and the environment, alongside risks in capital investment decisions. These challenges necessitate the development of optimization-based computational tools for process synthesis and design, which enable the integration of multiple phenomena that occur at different scales in an intensified unit. Current efforts in the field are yielding promising results that indicate the transformation of the petrochemical industry. This review highlights the role that PI can play in the production of fuels, chemicals and electricity from natural/shale gas, using reactive distillation with a Fischer–Tropsch-based gas-to-liquids application. We also discuss several related gas processing PI applications along with recent algorithmic developments for process synthesis.

Process Intensification promises novel solutions to current challenges in the chemical process industry, leading to a rapid growth in interest. There are different approaches to synthesize an intensified process, yet most are based on methods from Process Synthesis and Process Optimization. In this paper, we review those methods and provide an overview of their application in Process Intensification. We also review the evolution of phenomena-based representations, a central theme in the synthesis for PI. Finally, we summarize and compare the approaches that have been suggested for retrofit using PI and criteria to evaluate PI options.

Process systems engineering (PSE) tools can be utilized to enable the optimal operation and control of intensified processes. In this work, the challenges in the control of intensified processes are summarized, including the difficulties in modelling and performing online optimization of these highly complex dynamic systems. Nevertheless, PSE progress in the areas of nonlinear programming, reduced-order modeling, development of software tools, parallel computing and artificial intelligence are enabling the implementation and optimization of large-scale intensified systems. Future opportunities for research are identified, including the simultaneous optimization of scheduling of operation and control, a promising strategy that has proven its value in regular operations, and can expand the operating windows of intensified processes.

Process intensification can afford considerable benefits with respect to economics, sustainability and/or safety but also presents increased decision making challenges with respect to computational efficiency and flexibility across multiple temporal and spatial scales. Distributed decision making, that is, localized yet coordinated decision making among constituent subsystems, is a promising approach to alleviating these challenges. Determination of these subsystems is at the heart of the distributed paradigm. This paper gives a summary of recent developments and future directions in distributed decision making for intensified systems, specifically with respect to optimization, control and monitoring, with emphasis on methods for obtaining high quality decompositions for such problems based on network theory. It also discusses integrated renewable energy and chemical production, a new and promising domain of large-scale process intensification, in the context of systems engineering challenges and opportunities.

Product Design & Engineering (PDE) aims to define new and/or improved products based on customer needs and/or new technologies. A comprehensive discussion of PDE as a building block for chemical engineering education, research and practice seems still lacking, preventing a broader impact on academic and industry realities more and more concerned with the ‘knowledge economy’. The purpose of the present current opinion paper was to contribute to the mitigation of this gap by presenting the results the EFCE Section Group PDE survey based on PDE academia and industry expert and practitioner feedback as well as on a literature review. The paper discusses PDE status and challenges as well as maps academic and industry requirements, unmet needs and perspectives for the product manufacturing in the framework of Industry 4.0.

In this work we provide an overview of the current trend in process and product design as a multidisciplinary area within process system engineering. This problem shows a strong link between different fields including economics, marketing, molecular chemistry, physico-chemistry as well as process design and all the way up to ingredients and final products supply chain. While the different stages in product design have been studied one by one, recent efforts aim at the integrated product design, showing economic and environmental benefits. However, there is still a long way to go for the integrated product design problem that is of paramount importance in the case of formulated products where tradeoffs between product performance, environmental burden and cost can only be addressed from a global perspective.

In this minireview, electro-catalytic activation of some representative alcohols and greenhouse gases CO2 are taken as examples to comprehensively analyze the state of the art of electrocatalysis, and then recent research progress in the characterization techniques for electrocatalysis are also summarized, and several viewpoints on the further development of electrocatalysis are promoted in the end. Overall, further development of the electrocatalysis technique depends on design and exploitation of high-efficiency inexpensive catalysts, high-resolution operando characterization methods, accurate reaction process control as well as optimization of reaction systems.

