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Life cycle assessments (LCAs) provide valuable guidance regarding environmental implications of design and manufacturing choice; however, they remain resource intensive and time consuming. Streamlining approaches have been developed to address these issues. One of these streamlining approaches, structured under-specification and probabilistic triage, develops a high level assessment of the product or service in question, and only obtains more data on those parameters that contribute most both to the uncertainty and the total impact. In this paper, we build upon the structured under-specification and probabilistic triage methodology and include metrics to determine when sufficient data has been collected. This method enables significant reduction in effort to conduct an LCA while still preserving the ability to make resolvable conclusions around environmental choice related to reducing the impact of manufacturing these devices. We demonstrate the efficiency and effectiveness of this methodology on a case study of tablets for which we determine the burden of the product with 30% of the total effort required in a traditional LCA approach, thereby more readily focusing efforts for impact mitigation. We find that the life cycle environmental impact of the product is driven by the materials and manufacturing phase, more specifically the manufacturing of electronic components such as integrated circuits and printed wiring boards.

Optimization of manufacturing processes and practices requires multiple tradeoffs among often competing priorities. This is especially the case for green manufacturing, where meeting sustainability goals often requires the use of more expensive materials and technologies with uncertain effects on product performance. Not only are decisions regarding such trade-offs difficult to make, these decisions often need to be made with incomplete and uncertain information. These scenarios often result in requests for more information, some of which may be irrelevant for the decision at hand. Value of information (VoI), a decision analytic method for quantifying the expected benefit of acquiring additional information, can be used to improve a wide range of manufacturing decisions. By identifying the contribution of specific model parameter uncertainty to total product or decision uncertainty, VoI can prioritize additional data collection and research strategies to optimally reduce uncertainty and support decisions, i.e., identifying the greatest “bang for the buck.” VoI has been used in many fields including medicine, ecology, and economics, but is rarely used in manufacturing and has never been applied within life cycle assessment (LCA), e.g., to address uncertainty in product development decisions. This paper discusses the use of VoI with LCA in manufacturing and details a case study in which we calculate VoI related to the lifecycle environmental impact of electronic tablet production. We found that LCA-VoI can be successfully used to triage the data gathering process in electronic tablets, to more accurately describe lifecycle environmental impact. We anticipate future applications of LCA-VoI to lead to more cost-effective and sustainable production.

Macrophages, ubiquitous phagocytic cells in the human immune system, play a key role in homeostatic, immunological, and infl ammatory processes. [ 1‐2 ] Macrophages are widely distributed in various tissues and play a central role in clearing invading pathogens, dead cells, and foreign entities through phagocytosis. [ 3 ] Their wide presence in various organs and tissues makes them particularly suited to provide an immediate defense against invading threats. Moreover, macrophages are rapidly recruited to the diseased site by signaling molecules such as cytokines. Hence, macrophages are involved in a wide range of pathological conditions including cancer, atherosclerosis, various infl ammatory diseases such as vasculitis and asthma, and many others. Since macrophages play an indispensable role in most pathological conditions, they represent an ideal target for therapeutic applications. Several approaches seeking to use macrophages for targeted therapies involve feeding therapeutic nanoparticles to macrophages ex vivo, followed by re-injection of the macrophages to target the diseased site. This approach has shown promising results for treating HIV infections [ 4 ] , brain disorders, [ 5 ] and solid tumors. [ 6 ] While this strategy is effective for certain conditions, its applications are limited by the fact that the drug carriers are sequestered within the phagosome of macrophages, which reduces the release rates, and in certain cases, degrades the drug. This limitation can be potentially addressed by designing particles that: i) attach to the macrophage surface, ii) avoid internalization, iii) do not interfere with macrophage function, and iv) release the encapsulated drugs in a controlled manner. However, development of materials that simultaneously fulfi ll these requirements is a signifi cant challenge. Herein, we report the ability of cellular backpacks to successfully encapsulate and controllably release drugs and avoid phagocytic internalization while remaining on the macrophage’s surface. These characteristics point to new possibilities in creating cell-based bio-hybrid devices that leverage both the functions of the encapsulated cargo (drugs, nanoparticles, etc.) and the native functions of the cell. Cellular backpacks are fabricated using a standard photolithography lift-off technique of layer-by-layer and spray deposited fi lm. [ 7 ] Briefl y, a positive photoresist is patterned with regularly spaced 7- μ m-diameter holes that extend down to the substrate. Next, a layer-by-layer deposited fi lm consisting of alternating hydrogen bond donor‐acceptor pairs is deposited, and this layer comprises the release region that tethers the rest of the backpack to the substrate. Two hydrogen-bonded regions were used, and details can be found elsewhere. [ 7 ] Next, a Polyelectrolyte multilayer (PEM) of either (FITC-PAH/MNP) or (PDAC/SPS) is deposited to provide suffi cient mechanical rigidity for the backpack to survive the fi nal acetone sonication step [FITC =