Related Technologies Research Articles

Devising an economic-legal approach to the viability of innovative technology transfer in the process of its commercialization

The object of this study is to determine the economic effect of technology transfer during the period of its viability. This paper suggests a methodology that takes into account the appropriate amount of profit and the accumulated amount of royalties in the commercial use of innovative technology. The necessity of taking into account the viability of the transfer of innovative technology as the beginning of its new life cycle was substantiated. The possibility of formalizing this process in the form of an assessment of the sum of the present values of all projected cash flows, taking into account the eligibility criterion and the barrier rate, has been established. We propose an approach, which, unlike the existing ones, consists in allocating a certain period of viability of innovative technology transfer in the life cycle of technology. It is argued that based on the results of technology renovation, it is possible to assess the economic effect of its transfer due to the benefits of implementation and achievement of licensing activity by expanding the number of licensees. We substantiate the possibility of generating profits and royalties to the licensor as the amount of investment that can and should be directed to the development of a fundamentally new or improved technology in relation to the previous one. The transition to a new technology causes an increase in the overall technological level and leads to the formation of a technological gap between the S-shaped life curves of technical systems and, in parallel, forms a new S-shaped curve of a new technological system based on new knowledge. An economic and legal approach to the development of a methodology for determining the economic effect or viability of innovative-level TT was implemented. The results of the current study could be used in the formation of legislative and subordinate national regulations, as well as serve as a basis for further research on this issue

Synergizing edge computing and blockchain for cyber‐physical systems

SummaryAs a foundational technology for managing decentralized systems like smart grids and healthcare systems, blockchain is attracting a lot of interest. However, owing to excessive resource requirements and low scalability with frequent‐intensive transactions, its use in resource‐constrained mobile devices is restricted. To let mobile devices offload processing tasks to cloud resources, edge computing can be used. For scalability and secure transactions, the integration with edge computing guarantees consistent access, distributed computing, and non‐compromised storage. To accomplish effective integration, critical challenges such as reliability, adaptability, and resource planning must be resolved. Despite these efforts, further study is still needed to address issues with confidentiality, flexibility, and reliability to develop a workable, secure decentralized data storage system. This study utilizes edge computing to build an Internet of Things (IoT) architecture that satisfies the safety and scalability necessary criteria for integration along with the integration of peer‐to‐peer and blockchain technologies. Already‐existing blockchain and related technologies have also been investigated to suggest solutions that address issues like secrecy, reliability, and scalability in order to successfully incorporate blockchain in IoT systems. Our experimental findings indicate that achieving low rates of stale blocks and promoting decentralization requires a meticulous selection of block sizes and generation intervals. It is essential to maintain block creation intervals as short as practically possible, and utilizing blocks with a size below 1 MB is advisable.

Orosomucoid 2 as a biomarker of carotid artery atherosclerosis plaque vulnerability through its generation of reactive oxygen species and lipid accumulation in vascular smooth muscle cells

BackgroundOrosomucoid (ORM) has been reported as a biomarker of carotid atherosclerosis, but the role of ORM 2, a subtype of ORM, in carotid atherosclerotic plaque formation and the underlying mechanism have not been established. MethodsPlasma was collected from patients with carotid artery stenosis (CAS) and healthy participants and assessed using mass spectrometry coupled with isobaric tags for relative and absolute quantification (iTRAQ) technology to identify differentially expressed proteins. The key proteins and related pathways were identified via western blotting, immunohistochemistry, and polymerase chain reaction of carotid artery plaque tissues and in vitro experiments involving vascular smooth muscle cells (VSMCs). ResultsWe screened 33 differentially expressed proteins out of 535 proteins in the plasma. Seventeen proteins showed increased expressions in the CAS groups relative to the healthy groups, while 16 proteins showed decreased expressions during iTRAQ and bioinformatic analysis. The reactive oxygen species metabolic process was the most common enrichment pathway identified by Gene Ontology analysis, while ORM2, PRDX2, GPX3, HP, HBB, ANXA5, PFN1, CFL1, and S100A11 were key proteins identified by STRING and MCODE analysis. ORM2 showed increased expression in patients with CAS plaques, and ORM2 was accumulated in smooth muscle cells. Oleic acid increased the lipid accumulation and ORM2 and PRDX6 expressions in the VSMCs. The recombinant-ORM2 also increased the lipid accumulation and reactive oxygen species (ROS) in the VSMCs. The expressions of ORM2 and PRDX-6 were correlated, and MJ33 (an inhibitor of PRDX6-PLA2) decreased ROS production and lipid accumulation in VSMCs. ConclusionORM2 may be a biomarker for CAS; it induced lipid accumulation and ROS production in VSMCs during atherosclerosis plaque formation. However, the relationships between ORM2 and PRDX-6 underlying lipid accumulation-induced plaque vulnerability require further research.