Considerable efforts have been devoted towards developing effective drug delivery methods. Microfluidic systems, with their capability for precise handling and transport of small liquid quantities, have emerged as a promising platform for designing advanced drug delivery systems. Thus, microfluidic systems have been increasingly used for fabrication of drug carriers or direct drug delivery to a targeted tissue. In this review, the recent advances in these areas are critically reviewed and the shortcomings and opportunities are discussed. In addition, we highlight the efforts towards developing smart drug delivery platforms with integrated sensing and drug delivery components.

Recent advances in dynamic biointerfaces enable spatiotemporal control over cell position and migration after attachment using substrates that employ chemical, optical, thermal, or electrical triggers. This review focuses on flexible and accessible methods for the fabrication of cellular arrays or co cultures for fundamental studies of cell biology or regenerative medicine.

Treatment of cancer using nanoparticle-based approaches relies on the rational design of carriers with respect to size, charge, and surface properties. Polymer-based nanomaterials, inorganic materials such as gold, iron oxide, and silica as well as carbon based materials such as carbon nanotubes and graphene are being explored extensively for cancer therapy. The challenges associated with the delivery of these nanoparticles depend greatly on the type of cancer and stage of development. This review highlights design considerations to develop nanoparticle-based approaches for overcoming physiological hurdles in cancer treatment, as well as emerging research in engineering advanced delivery systems for the treatment of primary, metastatic, and multidrug resistant cancers. A growing understanding of cancer biology will continue to foster development of intelligent nanoparticle-based therapeutics that take into account diverse physiological contexts of changing disease states to improve treatment outcomes.

Semiconductor nanocrystals are tiny fluorescent particles that have recently made a major impact in the biological and medical sciences by enabling high-sensitivity imaging of biomolecules, cells, and tissues. Spherical quantum dots are the prototypical material for these applications but recent synthetic advances have led to a diverse range of nanostructures with controllable sizes, shapes, and materials combinations that offer new dimensions of optical and structural tunability. Uniform anisotropic shapes with linearly polarized light emission allow optical imaging of particle orientation, planar structures have large flexible surfaces and ultra-narrow electronic transitions, and compact nanoparticles have enhanced diffusion in crowded biological environments. These properties are providing unique opportunities to probe basic biological processes, cellular structures, and organismal physiology.

There is a bright future in the development and utilization of nanoscale systems based on intelligent materials that can respond to external input providing a beneficial function. Specific functional groups can be incorporated into polymers to make them responsive to environmental stimuli such as pH, temperature, or varying concentrations of biomolecules. The fusion of such "intelligent" biomaterials with nanotechnology has led to the development of powerful therapeutic and diagnostic platforms. For example, targeted release of proteins and chemotherapeutic drugs has been achieved using pH-responsive nanocarriers while biosensors with ultra-trace detection limits are being made using nanoscale, molecularly imprinted polymers. The efficacy of therapeutics and the sensitivity of diagnostic platforms will continue to progress as unique combinations of responsive polymers and nanomaterials emerge.

Sequencing-based analysis of single circulating tumor cells (CTCs) has the potential to revolutionize our understanding of metastatic cancer and improve clinical care. Technologies exist to enrich, identify, recover, and sequence single cells, but to enable systematic routine analysis of single CTCs from a range of cancer patients, there is a need to establish processes that efficiently integrate these specific operations. Such engineered processes should address challenges associated with the yield and viability of enriched CTCs, the robust identification of candidate single CTCs with minimal degradation of DNA, the bias in whole-genome amplification, and the efficient handling of candidate single CTCs or their amplified DNA products. Advances in methods for single-cell analysis and nanoscale technologies suggest opportunities to overcome these challenges, and could create integrated platforms that perform several of the unit operations together. Ultimately, technologies should be selected or adapted for optimal performance and compatibility in an integrated process.

