18 research outputs found
Exploration of customer churn routes using machine learning probabilistic models
The ongoing processes of globalization and deregulation are changing the competitive framework in the majority of economic sectors. The appearance of new competitors and technologies entails a sharp increase in competition and a growing preoccupation among service providing companies with creating stronger bonds with customers. Many of these companies are shifting resources away from the goal of capturing new customers and are instead focusing on retaining existing ones. In this context, anticipating the customerÂżs intention to abandon, a phenomenon also known as churn, and facilitating the launch of retention-focused actions represent clear elements of competitive advantage.
Data mining, as applied to market surveyed information, can provide assistance to churn management processes. In this thesis, we mine real market data for churn analysis, placing a strong emphasis on the applicability and interpretability of the results. Statistical Machine Learning models for simultaneous data clustering and visualization lay the foundations for the analyses, which yield an interpretable segmentation of the surveyed markets. To achieve interpretability, much attention is paid to the intuitive visualization of the experimental results. Given that the modelling techniques under consideration are nonlinear in nature, this represents a non-trivial challenge. Newly developed techniques for data visualization in nonlinear latent models are presented. They are inspired in geographical representation methods and suited to both static and dynamic data representation
The effect of noise and sample size in the performance of an unsupervised feature relevant determination method for manifold learning
The research on unsupervised feature selection is scarce in comparison to that for supervised
models, despite the fact that this is an important issue for many clustering
problems. An unsupervised feature selection method for general Finite Mixture Models
was recently proposed and subsequently extended to Generative Topographic Mapping
(GTM), a manifold learning constrained mixture model that provides data clustering
and visualization. Some of the results of previous research on this unsupervised feature
selection method for GTM suggested that its performance may be affected by insuficient
sample size and by noisy data. In this thesis, we test in detail such limitations of the
method and outline some techniques that could provide an at least partial solution to
the negative effect of the presence of uninformative noise. In particular, we provide a
detailed account of a variational Bayesian formulation of feature relevance determination
for GTM
Visualisation of bioinformatics datasets
Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental importance in biology. Predicting functions of polymorphic molecules is important in order to design more effective medicines. Analysing major histocompatibility complex (MHC) polymorphism is important for mate choice, epitope-based vaccine design and transplantation rejection etc. Most of the existing exploratory approaches cannot analyse these datasets because of the large number of molecules with a high number of descriptors per molecule. This thesis develops novel methods for data projection in order to explore high dimensional biological dataset by visualising them in a low-dimensional space. With increasing dimensionality, some existing data visualisation methods such as generative topographic mapping (GTM) become computationally intractable. We propose variants of these methods, where we use log-transformations at certain steps of expectation maximisation (EM) based parameter learning process, to make them tractable for high-dimensional datasets. We demonstrate these proposed variants both for synthetic and electrostatic potential dataset of MHC class-I. We also propose to extend a latent trait model (LTM), suitable for visualising high dimensional discrete data, to simultaneously estimate feature saliency as an integrated part of the parameter learning process of a visualisation model. This LTM variant not only gives better visualisation by modifying the project map based on feature relevance, but also helps users to assess the significance of each feature. Another problem which is not addressed much in the literature is the visualisation of mixed-type data. We propose to combine GTM and LTM in a principled way where appropriate noise models are used for each type of data in order to visualise mixed-type data in a single plot. We call this model a generalised GTM (GGTM). We also propose to extend GGTM model to estimate feature saliencies while training a visualisation model and this is called GGTM with feature saliency (GGTM-FS). We demonstrate effectiveness of these proposed models both for synthetic and real datasets. We evaluate visualisation quality using quality metrics such as distance distortion measure and rank based measures: trustworthiness, continuity, mean relative rank errors with respect to data space and latent space. In cases where the labels are known we also use quality metrics of KL divergence and nearest neighbour classifications error in order to determine the separation between classes. We demonstrate the efficacy of these proposed models both for synthetic and real biological datasets with a main focus on the MHC class-I dataset
Optimising opioids for cancer pain: Investigating the basis of inter-individual analgesic response and side-effect profile
There is significant inter-individual variation in response to morphine in terms of analgesia
and side-effects. In recent years there has been growing interest in the possibility that genetic
factors may play a role in variability in morphine response.