Identification of Endothelial Cell Protein C Receptor by Urinary Proteomics as Novel Prognostic Marker in Non-Recovery Kidney Injury.

Acute kidney injury is a common and complex complication that has high morality and the risk for chronic kidney disease among survivors. The accuracy of current AKI biomarkers can be affected by water retention and diuretics. Therefore, we aimed to identify a urinary non-recovery marker of acute kidney injury in patients with acute decompensated heart failure. We used the isobaric tag for relative and absolute quantification technology to find a relevant marker protein that could divide patients into control, acute kidney injury with recovery, and acute kidney injury without recovery groups. An enzyme-linked immunosorbent assay of the endothelial cell protein C receptor (EPCR) was used to verify the results. We found that the EPCR was a usable marker for non-recovery renal failure in our setting with the area under the receiver operating characteristics 0.776 ± 0.065; 95%CI: 0.648-0.905, (p < 0.001). Further validation is needed to explore this possibility in different situations.

A roadmap to achieving a healthier information ecosystem through GDPR implementation and privacy compliance technologies

AbstractPrivacy protection has become a central issue in information science, with the General Data Protection Regulation (GDPR) significantly impacting information ecosystems. Research gaps persist in understanding the causal relationship between GDPR implementation and websites' proactive changes, such as adopting privacy compliance technologies. This study aims to examine the influence of GDPR implementation on websites' information ecosystems and identify boundary conditions that may affect this relationship. Utilizing domain‐level data from a professional platform tracking website technologies before and after GDPR implementation, which encompasses a comprehensive longitudinal dataset of over 1.2 million websites, our results indicate that GDPR implementation has increased the decision, breadth, depth, and intensity of adopting related technologies. The variance in these adoptions is significantly shaped by the differing levels of institutional impacts experienced by trailblazing versus laggard industries. Our study contributes to the literature by revealing the importance of policy factors in fostering a healthier information ecosystem. We demonstrate the complex nature of the relationship between policy factors and technology adoption, highlighting the need for researchers to consider institutional context and industry‐specific characteristics. We further discuss valuable insights for relevant stakeholders.

Diffusion of BIM policies in China: an event history analysis

PurposeDespite the critical role of the policy environment in facilitating the advancement of building information modeling (BIM) as a systemic innovation to reshape traditional facility design, construction and operation processes, scant scholarly attention has been paid to systematically investigating how and why complex BIM policies are concretely and gradually implemented in different regional contexts from a dynamic policy diffusion perspective. This study aims to empirically investigate how different types of BIM policy instruments are dynamically implemented in heterogeneous regions over time and how the diffusion of BIM policies across different regions is comprehensively impacted by both internal efficiency needs and external legitimacy pressures.Design/methodology/approachThis study employed a positivist research paradigm in which BIM policy data from 182 prefecture-level and above cities in China during 2011–2022 were analyzed with quantitative approaches for theory verification. Based on the content analysis of the evolutionary characteristics of the adopted BIM policy instruments in heterogeneous regions over time, the event history analysis (EHA) method was then used to further examine the mechanisms underlying the diffusion of BIM policies across different regions.FindingsThe content analysis results show that while environmental instruments (such as technological integration and goal planning) are the primary policy instruments currently adopted in China, recent years have also witnessed increasing adoptions of supply-side instruments (such as fiscal support and information support) and demand-side instruments (such as demonstration projects and tax incentives). After controlling for the impacts of regional fiscal and technical resources, the EHA results illustrate that BIM policy adoption positively relates to regional construction industry scale but negatively relates to regional industry productivity and that compared with public pressures from industry participants, vertical pressures from the central government and horizontal pressures from neighboring regions are more substantial drivers for policy adoption.Originality/valueAs an exploratory effort of using a dynamic policy diffusion perspective to systematically investigate how BIM policies are adopted in heterogeneous regional contexts to facilitate BIM advancement, this study not only characterizes the complexity and dynamics of BIM policies but also provides deepened understandings of the mechanisms underlying policy adoption in the conservative construction industry. The findings hold implications for how multifarious policy instruments can be more effectively and dynamically adopted to facilitate the advancement of BIM and related technologies as innovative solutions in the construction domain.