This review highlights recent progress in developing DNA aptamers for personalized medicine, with more focus on in vivo studies for potential clinical applications. Examples include design of aptamers in combination with DNA nanostructures, nanomaterials, or microfluidic devices as diagnostic probes or therapeutic agents for cancers and other diseases. The use of aptamers as targeting agents in drug delivery is also covered. The advantages and future directions of such DNA aptamer-based technology for the continued development of personalized medicine are discussed.

The ability to design artificial extracellular matrices as cell instructive scaffolds has opened the door to technologies capable of studying cell fates in vitro and to guide tissue repair in vivo. One main component of the design of artificial extracellular matrices is the incorporation of protein-based biochemical cues to guide cell phenotypes and multicellular organizations. However, promoting the long-term bioactivity, controlling the bioavailability and understanding how the physical presentations of these proteins impacts cellular fates are among the challenges of the field. Nanotechnolgy has advanced to meet the challenges of protein therapeutics. For example, the approaches to incorporating proteins into tissue repairing scaffolds have ranged from bulk encapsulations to smart nanodepots that protect proteins from degradations and allow opportunities for controlled release.

There is significant interest within the tissue engineering and pharmaceutical industries to create 3D microphysiological systems of human organ function. The interest stems from a growing concern that animal models and simple 2D culture systems cannot replicate essential features of human physiology that are critical to predict drug response, or simply to develop new therapeutic strategies to repair or replace damaged organs. Central to human organ function is a microcirculation that not only enhances the rate of nutrient and waste transport by convection, but also provides essential additional physiological functions that can be specific to each organ. This review highlights progress in the creation of in vitro functional microvessel networks, and emphasizes organ-specific functional and structural characteristics that should be considered in the future mimicry of four organ systems that are of primary interest: lung, brain, liver, and muscle (skeletal and cardiac).

Cellular separations are required in many contexts in biochemical and biomedical applications for the identification, isolation, and analysis of phenotypes or samples of interest. Microfluidics is uniquely suited for handling biological samples, and emerging technologies have become increasingly accessible tools for researchers and clinicians. Here, we review advances in the last few years in techniques for microfluidic cell separation and manipulation. Applications such as high-throughput cell and organism phenotypic screening, purification of heterogeneous stem cell populations, separation of blood components, and isolation of rare cells in patients highlight some of the areas in which these technologies show great potential. Continued advances in separation mechanisms and understanding of cellular systems will yield further improvements in the throughput, resolution, and robustness of techniques.

Vascularization of tissue-engineered constructs, requiring the transport of oxygen, nutrients and waste through a thick and cellular dense meshwork, continues to hamper the success of the technology in addressing the donor organ shortage crisis. Microfluidic technology has emerged as a viable alternative to traditional in vitro platforms utilized by tissue engineers, to understand how the complex cellular microenvironment directs vascular cell behavior and functionality. In this review, the essence of microfluidic technology and transport phenomenon that make them unique for vascular tissue engineering will be briefly introduced. The main scope of this review is to expose how new and innovative microfluidic fabrication techniques are being utilized for exciting applications that have allowed insight into the spatio/temporal dynamics of vascular cell behavior. Specifically, microfluidic devices which range in functionality from simultaneously controlling oxygen and shear stress levels to perfusable biopolymer networks, will be discussed in the context of how they bolster traditional in vitro platforms, by providing greater data output, accessibility, and physiological relevance.

The effect of fluid flow on cancer progression is currently not well understood, highlighting the need for perfused tumor models to close this gap in knowledge. Enabling biological processes at the cellular level to be modeled with high spatiotemporal control, microfluidic tumor models have demonstrated applicability as platforms to study cell-cell interactions, effect of interstitial flow on tumor migration and the role of vascular barrier function. To account for the multi-scale nature of cancer growth and invasion, macroscale models are also necessary. The consideration of fluid dynamics within tumor models at both the micro- and macroscopic levels may greatly improve our ability to more fully mimic the tumor microenvironment.