The aims of this thesis were to develop a clinically relevant method of defining response to
morphine, to investigate how multiple clinical and genetic factors may interact together to
influence response to morphine and to explore constipation as a common side-effect of
morphine.
Clinical and biological data were collected as part of two clinical trials: 1) A prospective
observational study which included patients taking oral morphine for cancer pain (N=298)
and 2) A prospective follow-up randomised controlled trial of oral morphine versus oral
oxycodone for cancer pain (recruitment ongoing). Symptom complexes were examined using
Principal Components Analysis. Genetic association testing was carried out using both the
candidate gene approach (sequence-specific primers with polymerase chain reaction) and
genome-wide assays. Multivariate regression analyses were used to explore gene-gene and
gene-environment interactions. Preliminary testing of a constipation assessment tool was
performed.
Analgesic response and central side-effects appear to be distinct components of morphine
response. The genetic and clinical factors associated with these clinical outcomes and with
daily morphine dose requirements are markedly different.
There is inter-individual variation in bowel function in cancer patients on oral morphine.
Constipation is a common symptom and is generally poorly managed.
It is too early to be able to apply the results of genetic association studies of morphine
response in cancer pain to clinical practice. Response to morphine is complex, both in terms
of clinical confounders and pharmacogenetics. Challenges for future research include
carrying out carefully designed studies of adequate power, standardising outcome measures
of response to morphine and expansion of the genetic association testing
[<sup>18</sup>F]fluorination of biorelevant arylboronic acid pinacol ester scaffolds synthesized by convergence techniques
Aim: The development of small molecules through convergent multicomponent reactions (MCR) has been boosted during the last decade due to the ability to synthesize, virtually without any side-products, numerous small drug-like molecules with several degrees of structural diversity.(1) The association of positron emission tomography (PET) labeling techniques in line with the âone-potâ development of biologically active compounds has the potential to become relevant not only for the evaluation and characterization of those MCR products through molecular imaging, but also to increase the library of radiotracers available. Therefore, since the [18F]fluorination of arylboronic acid pinacol ester derivatives tolerates electron-poor and electro-rich arenes and various functional groups,(2) the main goal of this research work was to achieve the 18F-radiolabeling of several different molecules synthesized through MCR. Materials and Methods: [18F]Fluorination of boronic acid pinacol esters was first extensively optimized using a benzaldehyde derivative in relation to the ideal amount of Cu(II) catalyst and precursor to be used, as well as the reaction solvent. Radiochemical conversion (RCC) yields were assessed by TLC-SG. The optimized radiolabeling conditions were subsequently applied to several structurally different MCR scaffolds comprising biologically relevant pharmacophores (e.g. ÎČ-lactam, morpholine, tetrazole, oxazole) that were synthesized to specifically contain a boronic acid pinacol ester group. Results: Radiolabeling with fluorine-18 was achieved with volumes (800 ÎŒl) and activities (†2 GBq) compatible with most radiochemistry techniques and modules. In summary, an increase in the quantities of precursor or Cu(II) catalyst lead to higher conversion yields. An optimal amount of precursor (0.06 mmol) and Cu(OTf)2(py)4 (0.04 mmol) was defined for further reactions, with DMA being a preferential solvent over DMF. RCC yields from 15% to 76%, depending on the scaffold, were reproducibly achieved. Interestingly, it was noticed that the structure of the scaffolds, beyond the arylboronic acid, exerts some influence in the final RCC, with electron-withdrawing groups in the para position apparently enhancing the radiolabeling yield. Conclusion: The developed method with high RCC and reproducibility has the potential to be applied in line with MCR and also has a possibility to be incorporated in a later stage of this convergent âone-potâ synthesis strategy. Further studies are currently ongoing to apply this radiolabeling concept to fluorine-containing approved drugs whose boronic acid pinacol ester precursors can be synthesized through MCR (e.g. atorvastatin)
Generation and Applications of Knowledge Graphs in Systems and Networks Biology
The acceleration in the generation of data in the biomedical domain has necessitated the use of computational approaches to assist in its interpretation. However, these approaches rely on the availability of high quality, structured, formalized biomedical knowledge. This thesis has the two goals to improve methods for curation and semantic data integration to generate high granularity biological knowledge graphs and to develop novel methods for using prior biological knowledge to propose new biological hypotheses. The first two publications describe an ecosystem for handling biological knowledge graphs encoded in the Biological Expression Language throughout the stages of curation, visualization, and analysis. Further, the second two publications describe the reproducible acquisition and integration of high-granularity knowledge with low contextual specificity from structured biological data sources on a massive scale and support the semi-automated curation of new content at high speed and precision. After building the ecosystem and acquiring content, the last three publications in this thesis demonstrate three different applications of biological knowledge graphs in modeling and simulation. The first demonstrates the use of agent-based modeling for simulation of neurodegenerative disease biomarker trajectories using biological knowledge graphs as priors. The second applies network representation learning to prioritize nodes in biological knowledge graphs based on corresponding experimental measurements to identify novel targets. Finally, the third uses biological knowledge graphs and develops algorithmics to deconvolute the mechanism of action of drugs, that could also serve to identify drug repositioning candidates. Ultimately, the this thesis lays the groundwork for production-level applications of drug repositioning algorithms and other knowledge-driven approaches to analyzing biomedical experiments
âBeing Humanâ: A Grounded Theory of Complexity and Serendipity in Cancer Clinical Trials.