Exploring Impact of the Ultrasound and Combined Treatments on Food Quality: A Comprehensive Review

As a response to the evolving consumer demand for healthier food choices, ultrasound application in food processing emerges as a sustainable and green solution with no residual effects. This method, known for its cost-efficiency and sustainability, holds significant promise in meeting the increasing need for high-quality, chemical-free, and natural-tasting convenience foods in the ever-changing landscape of the food industry. Ultrasound, leveraging mechanical sound waves, spans across various frequencies: power ultrasound (20–100 kHz), high-frequency ultrasound (100 kHz-1 MHz), and diagnostic ultrasound (1–500 MHz). This study focuses on investigating the impact of ultrasound and combined treatments on food quality, summarizing their diverse applications across different unit operations such as texture and rheology, emulsification and homogenization, crystal formation and modification, dehydration and drying, fermentation, filtration, preservation and shelf-life extension, flavor enhancement, color and appearance, antioxidant activity, enzyme activity and food digestibility, bioavailability and bio-accessibility, and specific food divisions including unprocessed, minimally processed, processed, and ultra-processed foods, as well as culinary ingredients. It delves into their effects on technological and functional aspects of food products, explores emerging trends, offers possible recommendations in ultrasound technology for the food industry, while also recognizing existing challenges and limitations associated with ultrasound and related technologies.

Mapping the development of hydrogen-based technologies (HBTs) through patent analysis

PurposeThis paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the study provides a novel perspective on the development of HBTs and offers implications for managers and policymakers.Design/methodology/approachWe collected patent data at the level of patent families (PFs). Our sample includes 317,089 PFs related to hydrogen production and 62,496 PFs to hydrogen storage. We examined PF data to delineate the state of the art and major technical advancements of HBTs.FindingsOur analysis provides evidence of an increasing patenting activity in the area of HBTs, hence suggesting relatively high levels of expectations on the economic potential of these technologies. US and Japan hold the largest proportion of PFs related to HBTs (about 60%), while European applicants hold the highest proportion of highly cited PFs (about 60%). While firms represent the applicant with the highest share of PFs, our analysis reveals that firms holding HBT PFs are primarily from the chemical sector.Research limitations/implicationsWhile our analysis is limited to examining patent data which capture some aspects of the innovation activity around HBTs (namelly, patented inventions), our study enriches existing literature by performinng a patent analysis on a much larger sample of data when compared to previous studies.Practical implicationsTwo main implications emerge from our study. Firstly, there seems to be an urgent need to support the emergence of a dominant design so as to facilitate the consolidation and diffusion of the HBTs, hence the transition to a more sustainable energy production. Secondly, the majority of HBT PFs are held by a small number of countries. This, in turn, suggests opportunities to develop cross-country cooperation (e.g. international agreements, research and technology offices) to support the development and adoption of HBTs globally.Social implicationsConsidering the results obtained in this study, from a social point of view, the attention that organizations have paid to hydrogen related technologies is evident. This suggests that the development HBTs can function as a social enabler for a sustianable energy transition.Originality/valueExtant research has focused on the individual components of the hydrogen chain. As a result, we lack a comprehensive understanding of the progress made in the area of HBTs. To address this gap, this study examined HBTs by focusing on both production and storage technologies since their initial developments, hence adopting an observation period of about 70 years.

