European cities are placing a larger emphasis on urban data consolidation and analysis for optimizing public transport in response to changing urban mobility dynamics. Despite the existing efforts, traffic data analysis often disregards vital situational context, including large-scale events, weather factors, traffic generation poles, social distancing norms, or traffic interdictions. Some of these sources of context data are still private, dispersed, or unavailable for the purpose of planning or managing urban mobility. Addressing the above observation, the Lisbon city Council has already established efforts for gathering historic and prospective sources of situational context in standardized semi-structured repositories, triggering new opportunities for context-aware traffic data analysis.The work presented in this paper aims at tackling the following main research question: How to incorporate historical and prospective sources of situational context into descriptive and predictive models of urban traffic data?We propose a methodology anchored in data science methods to integrate situational context in the descriptive and predictive models of traffic data, with a focus on the three following major spatiotemporal traffic data structures: i) georeferenced time series data; ii) origin-destination tensor data; iii) raw traffic event data. Second, we introduce additional principles for the online consolidation and labelling of heterogeneous sources of situational context from public repositories. Third, we quantify the impact produced by situational context aspects on public passenger transport data gathered from smart card validations along the bus (CARRIS), subway (METRO) and bike sharing (GIRA) modes in the city of Lisbon.The gathered results stress the importance of incorporating historical and prospective context data for a guided description and prediction of urban mobility dynamics, irrespective of the underlying data representation.A novel methodology on how to acquire, consolidate and incorporate different sources of context for the context-enriched analysis of traffic data;The instantiation of the proposed methodology in the city of Lisbon, discussing the role of recent initiatives for the ongoing monitoring of relevant context data sources within semi-structured repositories, and further showing how these initiatives can be extended for the context-sensitive modelling of traffic data for descriptive and predictive ends;A roadmap of practical illustrations quantifying impact of different context factors  on different transportation modes using different spatiotemporal traffic data structures; andA review of state-of-the-art contributions on context-enriched traffic data analysis.The contributions reported in this work are anchored in the empirical observations gathered along the first stage of the ILU project (see footnote 1), providing a study case of interest to be followed by other European cities.Overall, the research offers the following major contributions: European and worldwide cities are entailing complex urban mobility changes to respond to the COVID-19 pandemic crisis and satisfy climate and environmental goals. Urban mobility decarbonisation initiatives, encompassing enhanced public transport, infrastructure interventions towards active modes such as walking and cycling, are aimed to provide a better fit with individual mobility needs and the distribution of traffic generation poles. In this light, most European cities such as Lisbon in Portugal are pursuing technological solutions to face the challenge of dynamically adapting public passenger transportation systems in accordance with the real traffic dynamics. To this end, efforts are being established towards traffic data collection, consolidation and exploration from public and private, individual and active modes of transport.Traffic dynamics are situated, meaning that these are dependent on a high multiplicity of situational factors including spatial urban context , meteorological context, occurring events , calendrical context, or traffic interdictions (including road accidents and construction works). Despite their well-recognized impact on urban mobility, sources of urban context are commonly disregarded for two major reasons. First, some of these sources are unstructured, private or unavailable, preventing their automated consolidation. Second, existing principles for context-aware traffic data analysis remain largely dispersed. In fact, state-of-the-art contributions for context-aware descriptive and predictive tasks generally fail to model the joint impact that these multiple sources of context exert on urban mobility. In addition, existing works generally fail to separate the important role of both historical and prospective sources of context. For instance, historical weather and event data are important to assert the true impact of situational context in transport demand, while prospective events and weather forecasts are essential to support predictions.how to perform context-aware analysis for different spatiotemporal traffic data structures, including georeferenced time series data, origin–destination (OD) tensor data, and raw event data ;how to dynamically consolidate the different sources of situational context; andhow to adapt the learning in accordance with the targeted task, whether descriptive modelling, pattern discovery, anomaly detection or forecasting.The research work presented in this paper aims at tackling the research question: How to incorporate historical and prospective sources of situational context into descriptive and predictive models of urban traffic data? To this end, we propose a comprehensive set of principles for the dynamic acquisition and incorporation of situational context onto traffic data analytics. We tackle the problem of context-augmented traffic data analysis in accordance with three major research needs:The Lisbon city is used as a case study for assessing the proposed research contributions. In recent years, the Lisbon City Council (CML) established protocols to monitor multiple sources of traffic data and situational context. Heterogeneous sources of situational context data are being consolidated in semi-structured repositories, offering unique opportunities for context-aware traffic data analysis. The contributions reported in this work are anchored in the empirical observations gathered along the first stage of the ILU projectThe gathered results consider bus, subway and cycling modes of urban traffic in the Lisbon city to quantify the impact produced by context data sources, showing the corresponding correction factors and motivating their relevance for pursuing context-aware analysis to support urban mobility planning decisions.A novel methodology on how to acquire, consolidate and incorporate different sources of context for the context-enriched analysis of traffic data;The instantiation of the proposed methodology in the city of Lisbon, discussing the role of recent initiatives for the ongoing monitoring of relevant context data sources within semi-structured repositories, and further showing how these initiatives can be extended for the context-sensitive modelling of traffic data for descriptive and predictive ends;A roadmap of practical illustrations quantifying impact of different context factors  on different transportation modes using different spatiotemporal traffic data structures; andA review of state-of-the-art contributions on context-enriched traffic data analysis.Accordingly, this work offers the following major contributions:This paper is structured as follows: Sect. This section provides a structured view on traffic data analysis Sect. , identifFour major sources of traffic data are generally monitored in urban centres: (1) road traffic data produced by stationary devices positioned along the city, and geolocalized speed meters from active mobile devices); (2) automated fare collection (AFC) data from public transport operators, generally consisting of smart card validations from users at stations or vehicles; (3) public transport planning data, generally termed General Transit Feed Specification (GTFS) data, encompassing all information pertaining to schedules, routes, stations of the public carriers in a standardized format; and (4) individual trajectory data collected from mobile devices during active modes of transport.Georeferenced time series data Sect. , generalOrigin–destination tensor data Sect.  mapped fRaw event data Sect. , comprisThe above traffic data structures are generally mapped into new spatiotemporal data structures more conducive to the subsequent data analysis. Generally, we find three major representations of traffic data Fig. :GeoreferTraffic data can generally be represented as georeferenced time series data, pairs .h upcoming observations,Given a time seriesClassical approaches for time series analysis generally rely on statistical principles, including decomposition, auto-regression, differencing, exponential smoothing, and smooth transitioning functions , 45  tensors, generally a numeric three-dimensional e period . Origin In the context of automated fare collection data, entry and exit validations per transport operator are generally paired to identify a trip segment. As a single trip may require commutes within a single carrier or between different carriers, trip segments can be then properly concatenated under specific spatiotemporal assumptions to identify the true origin and destination of a single whole trip . SimilarGiven a single OD tensor, descriptive tasks generally aim at finding frequent patterns or detecting vulnerabilities . For thiAn event is a tupleDescriptive and predictive tasks from event data generally resort to one of the previously covered spatiotemporal data structures Sects. . First, Public events, including: (a) conventions, (b) festivals, (c) concerts, and (d) sport events. The historic and prospective events are currently sourced from two major sites: (1) the planned usage of large halls, stadiums and large open areas in the city of Lisbon, and (2) the cultural agenda of the city;Historic, current and 10-day forecasted weather record data sourced from three meteorological stations maintained by Instituto Português do Mar e da Atmosfera (IPMA). Weather variables with potential impact on traffic include temperature, humidity, wind intensity, precipitation, nebulosity, and visibility;Relevant occurrences in the city, including: (a) road accidents, (b) medical emergencies, (c) fires and floods, (d) logistical help and falling structures, (e) transport requests, (f) conservation and complaints, and (g) rescue and civil protection;Ongoing and planned construction road works (traffic conditioning events) characterized by a set of trajectories with (possibly non-convex) interval of obstruction and accompanying details (including the number of affected ways and whether interruption is spasmodic);commercial] malls, commercial permits, markets, terminals; (2) [utils] citizen