Abstract
Background
Cancer presents a complex and intractable disease resulting in millions of deaths worldwide each year. As a metastatic disease bearing metamorphic characteristics, cancerâs emergent properties continue to challenge science, medicine, and society. Cancer research is a specialist field crucial to the advancement of patient treatment and care, yet it faces growing challenges due to the complex nature of an evolving disease, stratified treatments, and intensive trial protocols, compounded by increasing global disease burdens. Human ingenuity and resiliency are central to overcoming the greatest challenges facing contemporary populations, achieved through research innovation and knowledge exchange across ranging disciplines. Improving population health and patient-centred outcomes stands at the fore of global challenges facing society in the twenty first century, requiring novel and dynamic responses to increasing chronic disease burdens and exposure risks to emergent viral pathogens.
Aims
The aim of this thesis was to understand the nature of cancer clinical trial operational delivery, evaluating challenges and burdens of professionals and patients participating in cancer research studies. The nature of multi-agency working and transdisciplinarity across health sciences is as complex as the biological and societal challenges that their research seeks to address. Establishing sustainable, cohesive, and collaborative relationships across the medical continuum is pivotal to solving persistent challenges of complex diseases and societal burdens. The study sought to develop a contextualised grounded theory elucidating situated challenges and complexity experienced at NHS sites in the UK. The purpose of the grounded theory would be to support the development of enhanced, person-centred models of clinical research operational delivery, which could respond to emergent and dynamically adaptive healthcare and epidemiological population needs.
Methods
Evaluating Follow-up and Complexity in cancer Clinical Trials (EFACCT), the study presented in this thesis, was conducted at ranging NHS secondary care sites in England and Scotland. Drawing on constructivist grounded theory (Charmaz, 2006), the multi-faceted realities of cancer clinical trial delivery are unveiled, using a mixed methodsâgrounded theory (MM-GT) design. The comprehensive, contextual evaluation combines evidence from quantitative and qualitative paradigms, using inductive and deductive methods. The study drew together multifaceted perspectives and values of 165 participants from six studies; Delphi, questionnaire, and interview studies, separated into patient and professional cohorts.
Results
The research provides original insights into the nature of cancer research delivery, its challenges and complexities, highlighting the importance of coherency in healthcare systems. The Constructivist Grounded Theory presented in this thesis, provides an organising framework and practical model for managing and embracing transformative learning and practice in response to dynamically evolving challenges that exist within complex healthcare delivery systems and networks. The original data generated provides new knowledge on the human aspects of clinical research and the contexts for its practice. The situated experiences led to the development of a grounded theory of human perceptions of complexity and serendipity in clinical research and the conception of a Prismatic Coherence Model (PCM) for the evaluation and designing of patient care and follow-up and the effective operational management of complex relationships, practices and processes existing within adaptive clinical research and healthcare delivery systems. PCM is an inclusive and responsive strategic design approach, sensitive to variable contexts and system complexities, and promotes transdisciplinarity in order to advance opportunities, knowledge and resources to advance population health through clinical research
Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband
Erschienen bei: universi - UniversitÀtsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt:
Track 1: Produktion & Cyber-Physische Systeme
Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities
Service Systems, Smart Service Systems and Cyber- Physical SystemsâWhatâs the difference? Towards a Unified Terminology
Developing an Industrial IoT Platform â Trade-off between Horizontal and Vertical Approaches
Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory
Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis
Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs
Track 2: Logistic Analytics
An Empirical Study of Customersâ Behavioral Intention to Use Ridepooling Services â An Extension of the Technology Acceptance Model
Modeling Delay Propagation and Transmission in Railway Networks
What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?