Antibody druggability screening process and evaluation strategy

Since the approval of OKT3 as the first therapeutic monoclonal antibody in 1986, there has been rapid development in antibody technology and antibody drugs. Monoclonal antibodies, antibody fragments, bi (multi) specific antibodies, fusion proteins, nanobodies, and antibody-drug conjugates (ADCs) have been introduced and play a significant role in the treatment of oncology, hematology, immunology, respiratory, metabolic and other related diseases. The process of antibody drug discovery involves multiple rounds of biological function and druggability assessments to identify the best candidate sequences that are safe, effective, stable, and scalable. This lays the foundation for the efficiency and success of drug development and clinical studies. In the phase of antibody drug discovery, "druggability screening and evaluation" has received increasing attention. It involves drug discovery and design, screening and optimization of lead molecules as well as the validation of candidate molecules, with the aim of detecting potential physicochemical risk factors and evaluating controllability to ensure the quality stability of the subsequent drug development process. This paper classifies and defines the process of druggability screening and evaluation in the antibody discovery phase, covering monoclonal antibodies, bispecific antibodies, nanobodies, ADCs and other related technologies and drug forms. It also summarizes the quality attributes and high-throughput detection technology that should be emphasized in the druggability screening and evaluation. The systematic elaboration of the druggability development process and strategy provides a reference for the druggability screening and evaluation of emerging innovative drugs, significantly improving the efficiency and success rate of antibody drug development.

Assessing the Digital Transformation Readiness of the Construction Industry Utilizing the Delphi Method

The rapid advancement of digital technology has enabled digital transformation across various sectors, including construction. The construction industry has long been associated with conventional, labor-intensive practices that can adversely influence the entire construction process. However, this culture is changing as key players in the sector are progressively identifying and embracing the vast opportunities and associated benefits of using digital tools and technologies to improve the performance and outcomes of the overall project lifecycle. To this end, this study uses the Delphi technique to identify 70 factors that contribute to the digital transformation of the construction industry, categorizing them into five groups: management, design, technology, policy, and infrastructure. Delphi analysis is used to examine the critical success factors for digital transformation identified in the literature and rate their importance during the preconstruction, construction, and facility management phases. Furthermore, this research results in the introduction of the Digital Transformation Level of Readiness Framework (DTRLF) to help facility management firms, clients, organizations, contractors, and designers comprehend the implementation of digital transformation within their respective domains and support decision-makers in establishing action to adapt related technologies in their respected project phases.

Dynamics of M-truncated optical solitons and other solutions to the fractional Kudryashov’s equation

The study of soliton theory plays a crucial role in the telecommunication industry’s utilization of nonlinear optics. The principal area of research in the field of optical solitons revolves around optical fibers, metamaterials, metasurfaces, magneto-optic waveguides, and other related technologies. Therefore, the examination of these solitons received significant attention from scholars in recent years. Optical solitons refer to electromagnetic waves that are confined within nonlinear dispersive medium, wherein the balance between dispersion and nonlinearity effects enables the intensity to remain constant. In this manuscript, the dynamical behavior of Kudryashov’s equation is discussed with the assistance of truncated M-fractional derivative. Kudryashov’s equation is a mathematical model utilized to characterize complex phenomena in telecommunications and transmission technology. It describes the propagation of nonlinear pulses in optical fibers. Different forms of soliton solutions like bright, dark, singular and combo solitions have been extracted. Moreover, hyperbolic, periodic and Jacobi elliptic function solutions are recovered. Two recently modern integration tools like Φ6-expansion method and modified generalized exponential rational function method have been adopted to recover the solutions. The used methods not only provides previously extracted solutions but also secures new solutions. In order to visually depict the output, a variety of graphs featuring distinct shapes are produced in response to appropriate parameter values. The results obtained from this research indicate that the chosen methodologies are effective in improving the understanding of nonlinear dynamical phenomena. A large number of engineers who employ engineering models are expected to find this research interesting. The results demonstrate that the selected methods are practical, straightforward to implement, and applicable to intricate systems across numerous domains, with a specific emphasis on the field of optical fibers. The findings indicate that the system may contain a considerable number of soliton structures.