spaces, conservatories, social stores, councils, parks, public authorities; (3) [education] public and private schools, universities, institutes; (4) [health] hospitals, health centres, clinics; (5) [sport] sport facilities; (6) [cultural] concert halls, monuments, museums, movie; theatres, amphitheatres; (7) [transportation] public transport networks; and (8) [leisure] recreational spaces;Urban planning of the city with the localization of traffic generation-attraction poles, including: (1) [Other sources of interest including context around active modes of mobility , as well as calendrical context encompassing annotations associated with academic breaks, festivities, holidays and weekly-monthly-yearly seasonal factors.The available sources of situational context consolidated by the Lisbon City Council and considered in the targeted traffic data analysis tasks include:Automated fare collection data from the public transportation network, including card validations and the GPS positioning of public vehicles;Bike sharing data from the Lisbon’s public bike sharing system GIRA, includiRoad traffic data from three major types of sensors: (1) inductive loop detectors in major road junctions in the city, offering discrete views on traffic flow; (2) individual mobile devices with GPS producing aggregated views on traffic congestions , explored in the context of partnerships with WAZE and TomTom; and (3) privacy-compliant cameras in main roads;Other sources: data pertaining to emerging modes of transportation, including private scooter traffic data. An entry requirement for new private operators is precisely the full disclosure of trip records.The Lisbon city Council has established numerous initiatives to pursue a sustainable urban mobility. In the context of urban data monitoring and consolidation, the following sources of traffic data are currently being consolidated:The public transport network in the Lisbon Metropolitan Area (LMA) which includes the Lisbon city council and more 17 municipalities, covers more than 12 transport operators, being CARRIS (the major bus operator in the City of Lisbon) and METRO (the subway operator) distinctively large in passenger volumes and the only modes offering a solid footprint coverage within the Lisbon municipality. The single public bike sharing system is operated by EMEL/GIRA. Apart from active modes of transportation, the providers of bus, subway, railway and inland waterway modes of transport are currently operating under an integrated fare collection system, enabled through the VIVA card initiative. The VIVA card initiative, firstly established between METRO and CARRIS, currently encompasses other carriers interfacing with the city of Lisbon for an operation under a single consolidated ticketing system.Recent attention has been paid to the incorporation of contextual data to enhance the understanding of mobility dynamics and support traffic data analysis . UsuallyTwo major classes of context-sensitive approaches for traffic data analysis can be identified from the existing literature. First, approaches that aim to describe and predict traffic dynamics by segmenting data into chunks according to the available situational context and using only context-specific chunks for understanding and forecasting demand. Second, approaches able to embed the context directly into the models by capturing correlations with the context and using these correlations as corrections to automatically adjust descriptive and predictive models.Context-selective analysis of traffic data segments the available data—whether time series, OD series or raw traffic events—into chunks, each chunk sharing similar context. Data chunks are then used with the purpose of learning context-sensitive descriptive and predictive models. Hence, we can see descriptors and predictors of traffic as a set of arbitrarily different context-specific models. More advanced structures can, however, be considered . For insKwoczek et al.  proposedEl-Assi et al.  provide The second option is to allow the learning to analyse context and its integration with traffic data, thus allowing the available context to shape the learned models. Gallop et al.  explore Rodrigues et al.  introducTo analyse the impact of social events, Tomaras et al.  propose Ashqar et al.  considerThomas et al.  studied Principles to incorporate context within neural networks have been additionally proposed. Thu et al.  propose Anchored in the surveyed state-of-the-art contributions and practical experience from the established R&D efforts with the Lisbon city Council, this section introduces a methodology for the incorporation of context in big traffic data analytics Fig. . The metTwo major principles are proposed for the automated acquisition of situational context. First, social media, public administration repositories, weather portals, online calendars of festivities, cultural agendas, theatre sites, and online news can be periodically explored with the aim of retrieving specific context sources of interest. Wibisono et al. , TempelmLisboa Aberta” (Open Lisbon) portal. The repositories are periodically updated in order to facilitate administrative tasks, as well as to potentiate complementary strategic and research initiatives. The repositories can be standardly accessed, and the monitored contents are maintained in standard JSON formats  stores the sources of situational context listed in Sect. ats Fig.  in orderSources related with planned events can be automatically annotated in accordance with their typology and duration. The spatial extent, as well as the historical and prospective duration of some of these events, such as construction works, is maintained in these repositories. In contrast, for public events without such information, rules can be dynamically inferred with expectations on the average event duration in accordance with its typology. An illustrative rule is that sport events approximately impact entry validations at public transport stations 120 min before the game and up to 60 min after the game. Context-specific deviations to traffic can be assessed against daily traffic expectations to determine the spatiotemporal extent of the event. The deviation of demand can be assessed by considering an envelope  over a model of traffic demand in accordance with the principles highlighted in one of our previous works . In the The available sources of context data and traffic data are consolidated in a multi-dimensional database . TrafficThe integrative analysis of traffic data against the available context offers unique opportunities to understand and anticipate traffic dynamics. To this end, statistically significant correlations between mobility dynamics and their situational context can be first identified and then used to enhance the targeted descriptive and predictive models.Under the previously suggested consolidation schema, comprehensive correlations can be found between traffic records and their accompanying situational context using traditional Pearson or Spearman indices, as well as principles from multi-dimensional subspace clustering and relational pattern mining , 13, 15.In alternative, traffic data can be segmented in accordance with the available situational context—traffic records under comparable events and calendrical, meteorological and spatial context. Context-specific slices can be then selected for learning context-specific descriptors and predictors , 21.Finally, the available context can be seen as additional variables, whether static or temporal, used to augment traffic data. The context-enriched traffic data can then be subjected to machine learning approaches able to deal with heterogeneous, multivariate and spatiotemporal data structures. Neural network approaches are a natural candidate towards this end, as they can receive an arbitrarily-high number of inputs and be architecturally optimized to capture their inherent temporal, spatial and modal dependencies , 35, 40.context-driven corrections, context-driven data segmentation and context-driven data augmentation—can be pursued irrespectively of the underlying data structure. Sections The application of these three groups of principles—Context-driven corrections have been proposed for both classical and machine learning approaches for time series analysis. Context-driven data segmentation is not suggested for classical descriptive and predictive approaches, such as SARIMA and Holt-Winters, due to the observed temporal discontinuities with arbitrarily high duration produced by the segmentation procedures.Modelling and forecasting traffic demand are central tasks. In the surveyed work, different principles were recovered to support these tasks in the presence of situational context , 39, 42.context-enriched neural network approaches were proposed by extending recurrent neural network layering to incorporate both historical and prospective sources of context [In the context of the ILU project,  context . One of Prospective sources of context, including weather forecasts or planned events, may be available along the horizon of prediction. Considering the introduced sequential composition of LSTMs as the target architecture, prospective context data can then be inputted into the last LSTM component to adjust predictions see Fig. . In thisTwo major groups of principles are devised in accordance with the two major OD data structures introduced Sect. Context-aware tasks along the first scenario generally aim at assessing the impact of a well-defined context factor  in traffic. In this light, the time periods along a given calendar with similar situational context (events of same magnitude or comparable weather) can be marked. As a result, multiple OD tensors sharing comparable context are produced. Differences between OD entries can be extracted using principles from contrast set mining  or visuaContext-aware tasks along the second scenario—OD tensor series—generally resort to the introduced principles for context-aware time series analysis. To capture the inherent spatial nature of OD data, particular attention should be placed to guarantee that the selected learning approaches are able to capture dependencies across series (OD entries). In this context, cross-series correlation factors can be explored in distance-based approaches using multivariate distances with cross-variable dependencies  and in nTemporal association rules can be inferred from traffic events for the purpose of describing (forecasting) available (upcoming) traffic events . The leaConsidering the city of Lisbon as the case study, this section explores the impact produced by heterogeneous sources of situational context – planned events Sect. , trafficFigures CARRIS (the major bus carrier in Lisbon) near to the "Luz" stadium in the period between October, 2 and October, 15, 2018. The soccer match occurred in Sunday, October 7 at 17h30. The subsequent Sunday is highlighted to facilitate comparisons, providing strong evidence of the disruptive nature of the event in passenger