Tissue and organ replacement is required when there are no alternative therapies available. Although vascular tissue engineering was originally developed to meet the clinical demands of small-diameter vascular conduits as bypass grafts, it has evolved into a highly advanced field where perfusable vasculatures are generated for implantation. Herein, we review several cutting-edge techniques that have led to implantable human blood vessels in clinical trials, the novel approaches that build complex perfusable microvascular networks in functional tissues, the use of stem cells to generate endothelial cells for vascularization, as well as the challenges in bringing vascular tissue engineering technologies into the clinics.

Considerable advances have occurred in the development of tissue-engineered blood vessels (TEBVs) to repair or replace injured blood vessels, or as in vitro systems for drug toxicity testing. Here we summarize approaches to produce TEBVs and review current efforts to (1) identify suitable cell sources for the endothelium and vascular smooth muscle cells, (2) design the scaffold to mimic the arterial mechanical properties and (3) regulate the functional state of the cells of the vessel wall. Initial clinical studies have established the feasibility of this approach and challenges that make TEBVs a viable alternative for vessel replacement are identified.

Antibody therapeutics are one of the fastest growing classes of pharmaceuticals, with an annual US market over $20 billion, developed to treat a variety of diseases including cancer, auto-immune and infectious diseases. Most are currently administered as a single molecule to treat a single disease, however there is mounting evidence that cocktails of multiple antibodies, each with a unique binding specificity and protective mechanism, may improve clinical efficacy. Here, we review progress in the development of oligoclonal combinations of antibodies to treat disease, focusing on identification of synergistic antibodies. We then discuss the application of modern antibody engineering technologies to produce highly potent antibody preparations, including oligoclonal antibody cocktails and truly recombinant polyclonal antibodies. Specific examples illustrating the synergy conferred by multiple antibodies will be provided for diseases caused by botulinum toxin, cancer and immune thrombocytopenia. The bioprocessing and regulatory options for these preparations will be discussed.

The development of improved methods for early detection and characterization of cancer presents a major clinical challenge. One approach that has shown excellent potential in preclinical and clinical evaluation is molecular imaging with small-scaffold, non-antibody based, engineered proteins. These novel diagnostic agents produce high contrast images due to their fast clearance from the bloodstream and healthy tissues, can be evolved to bind a multitude of cancer biomarkers, and are easily functionalized by site-specific bioconjugation methods. Several small protein scaffolds have been verified for in vivo molecular imaging including affibodies and their two-helix variants, knottins, fibronectins, DARPins, and several natural ligands. Further, the biodistribution of these engineered ligands can be optimized through rational mutation of the conserved regions, careful selection and placement of chelator, and modification of molecular size.

Despite rapid advances in the field of stem/progenitor cells through experimental studies, relevant modeling approaches have not progressed with a similar pace. Various models have focused on particular aspects of stem cell physiology including gene regulatory networks, gene expression noise and signaling cascades activated by exogenous factors. However, the self-renewal and differentiation of stem cells is driven by the coordinated regulation of events at the subcellular, intercellular and milieu levels. Such events also span multiple time domains from the fast molecular reactions governing gene expression to the slower cell cycle and division. Thus, the development of multiscale computational frameworks for stem cell populations is highly desirable. Multiscale models are expected to aid the design of efficient differentiation strategies and bioprocesses for the generation of therapeutically useful stem cell progeny. Yet, challenges in making these models tractable and pairing those to sufficient experimental data prevent their wide adoption by the stem cell community. Here, we review modeling approaches reported for stem cell populations and associated hurdles.

The capacity of nanosilver (Ag nanoparticles) to destroy infectious micro-organisms makes it one of the most powerful antimicrobial agents, an attractive feature against "super-bugs" resistant to antibiotics. Furthermore, its plasmonic properties facilitate its employment as a biosensor or bioimaging agent. Here, the interaction of nanosilver with biological systems including bacteria and mammalian cells is reviewed. The toxicity of nanosilver is discussed focusing on Ag+ ion release in liquid solutions. Biomedical applications of nanosilver are also presented capitalizing on its antimicrobial and plasmonic properties and summarizing its advantages, limitations and challenges. Though a lot needs to be learned about the toxicity of nanosilver, enough is known to safely use it in a spectrum of applications with minimal impact to the environment and human health.