Exploring potential diffusion pathways of biorefinery innovations—An agent‐based simulation approach for facilitating shared value creation

AbstractIn many European countries with plentiful forest resources, novel forest‐based businesses play a key role in the transition from our current fossil‐based economy towards a circular bioeconomy. For example, kraft lignin, a by‐product from the pulping industry, is produced in large amounts globally. To date, however, it is still only offered on the market by a small number of pulping companies. The successful innovation diffusion of related new technologies and businesses requires establishing a collective effort among multiple societal actors to motivate the sharing of value creation processes. In this paper, potential innovation diffusion pathways are modeled and simulated by means of an agent‐based approach (Biorefinery Products Innovation Diffusion model, BioPID). The paper investigates the conditions needed to encourage the diffusion of kraft lignin innovations as a (partial) replacement for fossil‐based feedstock in selected applications. The results reveal the basic mechanisms behind potential innovation diffusion pathways. The major barriers were found to be the high level of uncertainty surrounding the additional costs arising in lignin processing, the small number of lignin providers, and the presence of relatively homogeneous pricing strategies based on opportunity and basic preparation costs. The analysis of two product categories revealed different patterns in terms of innovation diffusion and potential greenhouse gas emissions. A novelty of BioPID is that it allows for iterative technology evaluation and technology foresight analysis of biorefinery projects (e.g., by combining techno‐economic, socio‐technical, and environmental aspects). This produces knowledge for diverse stakeholders involved in the lignin innovation ecosystem, thus enabling better communication on shared values and furthering innovation diffusion.

Adopting human resource information system and work-related outcomes in emerging market SMEs: unified theory of acceptance and use of technology

PurposeThis study investigates the psychological adoption of technology in relation to employees' mental beliefs about using technology in their workplace, because it is necessary to investigate the direct and indirect effects of information systems (IS) on employees' work-related results that underpin creativity and engagement.Design/methodology/approachUsing a cross-sectional design, data were collected from 153 human resource (HR) employees who used human resource information systems (HRIS) in small- and medium-sized enterprises (SMEs) in Malaysia.FindingsThe results show that effective acceptance and adoption of an HRIS enables HR employees and management in SMEs to be creative, balanced and engaged. Facilitating conditions and task-technology fit positively affect the behavioral intention to accept and adopt an HRIS. Additionally, organizational citizenship behavior moderates the relationship between the behavioral intention to accept and adopt an HRIS and employee creativity.Originality/valueThis study significantly advances the fields of human resource management and IS by elucidating the factors influencing employees' adoption of technology. In an effort to address a research gap in existing research, it introduces a unified theory of acceptance and use of technology, which precedes the psychological adoption process by individuals. Furthermore, it offers both empirical and theoretical insights into the interplay between technology adoption factors and their subsequent impact on work-related outcomes.

Artificial intelligence algorithms in unmanned surface vessel task assignment and path planning: A survey

Due to the complex environment and variable demands, unmanned surface vessel (USV) task assignment and path planning have received much attention from academia and industry in recent years. Artificial intelligence technologies are increasingly adopted for solving the USV task assignment and path planning problems. This paper aims to give a comprehensive literature review of achievements, trends and challenges about the USV tasks assignment and path planning. First, the concerned problems are divided into two categories (single-USV and multi-USV), and the related work is thoroughly reviewed. Second, the solution methods, especially artificial intelligence (AI) related technologies and approaches, are analyzed and discussed. Third, the common external constraints and disturbances in the maritime environment are described. In particular, the obstacle avoidance strategies and algorithms are discussed and summarized systematically. Next, the applications to scientific exploration , military, and fishery industry are presented. Finally, we conclude this survey and indicate future research directions.