demand. The sudden passenger peak could be easily mistaken as a statistical outlier in the absence of context data.Figure Colégio Militar station, while Fig. Benfica and Lyon, and the second between Benfica and Portimonense—supporting the importance of considering the content of the event.Figure Oriente station, yet this time with the aim of measuring the impact on traffic demand generate by a large-scale concert. After detecting unusually high demand on this station on Wednesday, October 1 2019, the cultural records revealed the presence of a 2-h concert from Michael Bublé at the Altice Arena concert hall, in the immediacies of Oriente station. Figure A similar analysis was carried out for the Restauradores" and “Av. da Liberdade", with the finish line being placed near the bus stop "Praça do Comércio". This interdiction is represented in purple colour. On October 21 at 10 am, a bike event was acclaimed at "Praça do Comércio". This interdiction is represented with yellow color. On October 28 at 12am, an event inserted in the repository without content disclosure occurred at "Restauradores" and "Av. da Liberdade". The associated interdiction is represented in green. For this analysis, we consider passenger volume time series at three stops: "Restauradores"  are often disregarded, thus generally hampering traffic data analysis. Figure Instituto Superior Técnico The selected modes and sources of traffic data and their representation, whether through georeferenced time series, origin–destination (OD) tensors or raw traffic events;ii)The type of context, whether historical or prospective, and whether situational, meteorological or/and calendrical;iii)The targeted task, whether descriptive or predictive; andiv)context-driven traffic corrections, context-driven traffic data segmentation or context-sensitive learning approaches.The pursued principles for the context-augmented analysis of traffic data, whether given by Moved by the undoubted observation that accessible contextual factors strongly shape public transport demand, this work provides a structured view on how to incorporate heterogeneous sources of situational context into traffic data analysis for urban mobility planning. To this end, we surveyed and discussed important methodological principles towards the integrative analysis of traffic data and its situational context in accordance with:Using the city of Lisbon as a case study, we further motivate the role of well-established initiatives towards the collection of a wide-diversity of sources of relevant urban context into (semi-)structured repositories, allowing the dynamic acquisition and consolidation of both historical and prospective context information. In this light, multivariate, temporal and spatial urban content is standardly assigned to context records, allowing the real-time augmentation of traffic data using simplistic online routines to fetch new or updated context records. For instance, a comprehensive list on the requested occupancies of city halls, theaters, congress rooms, exposition centers, stadiums, and other large facilities is maintained in real-time. Similarly, historical and prospective geospatial information on road interdictions and other complementary events with potential impact on urban mobility are maintained by the city Council. In this work, the consolidation of context and traffic records is established via a multi-dimensional model in accordance with their spatial and temporal footprint.Once context data is consolidated, context-guided modelling of traffic dynamics becomes possible. In particular, the gathered results further motivate the relevance of context-sensitive correction, segmentation and learning principles for traffic data analysis. As extreme weather conditions affect transport modal preferences, we saw that weather-demand correlations can be assessed and used to discount predictive models of cycling demand with positive impact in the city of Lisbon. The analysis of congestions in road traffic data is currently undertaken by segmenting traffic in multiple comparable periods in accordance with calendrical constraints and additional available situational context. We further discussed how neural networks can be extended to incorporate both historical and prospective sources of context using masking principles for predictive tasks. To this end, prospective context, such as weather forecasts or planned events, can act as a regularizer of predictions and has shown to improve the forecast of station congestions at the Lisbon's public bike sharing system. Public transport reinforcement decisions for large-scale events, such as planned festivals and soccer matches, can further benefit from context-comparable origin–destination tensor data. CARRIS, the major bus operator in Lisbon, currently relies on dynamic multimodal origin–destination tensor data to assess demand deviations caused by public events. Concluding, the gathered results stress the importance of incorporating historical and prospective context data for a guided description and prediction of urban mobility dynamics, irrespective of the underlying data representation.


We share recommendations on 3 important pivots away from longstanding approaches to continued professional development and in-service training programs that have demonstrated a measurable benefit across a diversity of health-related applications and projects. The first pivot involves shifting from focusing on using data primarily for reporting purposes. Encouraging team members within facilities to regularly use their own data to track, review, and measure priority quality indicators promotes the quality improvement process and can improve service delivery outcomes.The second pivot involves shifting from focusing on repeated, external, quality assurance assessments, often from the district or subnational level, to using facility team-based internal service delivery indicator data reviews to implement quality improvement efforts based on these data.These pivots toward health care provider and facility manager ownership of the quality improvement process also lead to the third pivot, which involves shifting from one-time, group-based training toward workplace-based educational interventions. Team involvement in interpreting their facility data can lead to identifying targeted team-based learning needs and the potential need for individual mentoring. Many countries invest large portions of their health budgets on standalone, in-service training to enhance skills and performance of health care providers followed by repeated external supportive supervision visits, which often find similar challenges and gaps and result in a low return on investment. An increasing body of evidence points to the limitations of traditional training and supportive supervision to improve performance. A 2016 review of nationally representative surveys in 7 sub-Saharan Africa countries that examined the association of in-service training and supervision with provider quality in antenatal and sick child care found these traditional interventions were associated with only modest improvements.P<.001. The surgical site infection rate at baseline, before the intervention, was 13.9%. After 18 months of program implementation, this rate declined significantly to 0.7% , showing that the interventions had a positive impact. The same study also found a 38.5% reduction in the perioperative mortality rate related to cesarean deliveries in participating facilities.Subnational management teams invest significant effort collecting data on service delivery indicators to report up the management chain. We recommend investing greater effort to help support teams within facilities collect, review, and use their own priority service delivery indicators to identify gaps and improve performance rather than only report up the management chain. Across several projects, we have seen the power of helping teams within facilities use a few key service delivery indicators to measure quality improvement progress and identify areas where training is needed. The Tanzania Safe Surgery 2020 project, funded by the GE Foundation and ELMA Foundation and implemented from January 2018–December 2020 in the Kagera and Mara regions of Tanzania, used a team-based approach to introduce a package of proven quality improvement and capacity building interventions for surgical teams  in health care facilities. These approaches included enhancing teamwork, communication, and clinical/surgical skills that focused on team processes to promote a culture of patient safety and introduce infection prevention bundles, safety tools , regular audit and feedback, process mapping to improve functional organization of services, and regular data review of a few priority service delivery indicators to drive quality improvement efforts. These approaches resulted in significant improvements in health care provider performance and client health outcomes. The Surgical Safety Checklist utilization rate for cesarean deliveries increased from 3.7% (5 of 136) to 95.1% (136 of 143) with We have seen the power of helping teams within facilities to use a few key service delivery indicators to measure quality improvement progress and identify areas where training is needed.Regular data reviews of priority service delivery indicators tracked on facility wall charts and sharing data and learning with other sites were instrumental in identifying the need for training or clinical mentorship, prioritizing problems to address, creating quality improvement plans, and tracking improvements over time. During a team reflection meeting, Dr. Leopold Tibyehabwe, Safe Surgery 2020 team member, commented that beyond the improved performance, the regular data use increased provider confidence and ownership:Data is the way we are making the teams active in the sessions. They are engaged in the sessions because they know this is their data. It has really strengthened their confidence.As of April 2021, 4 months after the program ended, formerly supported program teams were still sharing their data with each other, indicating a significant change in the manner of data use.Regular review of a few priority service delivery indicators, tracked and visualized using facility wall charts, was also used to drive action under the Expansion of Malaria Services (EMS) project in Liberia, supported from 2017–2019 by the U.S. Agency for International Development (USAID)-funded Maternal and Child Survival Program. Similar to the Tanzania Safe Surgery 2020 project, facility wall charts were used to help facilities track and regularly review relevant malaria data and key service delivery indicators for quality improvement to target ongoing training and mentorship and to identify other interventions that were needed. At the completion of the project, more than 80% of health workers expressed that the wall charts were user-friendly and more than 90% of the staff were confident in plotting and interpreting 3 doses of intermittent preventive