Bioartificial or laboratory-grown organs is a growing field centered on developing replacement organs and tissues to restore body function and providing a potential solution to the shortage of donor organs for transplantation. With the entry of engineered planar tissues, such as bladder and trachea, into clinical studies, an increasing focus is being given to designing complex, three-dimensional solid organs. As tissues become larger, thicker and more complex, the vascular network becomes crucial for supplying nutrients and maintaining viability and growth of the neo-organ. Perfusion decellularization, the process of removing cells from an entire organ, leaves the matrix of the vascular network intact. Organ engineering requires a delicate process of decellularization, sterilization, reseeding with appropriate cells, and organ maturation and stimulation to ensure optimal development. The design of bioreactors to facilitate this sequence of events has been refined to the extent that some bioartificial organs grown in these systems have been transplanted into recipient animals with sustained, though limited, function. This review focuses on the state-of-art in bioreactor development for perfusion-based bioartificial organs and highlights specific design components in need of further refinement.

Stem cell therapy and translational stem cell research require large-scale supply of stem cells at high purity and viability, thus leading to the development of stem cell separation technologies. This review covers key technologies being applied to stem cell separation, and also highlights exciting new approaches in this field. First, we will cover conventional separation methods that are commercially available and have been widely adapted. These methods include Fluorescence-activated cell sorting (FACS), Magnet-activated cell sorting (MACS), pre-plating, conditioned expansion media, density gradient centrifugation, field flow fractionation (FFF), and dielectrophoresis (DEP). Next, we will introduce emerging novel methods that are currently under development. These methods include improved aqueous two-phase system, systematic evolution of ligands by exponential enrichment (SELEX), and various types of microfluidic platforms. Finally, we will discuss the challenges and directions towards future breakthroughs for stem cell isolation. Advancing stem cell separation techniques will be essential for clinical and research applications of stem cells.

Extremely thermophilic microorganisms have been sources of thermostable and thermoactive enzymes for over 30 years. However, information and insights gained from genome sequences, in conjunction with new tools for molecular genetics, have opened up exciting new possibilities for biotechnological opportunities based on extreme thermophiles that go beyond single-step biotransformations. Although the pace for discovering novel microorganisms has slowed over the past two decades, genome sequence data have provided clues to novel biomolecules and metabolic pathways, which can be mined for a range of new applications. Furthermore, recent advances in molecular genetics for extreme thermophiles have made metabolic engineering for high temperature applications a reality.

The use of protein nanoparticles for biosensing, biocatalysis and drug delivery has exploded in the last few years. The ability of protein nanoparticles to self-assemble into predictable, monodisperse structures is of tremendous value. The unique properties of protein nanoparticles such as high stability, and biocompatibility, along with the potential to modify them led to development of novel bioengineering tools. Together, the ability to control the interior loading and external functionalities of protein nanoparticles makes them intriguing nanodevices. This review will focus on a number of recent examples of protein nanoparticles that have been engineered towards imparting the particles with biocatalytic or biosensing functionality.

Stem cell delivery by local injection has tremendous potential as a regenerative therapy but has seen limited clinical success. Several mechanical challenges hinder therapeutic efficacy throughout all stages of cell transplantation, including mechanical forces during injection and loss of mechanical support post-injection. Recent studies have begun exploring the use of biomaterials, in particular hydrogels, to enhance stem cell transplantation by addressing the often-conflicting mechanical requirements associated with each stage of the transplantation process. This review explores recent biomaterial approaches to improve the therapeutic efficacy of stem cells delivered through local injection, with a focus on strategies that specifically address the mechanical challenges that result in cell death and/or limit therapeutic function throughout the stages of transplantation.