Classification of brain tumors based on magnetic resonance imaging (MRI) using deep learning models

Nowadays, With the advancements in medical care and the improvement in global living standards, there has been a continuous increase in the average life expectancy of people around the world, and the aging problem is constantly aggravated, brain tumors have become a growing global health problem. The project aims to use deep learning models to classify magnetic resonance imaging (MRI) images of brain tumors. By constructing convolutional neural network model, image feature extraction and classification are carried out. Data preprocessing, data enhancement, Adaptive Moment Estimation (Adam) are used to improve the model performance, plot the accuracy curve and generate the confusion matrix, and visualize the classification performance of the model. Possible future tasks may include optimizing the model architecture and expanding the exploration of data augmentation techniques to bolster the model's performance, while also further investigating the model's interpretability to understand the internal mechanisms of the model when making predictions. In addition, the project has great application potential, and the model can be applied to the actual clinical assisted diagnosis system, which has good scalability and application prospect. By using deep learning model and related technologies, the accuracy of brain tumor classification can be improved in clinical diagnosis, and better diagnosis and treatment services can be provided for the majority of brain tumor patients.

Make Way for the Wind—Promoting Urban Wind Corridor Planning by Integrating RS, GIS, and CFD in Urban Planning and Design to Mitigate the Heat Island Effect

Under the trend in climate change, global warming, and the increasingly serious urban heat island effect, promoting urban wind corridor planning to reduce urban temperature and mitigate the effect of urban heat islands has received widespread attention in many cities. With emerging awareness of the need to explicitly incorporate climate considerations into urban planning and design, integrating current spatial analysis and simulation tools to enhance urban wind corridor planning to obtain the best urban ventilation effect has become an increasingly important research topic in green city development. However, how to systematically carry out urban wind corridor planning by employing related technology and simulation tools is a topic that needs to be explored urgently in both theory and practice. Taking Zhumadian City in China as an example, this study proposes a method and planning approach that uses remote sensing (RS), geographic information system (GIS), and computational fluid dynamics (CFD) in an integrated way to understand urban landscape and to conduct urban wind corridor planning. The research results reveal that the urban form of Zhumadian City favors the development of urban wind corridors, and that the railway lines and some major roads in the city have the potential to be developed as the city’s main wind corridors. However, there are still ventilation barriers resulting from the existing land use model and building layout patterns that need to be adjusted. In terms of local-level analysis, the CFD simulation analysis also reveals that some common building layout patterns may result in environments with poor ventilation. Finally, based on the results of our empirical analysis and local planning environment, specific suggestions are provided on how to develop appropriate strategies for urban wind corridor planning and adjustments related to land use planning and building layout patterns in order to mitigate the impact of the urban heat island effect.

An Integrated Decision Support System for Low-Disturbance Surface Mining

Low-disturbance mining in surface mining (LDM) can transform traditional surface mine production systems into a more sustainable model by reducing the disturbance of surface mining, minimizing pollutant emissions, and reducing ecological impacts. The purpose of this paper is to explore the LDM evaluation method by applying multi-criteria decision-making to provide technical support for LDM implementation. Therefore, an evaluation method based on the combination of the fuzzy analytical hierarchy process (F-AHP) and grey clustering was proposed. Analyzed in terms of the current status of the evaluation indicators (reality) and the significance of the development of the LDM (desirability). Determined the weights and low-disturbance (LD) levels of the evaluation indicators. Combined with the fuzzy technique for order preference by similarity to an ideal solution (F-TOPSIS), the low-disturbance open pit mining paths are ranked, and finally, the decision support system for low-disturbance mining in surface mining is constructed. This study not only enriches the existing literature on related technologies but also lays the foundation for further research on LDM and provides exploratory insights for deeper improvement of LD level in surface mining.

Recent development and engineering practices of space grid structures in China

Space grid structures are widely used in the field of structural engineering due to their good mechanical properties and simple construction procedures. This paper reviews the development of space grid structures and mainly introduces the development of space grid structures in China in recent years. Some typical applications of space grid structures are introduced and the technical developments are summarized. It shows that China not only has a large number of engineering applications of space grid structures, but also a rapid development of related technologies. Finally, some prospects for space grid structures are discussed.

Mathematics and the formal turn

Since the early twentieth century, it has been understood that mathematical definitions and proofs can be represented in formal systems with precise grammars and rules of use. Building on such foundations, computational proof assistants now make it possible to encode mathematical knowledge in digital form. This article enumerates some of the ways that these and related technologies can help us do mathematics.

Building digital patient pathways for the management and treatment of multiple sclerosis.

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.