treatment of malaria in pregnancy (IPTp3) data in the wall chart.Across multiple countries, large investments are made in external, supervision visits to assess facility and provider performance, a strategy recognized as not resulting in improved health care provider performance.a structured organizational process for involving people in planning and executing a continuous flow of improvement to provide quality health care that meets or exceeds expectations.Shifting the balance of funding to invest more in support of facility-based quality improvement efforts and less on repeated external assessment visits may result in better cost efficiencies and greater health care provider performance.P<.0073; z=2.6817).In both the Safe Surgery 2020 and the EMS projects, continuous quality improvement approaches were a key intervention supported by as-needed, workplace-based training and/or clinical mentoring, This is supported by literature, which recognizes that this combination of efforts can result in greater effect size.Under the Safe Surgery 2020 project in Tanzania, continuous quality improvement supported by data review and digital technologies facilitated in-person, virtual, and e-mentoring to support teams within facilities. During the project, in-person Safe Surgery 2020 mentors prioritized data use, supported the development of clinical and nonclinical skills , and strengthened the organization of services and implementation of each teams' quality improvement plan. Project ECHO, a partner on the Safe Surgery 2020 project in Tanzania, supported additional weekly virtual mentoring via videoconferencing sessions for 10 sites, with a focus on case review and didactic presentations by clinical mentors.  E-mentoring was provided through WhatsApp groups for mentors and surgical teams that were formed early in the program by region for real-time knowledge exchange, group problem solving, and data and resource sharing. As part of regular data reviews, teams applied continuous quality improvement practices. For example, in response to service delivery indicator data trending in the wrong direction , teams identified the problem, performed root cause analysis, and took corrective actions.Invest greater effort to provide needs-based, just-in-time workplace-based or on-site training or clinical mentoring supported by digital technology Despite the lack of evidence to support one-time, group-based trainings, often they are still the default intervention to improve health care provider performance, frequently defined as adherence to clinical treatment protocols or guidelines.Shifting toward targeted, needs-based training based on health outcomes data and leveraging technology to support more efficient delivery can result in improved health care provider performance and lead to greater cost efficiencies.The Saving Lives at Birth study in Uganda in 2014 paired Helping Mothers Survive Bleeding after Birth  with Helping Babies Breathe . This was a USAID-funded Saving Lives at Birth Grand Challenges for Development research project. The goal was to build the capacity of providers in all 125 facilities conducting births in 12 districts to deliver these interventions. A 1-day training of the entire team—comprising midwives, nurses, clinical officers, and medical doctors—was conducted at each facility on postpartum hemorrhage. This was repeated 2 months later for birth asphyxia. Facility teams were supported to offer low-dose, high-frequency repeated practice sessions for these critical skills. Across all facilities, there was a 17% reduction in postpartum hemorrhage, 47% reduction in retained placenta, 34% reduction in intrapartum stillbirth, and 62% reduction in early newborn death.The Safe Surgery 2020 project in Tanzania provides an example of how digital technology expanded the provision of workplace-based clinical mentorship and training and the use of data to target training efforts. Starting in June 2020, in response to lockdowns due to the coronavirus disease (COVID-19) pandemic, the project continued to use the WhatsApp groups to share newly created instructional videos that used anatomical models and conduct videoconference sessions. Teams implemented virtual skills practice and participated in virtual mentorship sessions in their workplace. Each virtual mentoring session started with a review of facility service delivery indicator data and trends related to the selected topic for that session and then addressed challenges and quality improvement interventions the team implemented. The project’s clinical mentors delivered virtual mentorship to networks of 5–6 facilities at each session; during these sessions, each network had data reviews, quality improvement discussions, and a mini-case study or a video demonstration. The instructional video demonstrations were delivered via WhatsApp. The use of video added to the quality and richness of content and allowed learners to return to the content at their own pace and schedule if desired. In addition, providers recorded their skills practice in simulation with anatomical models and shared with clinical mentors for virtual feedback. Use of virtual mentorship allowed the mentor team to have more touch points for review and discussion, while reducing the burden on them to physically travel or leave their workplace to provide support.We see great potential in the power of leveraging mobile technology to support more efficient, cost-effective workplace-based learning. Delivering efficient, just-in-time learning via mobile devices can reduce in-person instruction time and allow programs to reach greater numbers of providers. Under the Safe Surgery 2020 project, WhatsApp was used to link participating teams within the facility networks for delivering needs-based, user-driven, just-in-time microlearning via YouTube video links and/or job aids. Participating teams also used WhatsApp to obtain peer support, share data, problem-solve difficult clinical cases, and push out links to key instructional content.Delivering efficient, just-in-time learning via mobile devices can reduce in-person instruction time and allow programs to reach greater numbers of providers.We recognize that these approaches—using service delivery indicators to drive facility-based continuous quality improvement and providing targeted, workplace-based and technology-supported training and/or clinical mentorship—are not novel. However, we believe the thoughtful combination of these 3 pivots can result in improved health care provider performance and client health outcomes, as well as greater return on investments and more sustainable solutions. As digital technology becomes more widespread in LMICs, it can be used in more, and novel, ways as a valuable tool for new methodologies of training and improving health care provider performance. It is important to note that while digital technology allows for efficiency and effectiveness of these approaches, there is no “one size fits all” technology that results in successful outcomes.We have seen the promise of combining these effective pivots that focus on data use, quality improvement, and workplace-based training. We recommend that projects consider these impactful pivots when designing interventions that target improving health care provider performance.


Aging is associated with chronic low-grade inflammation, cancer incidence and mortality. As inflammation contributes to cancer initiation and progression, one could hypothesize that age-associated chronic low-grade inflammation contributes to the increase in cancer incidence and/or mortality observed during aging. Here, we review the epidemiological, therapeutical and experimental evidence supporting this hypothesis. Despite a large body of literature linking aging, inflammation and cancer, convincing evidence for the clear implication of specific inflammatory pathways explaining cancer incidence or mortality during aging is still lacking.Aging is associated with chronic low-grade inflammation, cancer incidence and mortality. As inflammation contributes to cancer initiation and progression, one could hypothesize that age-associated chronic low-grade inflammation contributes to the increase in cancer incidence and/or mortality observed during aging. Here, we review the evidence supporting this hypothesis: (1) epidemiological associations between biomarkers of systemic inflammation and cancer incidence and mortality in older people, (2) therapeutic clues suggesting that targeting inflammation could reduce cancer incidence and mortality and (3) experimental evidence from animal models highlighting inflammation as a link between various mechanisms of aging and cancer initiation and progression. Despite a large body of literature linking aging, inflammation and cancer, convincing evidence for the clear implication of specific inflammatory pathways explaining cancer incidence or mortality during aging is still lacking. Further dedicated research is needed to fill these gaps in evidence and pave the way for the development of applications in clinical care. Chronological aging is associated with higher cancer incidence and cancer-related burden of disability and mortality. Both in Europe and in the USA, all-cancer annual incidence rises from <400 to >2000 per 100,000 persons aged <50 and >70, respectively . The saSince age is a strong risk factor common to cancer and several other chronic diseases ,4, a betInflammation can be defined as an adaptive response triggered by noxious stimuli and conditions. Inflammatory pathways include sensors such as TLR and NLR, mediators such as interleukine (IL)-1β, IL-6 and tumor necrosis factor (TNF), and effectors such as endothelial cells and leukocytes . The besAn increase in serum inflammatory cytokines and in vitro production of these cytokines by peripheral blood mononuclear cells or monocytes with age has been reported ,13, but Of note, this age-related chronic low-grade inflammatory profile—and the chronic diseases it is associated with—is specifically associated with the ‘western’ aging trajectory and is not shared by populations with a very different lifestyle as exemplified by several studies of hunter–gatherers (reviewed in ). Thus, In summary, chronic low-grade inflammation seems to be associated with ‘unsuccessful’ aging , specifically in Western lifestyle contexts, more than with aging itself.Several age-related chronic diseases are associated with chronic low-grade inflammation. In particular, inflammation has been recognized as a hallmark of cancer , due to The initiation stage is probably the most difficult to study, but evidence from animal models suggests that inflammation promotes genomic instability/DNA mutations , parAt the promotion stage, inflammatory cytokines  induce NF-κB and STAT3 transcription factors in cancer cells, which activate genes controlling cell survival, proliferation and growth. Inflammatory cytokines are produced by cancer cells themselves or by immune cells in a paracrine manner . AngAt the dissemination