Early-stage Decisions Research Articles

Care Pathway Analysis to Inform the Earliest Stages of Technology Development: Scoping Oncological Indications in Need of Innovation

ObjectivesIdentifying unmet needs for innovative solutions across disease contexts is challenging but important for directing funding and research efforts and informing early-stage decisions during the innovation process. Our aim was to study the merits of care pathway analysis to scope disease contexts and guide the development of innovative devices. We used oncologic surgery as a case study, for which many intraoperative imaging techniques are under development. MethodsCare pathway analysis is a mapping process, which produces graphical maps of clinical pathways using important outcomes and subsequent consequences. We performed care pathway analyses for glioblastoma, breast, bladder, prostate, renal, pancreatic, and oral cavity cancer. Differences between a “perfect” care pathway and the current care pathway in terms of percentage of inadequate margins, associated recurrences, quality of life, and 5-year overall survival were calculated to determine unmet needs. Data from The Netherlands Cancer Registry and literature were used. ResultsCare pathway analysis showed that highest percentages of inadequate margins were found in oral cavity cancer (72.5%), glioblastoma (48.7%), and pancreatic cancer (43.9%). Inadequate margins showed the strongest increase in recurrences in cancer of oral cavity, and bladder (absolute increases of 43.5% and 41.2%, respectively). Impact on survival was largest for bladder and oral cavity cancer with positive margins. ConclusionsCare pathway analysis provides overviews of current clinical paths in multiple indications. Disease contexts can be compared via effectiveness gaps that show the potential need for innovative solutions. This information can be used as basis for stakeholder involvement processes to prioritize care pathways in need of innovation.

Concept and application of the probability of pharmacological success (PoPS) as a decision tool in drug development: a position paper

BackgroundIn drug development, few molecules from a large pool of early candidates become successful medicines after demonstrating a favourable benefit-risk ratio. Many decisions are made along the way to continue or stop the development of a molecule. The probability of pharmacological success, or PoPS, is a tool for informing early-stage decisions based on benefit and risk data available at the time.ResultsThe PoPS is the probability that most patients can achieve adequate pharmacology for the intended indication while minimising the number of subjects exposed to safety risk. This probability is usually a function of dose; hence its computation typically requires exposure–response models for pharmacology and safety. The levels of adequate pharmacology and acceptable risk must be specified. The uncertainties in these levels, in the exposure–response relationships, and in relevant translation all need to be identified. Several examples of different indications are used to illustrate how this approach can facilitate molecule progression decisions for preclinical and early clinical development. The examples show that PoPS assessment is an effective mechanism for integrating multi-source data, identifying knowledge gaps, and forcing transparency of assumptions. With its application, translational modelling becomes more meaningful and dose prediction more rigorous. Its successful implementation calls for early planning, sound understanding of the disease-drug system, and cross-discipline collaboration. Furthermore, the PoPS evolves as relevant knowledge grows.ConclusionThe PoPS is a powerful evidence-based framework to formally capture multiple uncertainties into a single probability term for assessing benefit-risk ratio. In GSK, it is now expected for governance review at all early-phase decision gates.

Optimal Conversion of Organic Wastes to Value-Added Products: Toward a Sustainable Integrated Biorefinery in Denmark

It is crucial to leave behind the traditional linear economy approach. Shifting the paradigm and adopting a circular (bio)economy seems to be the strategy to decouple economic growth from continuous resource extraction. To this end, producing bio-based products that aim to replace a part, if not all, of the fossil-based chemicals and fuels is a promising step. This can be achieved by using multi-product integrated biorefineries that convert organic wastes into chemicals, fuels, and bioenergy to optimize the use and close the materials and energy loops. To further address the development and implementation of organic waste integrated biorefineries, we proposed the open-source organic waste to value-added products (O2V) model and multi-objective optimization tool. O2V aims to provide a quick and straightforward holistic assessment, leading to identifying optimal or near-optimal design, planning, and operational decisions. This model not only prioritizes economic benefits but also takes on board the other pillars of sustainability. The proposed tool is built on a comprehensive superstructure of processing alternatives that include all stages concerning the conversion of organic waste to value-added products. Furthermore, it has been framed and formulated in a “plug-and-play” format, where, when required, the user only needs to add new process data to the structured information database. This database integrates data on (i) new processes (e.g., different conversion technologies), (ii) feedstocks (e.g., composition), and (iii) products (e.g., prices), among others. Due to Denmark’s high availability of organic waste, implementing a second-generation integrated biorefinery in Denmark has been chosen as a realistic showcase. The application of O2V efficiently led to the identification of trade-offs between the different sustainability angles. Thus, it made it possible to determine early-stage decisions regarding product portfolio, optimal production process, and related planning and operational decisions. Henceforth, it has been demonstrated that applying O2V aids in shifting the fossil to bio-based production, thereby contributing to the switch toward a circular bioeconomy.