Stem cells undergo extensive metabolic rewiring during reprogramming, proliferation and differentiation, and numerous studies have demonstrated a significant role of metabolism in controlling stem cell fates. Recent applications of metabolomics, the study of concentrations and fluxes of small molecules in cells, have advanced efforts to characterize and maturate stem cell fates, assess drug toxicity in stem cell tissue models, identify biomarkers, and study the effects of environment on metabolic pathways in stem cells and their progeny. Looking to the future, combining metabolomics with other -omics approaches will provide a deeper understanding of the complex regulatory mechanisms of stem cells.

Metabolism coordinates the conversion of available nutrients toward energy, biosynthetic intermediates, and signaling molecules to mediate virtually all biological functions. Dysregulation of metabolic pathways contributes to many diseases, so a detailed understanding of human metabolism has significant therapeutic implications. Over the last decade major technological advances in the areas of analytical chemistry, computational estimation of intracellular fluxes, and biological engineering have improved our ability to observe and engineer metabolic pathways. These approaches are reminiscent of the design, operation, and control of industrial chemical plants. Immune cells have emerged as an intriguing system in which metabolism influences diverse biological functions. Application of metabolic flux analysis and related approaches to macrophages and T cells offers great therapeutic opportunities to biochemical engineers.

Induced pluripotent stem (iPS) cell reprogramming and direct reprogramming are promising approaches for disease modeling and personalized medicine. However, these processes are yet to be optimized. Biomaterials are increasingly integrated into cell reprogramming strategies in order to engineer the microenvironment, improve reprogramming efficiency and achieve effective in situ cell reprogramming. Although there are some studies on the role of biomaterials in iPS cell reprogramming, their effect on direct cell conversion has not been fully explored. Here we review the recent advances in the use of biomaterials for iPS cell reprogramming and direct reprogramming, with a focus on the biophysical aspect. We further highlight the future challenges and directions of the field.

Tissue stiffness is tightly controlled under normal conditions, but changes with disease. In cancer, tumors often tend to be stiffer than the surrounding uninvolved tissue, yet the cells themselves soften. Within the past decade, and particularly in the last few years, there is increasing evidence that the stiffness of the extracellular matrix modulates cancer and stromal cell mechanics and function, influencing such disease hallmarks as angiogenesis, migration, and metastasis. This review briefly summarizes recent studies that investigate how cancer cells and fibrosis-relevant stromal cells respond to ECM stiffness, the possible sensing appendages and signaling mechanisms involved, and the emergence of novel substrates - including substrates with scar-like fractal heterogeneity - that mimic the in vivo mechanical environment of the cancer cell.

Despite drug formulation improving circulation times and targeting, efficacy is stymied by inadequate penetration into and retention within target tissues. This review highlights the barriers restricting delivery to the connective tissue interstitium, lymphatics, and lymph nodes as well as advances in engineering drug carriers to overcome these delivery challenges. Three-dimensional tissue physiology is discussed in the context of providing material design principles for delivery to these tissues; in particular the influence of interstitial and lymphatic flows as well as differential permeabilities of the blood and lymphatic capillaries. Key examples of materials with different characteristics developed to overcome these transport barriers are discussed as well as potential areas for further development.

The specificity of DNA hybridization allows for the modular design of 2D and 3D shapes with wide-ranging applications including sensors, actuators, and even logic devices. The inherent biocompatibility of DNA and the ability to produce monodisperse structures of controlled shape and size make DNA nanostructures of interest as potential drug and gene delivery vehicles. In this review, we discuss several new approaches for the assembly of DNA nanostructures, advances in the modeling of these structures, and we highlight recent studies on the use of DNA nanotechnology for therapeutic applications such as drug delivery in tumor models.

The second leading cause of death in the United States, cancer is at its most dangerous as it spreads to secondary locations. Cancer cells in the blood stream, or circulating tumor cells (CTCs), present an opportunity to study metastasis provided they may be extracted successfully from blood. Engineers have accelerated the development of technologies that achieve this goal based on exploiting differences between tumor cells and surrounding blood cells such as varying expression patterns of membrane proteins or physical characteristics. Collaboration with biologists and clinicians has allowed additional analysis and will lead to the use of these rare cells to their full potential in the fight against cancer.