stage, inflammatory cytokines such as TNF, IL-1β and IL-6 increase the invasive capacity of malignant cells through the upregulation of chemokine receptor expression (review in ) and conSince (1) cancer incidence and mortality increase with age, (2) aging is associated with chronic low-grade inflammation and (3) inflammation contributes to several stages of tumorigenesis, it can easily be hypothesized that age-associated chronic low-grade inflammation contributes to the increase in cancer incidence and/or mortality observed during aging ,34; but Several cohort studies and nested case-control studies have found positive associations between serum markers of inflammation and the incidence of various cancers. The results are summarized in The median age in these studies was 45 to 73 years of age. Interestingly, in sub-analyses according to age groups three meta-analyses found significant results only in participants older than 60 ,38,39. TApart from cancer incidence, several cohort studies also found positive associations between serum inflammatory biomarkers and cancer-related mortality see . BiomarkBesides their modest effect size and bias as in the meta-analyses described above, these epidemiological studies have limitations. Firstly, associations do not mean causality, therefore inflammation might not be mechanistically involved in cancer initiation or progression despite these data. Thus, serum mediators of inflammation can be viewed as risk markers to some extent. Secondly, most of these biomarkers reported in cohort studies are routine clinical practice biomarkers that do not provide clues on specific inflammatory pathways that could contribute to cancer. Thirdly, serum mediators of inflammation do not necessarily provide information about inflammation at the (pre) tumoral site. Finally, regarding associations between inflammatory biomarkers and cancer mortality, death, as an event, encompasses cancer incidence and failure of cancer treatment. Thus, these associations could have several explanations. In addition, the above-mentioned studies used data obtained from cohorts of individuals from the general population. To explore links between systemic inflammation and cancer mortality, a complementary approach is to assess the prognostic value of inflammation biomarkers among cancer patients.In these settings, inflammation may originate from the tumor itself or the host. Thus, data cited in this section provide clues about how systemic inflammation contributes to cancer prognosis, but not specifically about how this inflammation contributes to cancer progression. Nevertheless, we discuss these data in the present review because they appear more directly translatable to clinical care.n = 30,000 patients) in 13 different countries and in various tumor sites and treatment types. It was reproducibly found predictive of cancer mortality, independently of disease severity. Associations with other clinical parameters and outcomes provide clues about putative mechanisms linking systemic inflammation and mortality in cancer patients. Indeed, the Glasgow prognostic score has been associated with weight and muscle loss, malnutrition, comorbidity and treatment toxicity, all of which might contribute to prognosis. Then, systemic inflammation may be considered as a marker of vulnerability in cancer patients in several ways: as a marker of reduced physiological reserve , tumor aggressivity and/or treatment efficacy. To explore the malnutrition hypothesis and to improve our understanding of ‘cancer cachexia’ mechanisms, a recent pooled analysis of three cohort studies assessed relations between CRP levels, food intake, cancer-associated weight loss and mortality in 12,253 patients (mean age: 65 y). Higher CRP was associated with weight loss independently of food intake; both higher CRP and reduced food intake independently predicted mortality [The most studied biomarkers are CRP and albumin, combined in a score referred to as the Glasgow prognostic score. As reviewed by McMillan , this scortality . This suCancers, Brattinga et al., report a significantly higher mortality rate three years after surgery in patients (median age 71.5) with pre-operative higher CRP or IL-6 plasma levels. This association was independent of age, disease stage, comorbidities, type of surgery and complications [Given the growing interest in oncogeriatric research, more recent studies specifically focused on the prognosis of inflammatory biomarkers in older patients with cancer. In this special issue of ications .Evidence that drugs with an anti-inflammatory effect are associated with a reduction in cancer incidence or mortality are summarized in Stronger evidence is provided by secondary analyses of randomized controlled trials (RCT) of anti-inflammatory drugs. Most data are from studies of the cardiovascular preventive effect of aspirin. A meta-analysis of two British RCT of aspirin  revealed a reduction in first colorectal cancer incidence only after 10 years of use . AnotherBesides these data focusing on colorectal cancer, two meta-analyses of 8 and 51 RCT, respectively, showed a reduction in total cancer risk in participants taking aspirin ,59. Of pNevertheless, low doses of aspirin (75–100 mg) are not usually considered as anti-inflammatory and the mechanisms of their putative effect on cancer risk reduction are still elusive. Non-inflammatory mechanisms, both COX-dependent and independent, have been hypothesized to explain the anti-cancer properties of aspirin, including effects on apoptosis, DNA-mismatch repair, migration and angiogenesis, possibly involving platelets and microbiota ,62.Recent data suggest that the specific inhibition of IL-1β with a monoclonal antibody could reduce cancer risks. CANTOS was a secondary cardiovascular prevention trial in patients with persistent low-grade inflammation after myocardial infarction . In addiObservational studies and RCT thus suggest that inhibiting inflammation may reduce cancer incidence and mortality, especially in colorectal and lung cancer. Despite these promising data, none of these studies were initially designed to study cancer and few of them concentrated on older patients; the underlying mechanisms of these effects are still poorly understood and these data have not yet been translated into clinical care.Animal models may provide more insight into the mechanisms linking inflammation to tumorigenesis during aging. Biological aging is a highly complex and multifaceted process that remains difficult to study comprehensively. Thus, experimental research is frequently focused on one of its specific aspects, recognized as the hallmarks of aging ,10. In tThe accumulation of DNA damage is frequently suggested as a major cause of increasing cancer incidence with aging. DNA replication errors are thought to be responsible for two-thirds of the mutations in human cancers  and invasion/progression of melanoma tumors were increased in these hosts compared to wildtype fishes. This phenotype was reversed by using anti-inflammatory drugs [Telomere shortening is a specific type of genomic damage observed during normal aging in mice and humans . Telomerry drugs . This suCell senescence is another hallmark of biological aging thought to be a cause of age-related chronic low-grade inflammation. It is described as a stable arrest of the cell cycle coupled to the production of several molecules (including inflammatory cytokines) known as the senescence-associated secretory phenotype (SASP), which facilitates tumor cell growth . Again, Using a murine model of stromal-specific inducible senescence, Ruhland et al., demonstrated that stromal senescence increases the expression of pro-inflammatory cytokines and chemokine genes (notably IL-6) and the presence of myeloid-derived suppressor cells. These cells reduce the proliferation and effector functions of CD8+ T cells and facilitate tumor growth following skin injection of cancer cells in an IL6-dependent manner. Interestingly, the authors also reported the accumulation of senescent cells, IL-6 and myeloid-derived suppressor cells during human skin aging . Thus, iCKIα deficiency triggered a ‘senescence-associated inflammatory response’, leading to growth arrest when the tumor suppressor gene p53 was functional, but to carcinogenesis in the absence of p53 . Experiments in pure epithelial organoid cultures derived from these mice suggested that this phenomenon is cell autonomous without the involvement of microbiota or immune cells. Furthermore, anti-inflammatory drugs decreased tumor burden in double KO mice and reversed proliferation of double KO organoids. This illustrates the principle that carcinogenesis can be induced by low-grade inflammation resulting from tissue stress, in line with the concept of ‘para-inflammation’ [Links between senescence, inflammation and tumorigenesis were further highlighted by Pribluda et al., in a murine model of colorectal cancer. In this work, enterocyte-specific mmation’  (and seemmation’ ). It alsTnf and Il6 via the NF-κB and JAK STAT3 pathways, respectively. Survival of these mice was reduced due to hematological malignancy in an Il6- and Tnf-dependent manner. In addition to a bone marrow inflammatory milieu in miR146a−/− mice, cell-intrinsic signals probably contributed to carcinogenesis, since miR146a−/− HSC were more sensitive to IL-6-mediated rupture of quiescence. This suggests that IL-6 and TNF pathways may contribute to myeloid malignancy during age-associated HSC dysfunction.Stem cell dysfunction is recognized as a hallmark of aging and the aging features of hematopoietic stem cells (HSC) include inflammation and a propensity to myeloid malignancy. Grants et al.  reportedIn the same line, Henry et al.  describeIn this review, we have summarized the epidemiological, therapeutical and experimental evidence that inflammation might contribute to cancer incidence and mortality during aging. Serum levels of inflammatory markers like CRP, IL-6 and TNF are associated with the incidence of several cancers and mortality in cohorts and meta-analyses in the general population, with a modest effect size. Inflammatory markers also have a prognostic value among cancer patients in various settings. Long-term aspirin use is associated with lower cancer incidence and mortality, especially for colorectal cancer and in older people, but the mechanism of this putative effect remains elusive. Lung cancer incidence and mortality might be reduced by IL-1β inhibition, but this is counterbalanced by the incidence of fatal infections and needs confirmation in other studies. Animal models provide clues into how inflammation might link hallmarks of biological aging  to cancer initiation and progression; however, they are not easily translated into understanding the exact role of inflammation in age-associated cancers as hallmarks of aging taken separately do not reproduce the complexity of the human aging process. Altogether, these data support the putative effect of aging-associated inflammation on the