UAVs to Monitor and Manage Sugarcane: Integrative Review

Pilotless aircraft systems will reshape our critical thinking about agriculture. Furthermore, because they can drive a transformative precision and digital farming, we authoritatively review the contemporary academic literature on UAVs from every angle imaginable for remote sensing and on-field management, particularly for sugarcane. We focus our search on the period of 2016–2021 to refer to the broadest bibliometric collection, from the emergence of the term “UAV” in the typical literature on sugarcane to the latest year of complete publication. UAVs are capable of navigating throughout the field both autonomously and semi-autonomously at the control of an assistant operator. They prove useful to remotely capture the spatial-temporal variability with pinpoint accuracy. Thereby, they can enable the stakeholder to make early-stage decisions at the right time and place, whether for mapping, re-planting, or fertilizing areas producing feedstock for food and bioenergy. Most excitingly, they are flexible. Hence, we can strategically explore them to spray active ingredients and spread entomopathogenic bioagents (e.g., Cotesia flavipes and Thricrogramma spp.) onto the field wherever they need to be in order to suppress economically relevant pests (e.g., Diatraea saccharalis, Mahanarva fimbriolata, sugarcane mosaic virus, and weeds) more precisely and environmentally responsibly than what is possible with traditional approaches (without the need to heavily traffic and touch the object). Plainly, this means that insights into ramifications of our integrative review are timely. They will provide knowledge to progress the field’s prominence in operating flying machines to level up the cost-effectiveness of producing sugarcane towards solving the sector’s greatest challenges ahead, such as achieving food and energy security in order to thrive in an ever-challenging world.

Novel super-reduced, pedagogical model for scoping net zero buildings

Since early-stage decisions have the largest impact on climate related emissions, if modelling is to help deliver zero carbon designs, tools are needed that can be used by those involved at this stage. By contrast, tools that require a detailed description of the building or a specialist have less usefulness at this point in the design cycle. So, just how simple can models be (mathematically and interface-wise), to give meaningful answers to decisions such as the shape of the building and the glazing ratio? The ideal tool would be pedagogical and leave the user with knowledge that they could apply even earlier to the next project. In this work we present ZEBRA, a highly simplified, quick-to-use, model for scoping zero-carbon buildings. The model only requires approximately 33 inputs, no training, considers embodied emissions and renewables and leaves the user upskilled on zero carbon design. The predictions from 5 very low energy buildings placed into 559 climates obtained by this new model are compared to the leading model for high-performing buildings. The average difference was 0.9 kWh·m−2·a−1 (SD = 0.6). The mean time taken to model a building by someone not previously exposed to ZEBRA was 35 min (SD = 8), and 17 min (SD = 3) on second use. Therefore, ZEBRA is highly accurate when compared to the best-in-class tool and can be used quickly by the uninitiated. Hence ZEBRA has the potential to be highly useful as a first-pass tool whilst simultaneously rapidly upskilling the industry.

Evolution in Design Methodology for Complex Electric Ships

Modern ships are highly complex technological systems and have a long and resource-intensive development cycle. Moreover, the final design must comply with many specific technical and regulatory requirements while constraining the capital and operational expenditures. Decisions made during the early stages of design have a large impact on ship functionality and determine the overall configuration of the ship; the advanced computational resources available today can be used to change the traditional approach to ship design, significantly improving the data available for these early-stage decisions. Moreover, the new methodologies can improve the ability to assess the impact of innovative technologies such as those inherent in the complete electrification of ships, and can simultaneously allow visualization of a three-dimensional (3D) virtual prototype of the designs. In this article, a methodological approach is presented that exemplifies these advantages.

Characterizing general arrangements and distributed system configurations in early-stage ship design

General arrangement and distributed system design is a complex problem that is a fundamental aspect of ship design. Current approaches to this design problem employ a paradigm of using automated tools to generate and analyze potential vessel solutions. These approaches rely on the generation and optimization of vessel models based on design parameters. Created vessel models are then evaluated and compared to understand how parameters influence possible vessel characteristics. This process is time and resource intensive, which limits its application in early-stage design when many critical arrangement and distributed system design decisions are made. In this paper a new approach is proposed to complement the automated tool-based paradigm. For a vessel with a defined set of systems to be arranged and connected, the approach measures the probabilistic arrangement and distributed system configuration, without generating vessel models. This efficiently provides leading indicators of the expected design outcomes and resultant vessel characteristics, which can help guide early-stage decisions and lead to better applications of resource-intensive design tools. In this paper, methods supporting this approach are presented and application is demonstrated on a naval frigate concept design.

Natural fibre selection for composite eco-design

Abstract Natural fibre composites (NFC) are gaining interest in manufacturing because they address some of the environmental problems of traditional composites: use of non-renewable resources, and large impacts related to their production and disposal. Since natural fibres are not yet optimized for composite production, it is crucial to identify the most appropriate applications, and determine the optimal fibre/matrix ratio. A methodology is proposed for early-stage decisions support on selection of bio-composite materials. Results help identify the application with the largest reduction in environmental burden and show that the fibre/matrix combination with the lowest environmental burden also has the best mechanical properties.