Cancer metastasis is a multi-step, secondary tumor formation that is responsible for the vast majority of deaths in cancer patients. Animal models have served as one of the major tools for studying metastatic diseases. However, these metastasis models inherently lack the ability to decouple many of the key parameters that might contribute to cancer progression, and therefore ultimately limit detailed, mechanistic investigation of metastasis. Recently, organ-on-a-chip model systems have been developed for various tissue types with the potential to recapitulate major components of metastasis. Here, we discuss recent advances in in vitro biomimetic on-a-chip models for cancer metastasis.

Engineered cardiac tissues hold great promise for use in drug and toxicology screening, in vitro studies of human physiology and disease, and as transplantable tissue grafts for myocardial repair. In this review, we discuss recent progress in cell-based therapy and functional tissue engineering using pluripotent stem cell-derived cardiomyocytes and we describe methods for delivery of cells into the injured heart. While significant hurdles remain, notable advances have been made in the methods to derive large numbers of pure human cardiomyocytes, mature their phenotype, and produce and implant functional cardiac tissues, bringing the field a step closer to widespread in vitro and in vivo applications.

The dominant roles of the tumor microenvironment in regulating tumor formation, progression, and metastasis have driven the application of tissue engineering strategies in cancer biology. Highly dynamic and reciprocal communication of tumor cells with their surroundings suggests that studying cancer in custom-designed biomaterial scaffolds may lead to novel therapeutic targets and therapeutic regimens more reliably than traditional monolayer tissue culture models. As tissue engineering becomes progressively more successful in recapitulating the native tumor environment, critical insights into mechanisms of tumor resistance may be elucidated, to impact clinical practice, drug development, and biological research. We review here the recent developments in the use of custom-designed biomaterial scaffolds for modeling human tumors.

Cancer spread (metastasis) is responsible for 90% of cancer-related fatalities. Informing patient treatment to prevent metastasis, or kill all cancer cells in a patient's body before it becomes metastatic is extremely powerful. However, aggressive treatment for all non-metastatic patients is detrimental, both for quality of life concerns, and the risk of kidney or liver-related toxicity. Knowing when and where a patient has metastatic risk could revolutionize patient treatment and care. In this review, we attempt to summarize the key work of engineers and quantitative biologists in developing strategies and model systems to predict metastasis, with a particular focus on cell interactions with the extracellular matrix (ECM), as a tool to predict metastatic risk and tropism.

The discovery of antibiotics is one of the most important advances in the history of humankind. For eighty years human life expectancy and standards of living improved greatly thanks to antibiotics. But bacteria have been fighting back, developing resistance to our most potent molecules. New, alternative strategies must be explored as antibiotic therapies become obsolete because of bacterial resistance. Mathematical models and simulations guide the development of complex technologies, such as aircrafts, bridges, communication systems and transportation systems. Herein, models are discussed that guide the development of new antibiotic technologies. These models span multiple molecular and cellular scales, and facilitate the development of a technology that addresses a significant societal challenge. We argue that simulations can be a creative source of knowledge.

Stochasticity in the dynamics of small reacting systems requires discrete-probabilistic models of reaction kinetics instead of traditional continuous-deterministic ones. The master probability equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks. With the first solution of chemical master equations, a wide range of experimental observations of small-system interactions may be mathematically conceptualized.

Identifying the network of biochemical interactions that underpin disease pathophysiology is a key hurdle in drug discovery. While many components involved in these biological processes are identified, how components organize differently in health and disease remains unclear. In chemical engineering, mechanistic modeling provides a quantitative framework to capture our understanding of a reactive system and test this knowledge against data. Here, we describe an emerging approach to test this knowledge against data that leverages concepts from probability, Bayesian statistics, and chemical kinetics by focusing on two related inverse problems. The first problem is to identify the causal structure of the reaction network, given uncertainty as to how the reactive components interact. The second problem is to identify the values of the model parameters, when a network is known a priori.