development of cancer in old age, but they fail to provide final evidence; they provide neither clear evidence of causality nor clues into the specific inflammatory pathways involved in age-related cancers. Thus, it is too early to state that inflammation contributes to age-related cancers, although it is obvious for physicians that tumors themselves produce inflammation that can be detected in clinical practice.This lack of evidence for the role of inflammation in age-related cancers may be in part related to the vagueness of the concept of age-related inflammation and how it is measured. While inflammation in older persons is usually considered as chronic and low grade, most studies cited in this review relied on single measures of inflammatory markers, therefore the term ‘chronic’ may not be appropriate; furthermore, the term ‘low grade’ has never been precisely defined. Secondly, is age-related inflammation supposed to be local or systemic? Epidemiological studies present only systemic inflammatory markers, while animal model studies have mostly concentrated on local inflammation. The study by Henry et al.  on B celGiven these limitations and the lack of strong evidence, we propose the following perspective , derivedOne could hypothesize that the oxidative stress  and mitochondrial dysfunction observed during aging could be a source of age-related inflammation and could contribute to cancer; indeed, inflammation increases ROS production and ROS are drivers of carcinogenesis, notably through DNA damage ,82. FurtImportantly, inflammation is not the only aspect of the immune system that may link aging to cancer. The role of immunocompetent cells in controlling the development of tumors is now well established; a process referred to as ‘cancer immunosurveillance’ . By virtHow could we better understand the role of inflammation in age-related cancers? Experimental data come from animal models of an accelerated hallmark of aging . They provide insights into the molecular and cellular consequences of the biological changes that occur during aging, but do not recapitulate the biological complexity of ‘natural’ aging. As demonstrated by Golomb and al., , it is f


There are many reports of non-occlusive mesenteric ischemia in patients on maintenance hemodialysis and following cardiac surgery. However, there are few reports of non-occlusive mesenteric ischemia in patients with acute stroke.We report three cases of non-occlusive mesenteric ischemia with onset during treatment for acute stroke. All of the patients were undergoing strict blood-pressure control, and two patients developed NOMI soon after tracheostomy when enteral nutrition had been resumed.Many stroke patients are older adults with risk factors such as arteriosclerosis. Thus, during acute stroke management, there is a possibility that patients may develop non-occlusive mesenteric ischemia due to decreased intestinal blood flow secondary to strict blood-pressure control. This case report implicates early enteral nutrition as a potential etiopathogenic factor of non-occlusive mesenteric ischemia in patients with acute stroke. Non-occlusive mesenteric ischemia (NOMI) is an acute mesenteric circulatory disorder that occurs without organic vascular occlusion and is associated with extremely high mortality . PotentiAmong the 296 stroke patients  treated in the intensive care unit (ICU) of our hospital from May 2018 to January 2021, based on contrast-enhanced computed tomography (CECT) scans of the abdomen, we identified three patients with acute stroke and NOMI.A 60-year-old woman underwent coil embolization for subarachnoid hemorrhage due to a basilar artery aneurysm rupture, but developed abdominal distension, vomiting, and metabolic acidosis on the sixth postoperative day. Abdominal CECT showed widespread contrast defects in the small intestine along with portal and intestinal emphysema, which indicated NOMI. Emergency laparotomy was performed on the same day and revealed small intestinal and ascending colon necrosis with skip lesions Fig. . IndocyaA 78-year-old woman underwent a craniotomy for subcortical hemorrhage in the right parietal lobe. A tracheostomy was performed on postoperative day 6, and enteral nutrition was started on the same day. To evaluate abdominal distension, a CECT was performed on postoperative day 8 and showed poor contrast uptake in the small intestine and portal emphysema. Thus, NOMI was suspected and, on the same day, emergency laparotomy revealed small bowel and ascending colon necrosis with skip lesions. ICG fluorography to evaluate intestinal blood flow revealed the ischemic bowel segments as regions of poor fluorescence emission. The necrotic bowel was resected. Bowel anastomosis was not performed, and a stoma was created. Histopathological findings supported a diagnosis of NOMI, and the patient was discharged on day 35 of hospitalization.An 82-year-old woman underwent coil embolization for subarachnoid hemorrhage due to internal carotid artery–posterior communicating artery aneurysmal rupture. Enteral nutrition was started on postoperative day 2, and a tracheostomy was performed on postoperative day 7; enteral nutrition was restarted on the same day. CECT for abdominal distension on postoperative day 9 revealed extensive areas with poor contrast uptake in the small intestine and portal emphysema, which indicated NOMI, and an emergency laparotomy that was performed on the same day showed extensive small bowel and colon necrosis with skip lesions. The necrotic bowel was resected, but bowel anastomosis was not performed, and a stoma was created. However, histopathology showed no specific findings, and the patient died of cerebral herniation 16 days after hospitalization. The results are summarized in Table NOMI causes segmental, discontinuous intestinal vascular obstruction without organic occlusion of the mesenteric vascular trunk . NOMI geThe American Society for Parenteral and Enteral Nutrition and Society of Critical Care Medicine 2009 recommendations for early initiation of enteral nutrition  have proHowever, NOMI is a disadvantage of early enteral nutrition. Although early enteral nutrition is cautiously administered in patients with known risk factors, enteral nutrition is aggressively used in stroke patients. Given the increasing frequency of NOMI in stroke patients , we evaluated whether, due to several factors, stroke patients might be at higher risk for NOMI.One of the pathogenetic mechanisms of NOMI is a mismatch in the oxygen demand-and-supply ratio in the intestine, particularly in the vulnerable superficial mucosa, that is induced by early enteral nutrition , 9. ThusWe consider it is preferable to start enteral nutrition after tracheostomy with a small amount or the day after tracheostomy. Of course, pathological condition leading to tracheostomy has greater effect on intestinal peristalsis. Although tracheostomy does not directly affect intestinal movement, we think it does have an indirect effect on decreased intestinal movement. Under such circumstances, early enteral nutrition may be a risk factor for NOMI.In addition, nicardipine, which is used for strict blood-pressure control, has an inhibitory effect on the gastrointestinal smooth muscle and may cause paralytic ileus (which is a well-known side effect that tends to be ignored). Moreover, administering early enteral nutrition in ileus may lead to bacterial overgrowth and progressive edema, thereby impairing intestinal mucosal blood supply and causing ischemic injury .Many stroke patients have high vascular risks, and optimal intestinal blood flow may not be maintained during strict blood-pressure control. All of the above-mentioned cases occurred under strict blood-pressure control, and two patients developed NOMI early after tracheostomy following resumption of enteral nutrition.For the above-mentioned reasons, patients with acute stroke should be considered to be at a high risk for NOMI.Early enteral nutrition, in addition to its manifold benefits, poses a risk of NOMI.The stroke patients under strict blood-pressure control may be at increased risk for NOMI, and we should especially be aware when initiating enteral nutrition.


Systemic treatments, such as chemotherapies, as well as targeted treatments, whose efficacy cannot be fully predicted yet by other diagnostic tests, may be assessed through these means. The results can provide helpful information to assist clinicians in their decision-making process. We explore here the most advanced functional assays across oncology indications, with an emphasis on tests already displaying a convincing clinical demonstration. We then recapitulate the main technical obstacles faced by researchers and clinicians to produce more accurate, and thus more predictive, models and the recent advances that have been developed to circumvent them. Finally, we summarize the regulatory and quality frameworks surrounding functional assays to ensure their safe and performant clinical implementation. Functional assays are valuable in vitro diagnostic tools that already stand beyond the “proof-of-concept” stage. Clinical studies show they have a major role to play by themselves but also in conjunction with molecular diagnostics. They now need a final lift to fully integrate the common armament used against cancers, and thus make their way into the clinical routine.As complex and heterogeneous diseases, cancers require a more tailored therapeutic management than most pathologies. Recent advances in anticancer drug development, including the immuno-oncology revolution, have been too often plagued by unsatisfying patient response rates and survivals. In reaction to this, cancer care has fully transitioned to the “personalized medicine” concept. Numerous tools are now available tools to better adapt treatments to the profile of each patient. They encompass a large array of diagnostic assays, based on biomarkers relevant to targetable molecular pathways. As a subfamily of such so-called companion diagnostics, chemosensitivity and resistance assays represent an attractive, yet insufficiently understood, approach to individualize treatments. They rely on the assessment of a composite biomarker, the  It is widely accepted that, for diseases with complex and heterogeneous molecular backgrounds such as cancers, “one-size-fits-all” treatment strategies are no longer desirable. This is best illustrated by the unsatisfying response and survival rates observed on unselected patient cohorts for most classes of drugs. To propose and sort patients according to their predicted response to a cure, personalized medicine - or, more accurately, subpopulation medicine - requires reliable tests to stratify and ultimately retain relevant groups of responsive patients. Such tests measure specific response biomarkers in adequate samples. They are formally gathered under the companion diagnostics (CDx) designation in vitro device, which provides information that is essential for the safe and effective use of a