Let My People Go: Ethnic In-Group Bias in Judicial Decisions - Evidence from a Randomized Natural Experiment

Does ethnic identity affect judicial decisions? We provide new evidence on ethnic biases in judicial behavior, by examining the decisions of Arab and Jewish judges in first bail hearings of Arab and Jewish suspects in Israeli courts. Our setting avoids the potential bias from unobservable case characteristics by exploiting the random assignment of judges to cases during weekends, and by focusing on the difference in ethnic disparity between Arab and Jewish judges. The study concentrates on the early-stage decisions in the judicial criminal process, controlling for the state's position, and excluding agreements, thereby allowing us to distinguish judicial bias from other sources of ethnic disparities. We find systematic evidence of in-group (same ethnic group) bias in detention decisions. However, in cases where the decision is to detain, no ethnic bias was found in the length of the detention. Possible interpretations and implications of these findings are discussed.

Let My People Go? Ethnic Bias of Jewish and Arab Judges in Pretrial Detention Decisions in Israel

This is the first study to assess the effect of suspects' ethnic identity on pre-trial detention decisions across the ethnic identity of the deciding judges. Concentrating on the early-stage decisions in the criminal process, controlling for the state's position and for the ethnicity of the judges, and excluding agreements, allows us to better control of intervening factors, and for evaluating competing explanations of the findings under assumptions of incomplete information. The multi-level analyses draw on a sample of pretrial detention decisions in three Israeli magistrate courts. We find that the ethnicity of suspects carries a significantly different effect between Arab and Jewish judges. When the judge is Jewish, a Jewish defendant has significantly higher chances of being released on bail than a similarly situated Arab suspect. Yet, while an average inverse bias was found for Arab Judges, the ethnic identity of the defendant was not found to have a significant effect in this condition. The implications of the findings, as well as the merit of concentrating on early-stage judicial decisions in the study of judicial ethnic bias are discussed.

Early technology assessment of new medical devices

In the United States, medical devices represent an eighty-billion dollar a year market. The U.S. Food and Drug Administration rejects a significant number of applications of devices that reach the investigational stage. The prospects of improving patient condition, as well as firms' profits, are thus substantial, but fraught with uncertainties at the time when investments and design decisions are made. This study presents a quantitative model focused on the risk aspects of early technology assessment, designed to support the decisions of medical device firms in the investment and development stages. The model is based on the engineering risk analysis method involving systems analysis and probability. It assumes use of all evidence available (both direct and indirect) and integrates the information through a linear formula of aggregation of probability distributions. The model is illustrated by a schematic version of the case of the AtrialShaper, a device for the reduction of stroke risk that is currently in the preprototype stage. The results of the modeling provide a more complete description of the evidence base available to support early-stage decisions, thus allowing comparison of alternative designs and management alternatives. The model presented here provides early-stage decision-support to industry, but also benefits regulators and payers in their later assessment of new devices and associated procedures.

Assessing the natural ventilation potential of the Basel region

A method is proposed to assess the natural ventilation potential (NVP) of the Basel Region, Switzerland, by taking into account the most comprehensive set of factors involved in natural ventilation. These factors are either driving forces, such as wind pressure and stack effect, or constraints, like noise pollution and atmospheric pollution. The process considers these factors in an ordinal qualitative scale and gives its result in this same scale. Climatic data are extracted from a mesoscale atmospheric simulation model referred to as Finite Volume Model (FVM), accounting for the effect of the urban fabric and taking as boundary conditions data coming from a model of the Swiss national weather service (MeteoSwiss). FVM provides an urban turbulence module which specifically simulates the effects of urban areas on the meteorology. Qualitative scales allow to bypass the problem of the inaccuracy of some parameters, which can be very high, especially in urban environment and in the pre-design phase of a construction project. Actually, the method is particularly suitable for designers intending to take early-stage decisions.

Toward a Small Donor Democracy: The Past and Future of Incentive Programs for Small Political Contributions

Political contribution incentive programs are a promising, under-explored means to address the problem of political equality in the American system of campaign finance. If properly designed, these programs - which include tax credits, refunds, and vouchers - could allow all Americans to participate on an equal basis in the crucial early-stage decisions that determine which candidates decide to run and are able to compete effectively. This article, written on behalf of U.S. PIRG, proposes a tax credit for political contributions as a first step toward building a small donor democracy.

Multicriteria assessment of natural ventilation potential

A method is proposed to assess the natural ventilation potential by taking into account the most comprehensive set of factors involved in natural ventilation. These factors are either driving forces, such as wind pressure and stack effect, or constraints, like noise pollution and atmospheric pollution. The process considers these factors in an ordinal qualitative scale and gives its result in that scale. This bypasses the problem of the inaccuracy of some parameters, which can be very high, especially in urban environment and in the pre-design phase of a construction project. Actually, the method is particularly suitable for designers intending to take early-stage decisions.

Optimization of Short Grinding Cycles

Natural fibre composites (NFC) are gaining interest in manufacturing because they address some of the environmental problems of traditional composites: use of non-renewable resources, and large impacts related to their production and disposal. Since natural fibres are not yet optimized for composite production, it is crucial to identify the most appropriate applications, and determine the optimal fibre/matrix ratio. A methodology is proposed for early-stage decisions support on selection of bio-composite materials. Results help identify the application with the largest reduction in environmental burden and show that the fibre/matrix combination with the lowest environmental burden also has the best mechanical properties.