corresponding drug or biological product [and which] can identify patients who are most likely to benefit from a particular therapeutic product” True CDx are currently defined by the US Food and Drug Administration (FDA) as “a medical device, often an The history, current role and perspectives of common CDx and CoDx have been extensively reviewed in vitro assays, led on selected models to study the response to a drug candidate, to clinically-applicable ex vivo assays: indeed, they test on a patient's own cells, upstream of treatment initiation, the arsenal of therapies available for a specific indication. Instead of identifying the roots of a diseased phenotype, they capture the final, and as such clinically relevant, response to a drug produced by the interplay between all biological variables. This outcome acts as a composite, surrogate biomarker for drugs with no known indicator of susceptibility or resistance. Functional assays may hence provide a personalized medicine approach for systemic treatments, including chemotherapies, which have not been clinically associated with single or groups of biomarkers yet.The definitions for CDx and CoDx are broad and understood as associating the presence of a specific biomarker  in a patient's body with a specific drug. This refers to the diseased tissue's history ex vivo modelling of a patient's tumour from pathologically-qualified samples obtained during a medical procedure , which may mirror that of the original cancer lesions. This profile is ultimately integrated into the clinical decision-making process to individualize the treatment(s) a cancer patient will receive.Predictive functional assays, especially chemosensitivity and resistance assays (CSRA), have been pursued for several decades e Figure : diagnosThe use of CRSA to select chemotherapeutic agents for individual patients is not recommended outside of the clinical trial setting. Oncologists should make chemotherapy treatment recommendations on the basis of published reports of clinical trials and a patient's health status and treatment preferences. Because the in vitro analytic strategy has potential importance, participation in clinical trials evaluating these technologies remains a priority”. This statement enough shows the great potential the ASCO sees in CSRA, albeit they have not fulfilled clinicians' expectations yet.Despite long-standing efforts, an efficient protocol still has to obtain recognition by the biomedical community In this review, we present the most advanced functional assays for treatment individualization in oncology. We then show through a meta-analysis of technical and clinical performances gathered so far that the notion of CSRA is already way beyond “proof-of-concept”. Challenges faced by functional assays, especially in their development along with the expansion of the anticancer drug modes of action (MoA), are presented. Finally, we discuss quality management of the environment of functional assays, as well as regulatory considerations framing their approval, for they provide both hurdles and handrails for the successful implementation of these assays within the clinical routine.ex vivo the action of a drug or a combination of drugs on a patient's tumour. Cell culture methods and readouts varied throughout the years, and techniques improved to reach high accuracy levels. In their vast majority, these functional assays follow common steps: (i) dissociation of a tumour specimen and isolation of tumour cells, (ii) primary cell culture in presence of chemotherapies, (iii) assay cell viability/mortality, and (iv) data analysis to produce a chemosensitivity profile , and the Extreme Drug Resistance Assay (EDR), also known as the Kern assay. The DiSC assay is based on the counting of global cell death among the tumour cell population following drug treatment. Cell death observation relies on the loss of cell membrane integrity, which is observed by dye exclusion using Fast Green. Viable cells are then counterstained with hematoxylin/eosin, then cell mortality is evaluated using a light microscope Numerous studies investigated the relevance of applying cell metabolism measurement techniques to primary tumour chemosensitivity. The first example is the ATP-Chemotherapy Response Assay (ATP-CRA). This technique relies on total ATP dosage by bioluminescence in vivo situation In vitro drug sensitivity is then determined by implementing a growth inhibition rate threshold, which is mostly above 50%.Another cell metabolism assay designed for chemosensitivity assessment purpose is MTT. This technique has been extensively used for the development of the Histoculture Drug Response Assay (HDRA). Unlike ATP-CRA, HDRA is based on the culture of small pieces of the tumour (1-2 mm) on collagen-coated matrices i.e. fluorescent microscopy pictures, before and after drug treatment Although less developed, several other academic initiatives are worth mentioning, notably Fluorescent Cytoprint (FCA) and Sulforhodamine B (SRB) assays. FCA measures the activity of cytosolic esterases, which convert non-fluorescent fluorescein monoacetate into fluorescein. Small tumour fragments, named micro-organs, are cultured on collagen-coated metal grids. Drug-induced cytotoxicity is measured by comparing cytoprints, via apoptosis 600 following drug treatment The MicroCulture-Kinetic assay (MiCK) is a drug-induced apoptosis assay. The history of this assay relies on the observation that most chemotherapies induce cell death ® assay has been recently commercialized by US-based company Cordgenics. It is atypical since it aims at providing separate bulk tumour cell and cancer stem-like cell (CSC) responses to chemotherapies. Procedures include the following steps: tumour dissociation, CSC enrichment in a bioreactor, cell sorting by flow cytometry, chemotherapy treatment, and finally a WST-8 cell proliferation assay The ChemoID® assay has been developed by the US company Helomics and is dedicated to gynaecological cancers 3 tumour fragments until confluency, then trypsinization and subculture into 384-well plates with drugs. Serial dilutions are tested and, following a 72-h treatment, cells are stained with DAPI then counted by fluorescent microscopy. Tumour response is evaluated by measuring the area under the curve.The ChemoFX® technology has been developed by Indian company Mitra Biotech. This technique recreates the native tumour environment by culturing thin tumour explants into a 3D matrix, in presence of autologous serum The CANscript® has been developed by the French company Oncomedics to which belong/belonged some of the authors of this review. It consists in the measurement of drug-induced cellular mortality using fluorescence microscopy. Its main advantage lies in the use of a fully standardized, serum-free cell culture medium, allowing both optimal reliability and high culture success rates ® was designed to measure the effect of drug combinations routinely used in cancer patient care, such as FOLFOX or FOLFIRI. The Oncogramme® was originally developed against metastatic colon cancer , and its use in breast and ovary cancers is currently under investigation . The Oncogramme® is, to our knowledge, the only CE-marked functional assay, allowing its distribution within the European Union. A randomized, assay-directed phase 3 clinical trial is currently ongoing to evaluate its capacity to improve 1-year progression free survival (PFS) of metastatic colon cancer patients .The OncogrammeApart from these academic initiatives, several proprietary assays were also developed by biotechnology companies. Below are detailed five of the most advanced techniques:Numerous proof-of-concept studies have been performed on a wide panel of malignant pathologies using methods described above. Table A total of 42 studies have been included, from 1991 to 2019. Clinical studies older than 1990 and/or related to clonogenic assays were deliberately omitted.®, without affecting success rate First interesting observation is the high primary culture success rate obtained in most studies. It ranges from 43.8% to 98.8%, with a mean of 86.6%. Of note, the lower limit of this range, obtained on lung cancer In the context of CSRA, sensitivity represents a key parameter to study, since it measures the proportion of responders properly identified as such by the assay i.e. the proportion of non-responders among the population found as such by the assay. In studies listed in Table Opposite to sensitivity, specificity represents the percentage of true negative, i.e. which already underwent chemotherapeutic treatments, or from diverse histologic grades. Because of this lack of consistency, one can hardly determine whether one chemosensitivity assay gives better results than another. To our knowledge, only few comparative studies were performed on the same tumour material. In ovarian cancer, it has been shown that DiSC, ATP tumour chemosensitivity and MTT assays correlate well Taken together, these results demonstrate the accuracy of chemosensitivity assays, with an ability to predict positive outcomes of around 90%. Despite being high, prediction of non-responders is still perfectible in most cases, as specificity is almost systematically lower than sensitivity. However, results must be taken with care, since many of the abovementioned studies were conducted using heterogenous samples, vs. 16 months, p = 0.025) To ensure the reliability of CSRA, technical performances must be linked to clinical benefits. Among 27 clinical studies listed in our meta-analysis Table , only twvs. 7.4 months, p = 0.041) ®, NCT03133273), glioblastoma  and ovarian cancer .So far, seven studies were conducted in a prospective manner, with treatments being guided by CSRA results. Again, patients who benefited from CSRA showed better clinical outcomes. OS was statistically improved in one study  models Another bias that hampers representativeness of ex vivo/in vivo comparison to study the predictive capacities of the model, a few examples of which follow. First, short-term culture of tumour fragments on poly-2-hydroxyethylmetacrylate (PolyHEMA) was used to investigate the chemosensitivity of various patient samples, including liver metastases, to irinotecan active metabolite SN-38 TUMOROID clinical trial studied the capacity of a CRC patient-derived tumour organoid-based assay to identify non responders to first- and second-line chemotherapy in vivo drug bioavailability influenced by, among other factors, administration route, plasma clearance, extracellular matrix and cancer-associated fibroblasts (CAF). A thorough reconstitution of TME is illustrated by the CANscriptTM platform, which uses explants cultivated within a tumour grade-matched protein matrix supplemented with autologous patient serum Tumour heterogeneity is also reflected in tumour microenvironment (TME). Two-dimension (2D) models obtained from dissociation of tumour tissue have been favoured so far. Obviously, such models are not comprehensively representative of tumour contexture, lacking key elements from the TME that cannot be fully compensated for with specifically formulated culture media. 3D models receive more and more attention to study the impact of drugs on tumour growth, neo-angiogenesis, or interaction between immune cells and tumours in vivo-like microenvironment. Label-free, non-destructive biophysical treatment sensitivity biomarkers are also investigated, hence mass accumulation rates determined at the single-cell level Desirable characteristics to improve models include miniaturization, tight control of culture conditions over time, throughput enhancement, and study of orthogonal functional response parameters ex vivo models we previously emphasized, making it challenging to reproduce pharmacokinetics of drug exposure in vitro. Depending on the drug's MoA, it may rather be required to finely tune its conditions to fully study its effects, then predict a clinical response. This could be done by controlling total duration of assay and specific duration of drug exposure, as well as measuring cell response at different time points and concentrations, in presence of the drug or after a recovery time. Microfluidics-based technologies, previously cited, may bring the required plasticity.Besides accurate tumour modelling, to be predictive an assay should measure: (i) how efficiently a drug induces cancer cell killing, as it is the foundation of tumour shrinkage; and (ii) which cancer cells are killed among a heterogeneous subpopulation; as previously stated, the latter is particularly important to predict recurrence. Chemoradiation therapy induces cell death through a large variety of mechanisms e.g. tumour mutation burden (TMB), PD-1/PDL-1, and tumour-infiltrating lymphocytes (TIL). Percentages of response are variable and, to some extent, fail to be accurately predicted by biomarkers ex vivo model is challenging; adding another level of complexity, that is to say coculturing cancer cells with autologous immune cells and measuring a response, is even more challenging. Yet, several functional assays are being developed in vitro activity of most immunotherapy drug classes and immune effector cells TM platform ex vivo sensitivity assays aiming at predicting tumour response to ICI targeting this pair, as well as, more generally, any other non-static target with a fluctuating and microenvironment-dependant presence.The essential and ambiguous role of immune contexture in modulating both clonal evolution patterns of cancer through immunoedition ex vivo models, especially because they would require a longer time to allow tumour model vascularization. Preclinical models exist but are not easily amenable to the clinic in vivo-model is easier, time- and cost-competitive to generate as compared to mouse models. The whole process allows obtaining usable tumours within 10-13 days of grafting; it thus appears suitable for clinical applications. CAM has hence been used for testing chemosensitivity or chemotoxicity Another category of anticancer drugs, anti-angiogenics, are challenging to test using conventional 2D/3D in vitro from cell extracts and represent a promising tool to predict response to drugs targeting DNA damage response pathways In vitro detection of DNA damage may be approached through analytical chemistry, molecular or immunological methodologies ex vivo results obtained on more easily accessible PBL rather than directly on tumour cells, suggesting a surrogate target for measuring specific anticancer activity. The Comet assay has also proven useful to measure alkylation and addition products generated by chemotherapies, suggesting a transferability to CSRA DNA repair capacities of cancer cells can be studied  in vivo models appear scientifically sound to preserve the tumour's characteristics, recreate its environment and study the response of a whole sample instead of individualized cells or clonal groups For drug discovery purposes, PDX-basedin vitro assessment of a drug's MoA, functional assays allow preparing in vivo and first-in human studies by identifying and/or confirming disease subtypes most susceptible to respond to the drug candidate. This additional data investigating the biological hypothesis of a drug might reinforce the Investigational New Drug (IND) dossier. Additionally, it is worth noting that functional assays have another role to play in drug clinical development. Since they rely on a specific type of biomarker, functional assays may also help shaping clinical trials, much like CDx are doing with umbrella and basket trials Because of their demonstrated predictive capacities on patient-derives models, functional assays are interesting tools for drug preclinical validation. Some contract research organisations (CRO) rely on such business model. Following Two-dimension models currently offer the easiest path to clinical implementation of CSRA. This is due to both their adaptability to various clinical laboratory settings, and shorter turnaround time. However, the diversity of approaches overviewed here offers much promise to generate more complex and more predictive models. Continued integration of live cell culture technologies within clinical laboratories should facilitate their routine use. Moreover, technological advances, especially in image analysis and high content screening CDx and CoDx may directly influence a patient's course of treatment. Consequently, they fall under strict regulation, and their manufacturing and execution require a stringent quality management framework. In our introduction, we pointed out CDx and CoDx have received, respectively, official and unofficial definitions. Functional assays, because of their nature, definitely are CoDx: they recommend specific treatment among the available list against a given indication; the medical team ultimately decide the best strategy to apply, based on this information but also on pathology's characteristics and overall patient's status. In addition, functional assays predict treatment response concomitantly for several drug classes, contrary to conventional CDx or CoDx; they may thus require a specific definition. In any case, the regulatory framework applicable to CDx also applies to functional assays.making medical treatment decision” basic information” about their product.Regulations in Europe and USA differ in the way they consider CDx as a whole, and functional assays dedicated to treatment individualization in particular. In the US, CDx fall within “class III” products, presenting a potential, unreasonable risk of illness or injury. As such, they require clinical investigation under an Investigational Device Exemption (IDE) before premarket approval (PMA). PMA is issued by the FDA's Center for Devices and Radiobiological Health (CDRH). Approval from the FDA allows commercialisation of CDx, which must be performed in an environment certified under the Clinical Laboratory Improvement Amendments (CLIA). Historically, some functional assays have started as laboratory developed tests (LDT) in clinical institutions Marketing of MD in the European Union is conditioned to CE marking. In that respect, IVD-MD used to fall under the 98/79 EC directive. It allowed manufacturers to self-certify their diagnostics products for CE marking. Also, CDx were considered as “low-risk devices”, which, given their destination, was not appropriate e.g. minimal quantity of material to assess for producing a reliable result). In most advanced functional assays, patient's clinical response acts as the gold standard for benchmarking the patient's cell in vitro response. Hence, most of the aforementioned parameters must be derived from studies directly involving patients. There is no common rule regarding reproducibility of biomarker assays as a whole; however, coefficients of variation inferior to 15 % were cited as an aim to achieve in vitro models such as cells lines ®, with improved accuracy and precision Inherent to CDx and CoDx is the dependency of risks and benefits of the selected treatment(s) upon the intrinsic performances of the assays. Rigorous demonstration of the assay robustness, reproducibility and clinical benefit must be conducted to achieve sufficient reliability. The three pillars of assay validation are: analytical validation, clinical validation and clinical utility Sample collection, processing and logistics are key steps in the functional assay flowchart, since such tests necessarily deal with live cells or cell extracts identify, measure, or predict the presence or absence of a medical condition or predisposition” for which the device is intended Following proper design controls and performance measurements, clinical validity of the IVD-MD is assessed. It aims at demonstrating its ability to “As previously discussed, the proliferation of experimental or clinically implemented chemosensitivity assays directed against a large array of indications has been accompanied with the development of greatly varying protocols. Although understandable from a technological differentiation standpoint, the major pitfall of such situation is already illustrated by anti-PD-1/PD-L1 antibodies: each marketed antibody has its own CDx, with clinical trials constructed in such a way that they lead to drug-specific cut-offs to declare efficacy As stated in a founding review ex vivo response into clinical response The main criticism raised against CSRA is the lack of translatability of The intense development of targeted therapies might have caused some to forget that chemotherapies still stand as standards-of-care against cancer. Obviously, their response rates remain insufficient. Use of these “historical” anticancer treatments would benefit from personalized approaches, too, which has been the foundation of CSRA. Failure of chemoresistance prediction now allows efforts to concentrate of chemosensitivity prediction, which clearly holds a much higher clinical utility While this may remain a pious wish because of industrial reasons, the recent experience gained from the development of “me-too” drugs and CDx in immuno-oncology, with thresholds that are not comparable from one assay to the other while they are supposed to measure the same endpoint, leads us to suggest the creation of working groups and workshops dedicated to functional assays. They would gather the main actors in the field to discuss technical  and regulatory considerations to help structuring assays.Personalized medicine offers the perspective of tailoring therapeutic approaches for every patient. Yet, not every patient harbours an already known actionable drug target. Blending biological knowledge with technological development to better grasp the behaviour of every patient's cancer should ensure that none is left in the ditch along the road.Pr. M. Mathonnet, Dr. C. Bounaix Morand du Puch, Dr. N. Christou, Dr. S. Giraud and Dr. C. Lautrette conceived the original idea. Dr. C. Bounaix Morand du Puch and Dr. M. Vanderstraete drafted the manuscript with equal contributions. Pr. M. Mathonnet revised the manuscript.