Robust Route Planning in Intermodal Urban Traffic
Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design)
Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes
Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement
Strategic Analysis in the Realm of Enterprise Modeling â On the Example of Blockchain-Based Initiatives for the Electricity Sector
Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren
Novicesâ Quality Perceptions and the Acceptance of Process Modeling Grammars
Entwicklung einer Definition fĂŒr Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen
Designing a Reference Model for Digital Product Configurators
Terminology for Evolving Design Artifacts
Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects
Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications
Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy
Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications
Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management)
eGovernment Competences revisited â A Literature Review on necessary Competences in a Digitalized Public Sector
Say Hello to Your New Automated Tutor â A Structured Literature Review on Pedagogical Conversational Agents
Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education
Conceptualizing Immersion for Individual Learning in Virtual Reality
Designing a Flipped Classroom Course â a Process Model
The Influence of Risk-Taking on Knowledge Exchange and Combination
Gamified Feedback durch Avatare im Mobile Learning
Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks
Track 5: Data Science & Business Analytics
Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness
Applied image recognition: guidelines for using deep learning models in practice
Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting
Reading Between the Lines of Qualitative Data â How to Detect Hidden Structure Based on Codes
Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation
Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data
Topic Embeddings â A New Approach to Classify Very Short Documents Based on Predefined Topics
Leveraging Unstructured Image Data for Product Quality Improvement
Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Knowledge Discovery from CVs: A Topic Modeling Procedure
Online Product Descriptions â Boost for your Sales?
EntscheidungsunterstĂŒtzung durch historienbasierte Dienstreihenfolgeplanung mit Pattern
A Semi-Automated Approach for Generating Online Review Templates
Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization
Bedeutung von Predictive Analytics fĂŒr den theoretischen Erkenntnisgewinn in der IS-Forschung
Track 6: Digitale Transformation und Dienstleistungen
Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems
Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey
Taxonomy of Digital Platforms: A Platform Architecture Perspective
Value of Star Players in the Digital Age
Local Shopping Platforms â Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis
A Socio-Technical Approach to Manage Analytics-as-a-Service â Results of an Action Design Research Project
Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units
Expectations vs. Reality â Benefits of Smart Services in the Field of Tension between Industry and Science
Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment
Characterising Social Reading Platformsâ A Taxonomy-Based Approach to Structure the Field
Less Complex than Expected â What Really Drives IT Consulting Value
Modularity Canvas â A Framework for Visualizing Potentials of Service Modularity
Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things
A Taxonomy of Barriers to Digital Transformation
Ambidexterity in Service Innovation Research: A Systematic Literature Review
Design and success factors of an online solution for cross-pillar pension information
Track 7: IT-Management und -Strategie
A Frugal Support Structure for New Software Implementations in SMEs
How to Structure a Company-wide Adoption of Big Data Analytics
The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age
Bewertung des Kundennutzens von Chatbots fĂŒr den Einsatz im Servicedesk
Understanding the Benefits of Agile Software Development in Regulated Environments
Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies
Agile and Attached: The Impact of Agile Practices on Agile Team Membersâ Affective Organisational Commitment
The Complexity Trap â Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations
Platform Openness: A Systematic Literature Review and Avenues for Future Research
Competence, Fashion and the Case of Blockchain
The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity
Track 8: eHealth & alternde Gesellschaft
Security and Privacy of Personal Health Records in Cloud Computing Environments â An Experimental Exploration of the Impact of Storage Solutions and Data Breaches
Patientenintegration durch Pfadsysteme
Digitalisierung in der StressprĂ€vention â eine qualitative Interviewstudie zu Nutzenpotenzialen
User Dynamics in Mental Health Forums â A Sentiment Analysis Perspective
Intent and the Use of Wearables in the Workplace â A Model Development
Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review
Understanding the Habitual Use of Wearable Activity Trackers
On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Usersâ Goal Orientations in Affecting the Benefits Gained
Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects
Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings
Track 9: Krisen- und KontinuitÀtsmanagement
Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland
Fake News Perception in Germany: A Representative Study of Peopleâs Attitudes and Approaches to Counteract Disinformation
Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment
Track 10: Human-Computer Interaction
Towards a Taxonomy of Platforms for Conversational Agent Design
Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis
Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment
Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren
Designing Dynamic Decision Support for Electronic Requirements Negotiations
Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress
Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents
Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review
Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach
The Role of Early User Participation in Discovering Software â A Case Study from the Context of Smart Glasses
The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games
Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods
Track 11: Information Security and Information Privacy
Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions
To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context
Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR
On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market
What is Your Selfie Worth? A Field Study on Individualsâ Valuation of Personal Data
Justification of Mass Surveillance: A Quantitative Study
An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms
Track 12: Umweltinformatik und nachhaltiges Wirtschaften
KommunikationsfĂ€den im Nadelöhr â Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt
Potentiale und Herausforderungen der Materialflusskostenrechnung
Computing Incentives for User-Based Relocation in Carsharing
Sustainabilityâs Coming Home: Preliminary Design Principles for the Sustainable Smart District
Substitution of hazardous chemical substances using Deep Learning and t-SNE
A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment
A Survey of Smart Energy Services for Private Households
Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation â A Literature Review
Ein EntscheidungsunterstĂŒtzungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse
Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy
Digitale RĂŒckverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie
Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones
Towards Predictive Energy Management in Information Systems: A Research Proposal
A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology
Track 13: Digital Work - Social, mobile, smart
On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work
The Potential of Augmented Reality for Improving Occupational First Aid
Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants
Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI
A Case Study on Cross-Hierarchical Communication in Digital Work Environments
âShow Me Your People Skillsâ - Employing CEO Branding for Corporate Reputation Management in Social Media
A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change
The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects
The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance
Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp
The Effect of Marker-less Augmented Reality on Task and Learning Performance
Antecedents for Cyberloafing â A Literature Review
Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project
Track 14: GeschÀftsmodelle und digitales Unternehmertum
Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes
Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services
Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective
Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction
Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes
Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators
When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies
Special Track 1: Student Track
Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail
From Facets to a Universal Definition â An Analysis of IoT Usage in Retail
Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study
Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Application of Process Mining Techniques to Support Maintenance-Related Objectives
How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce
Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance?
Improving Business Model Configuration through a Question-based Approach
The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning
Evaluation von ITSM-Tools fĂŒr Integration und Management von Cloud-Diensten am Beispiel von ServiceNow
How Software Promotes the Integration of Sustainability in Business Process Management
Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry
Special Track 3: Demos & Prototyping
Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype
Application-oriented robotics in nursing homes
Augmented Reality for Set-up Processe
Mixed Reality for supporting Remote-Meetings
Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung
Automatically Extracting and Analyzing Customer Needs from Twitter: A âNeedminingâ Prototype
GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities
TUCANA: A platform for using local processing power of edge devices for building data-driven services
Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur
Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation fĂŒr Ă€ltere Nutzerinnen und Nutzer
A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach
Exergames & Dementia: An interactive System for People with Dementia and their Care-Network
Workshops
Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik â EMoWIâ19)
Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates
Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management
Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research
Die Mitarbeiter von morgen - Kompetenzen kĂŒnftiger Mitarbeiter im Bereich Business Analytics
Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati
Scale-Âup of human pluripotent stem cell-Âbased therapies for age-Ârelated macular degeneration
This doctoral thesis was in collaboration with a research group from the Institute of
Ophthalmology at Moorfields Eye Hospital and the London Project to Cure Blindness. The
group was in late stage pre-clinical development creating a pluripotent stem cell (PSC)
derived therapy to produce retinal pigment epithelium cells (RPE) for the treatment of Age
Related Macular Degeneration (AMD). Creating effective treatments for AMD is vital given
that it is the leading cause of blindness in the developed world with around 500,000 people
in the UK afflicted with the disease, half of which are registered as visually impaired. In
addition, for the dry form of the disease, which represents 85-90% of total cases, there is no
effective treatment.
The current lab based manufacturing protocols intended for use during Phase 1 trials are
not feasible for subsequent larger scale clinical trials or for the commercial manufacture of
an affordable mass-produced therapy. The aim of this thesis was to explore the feasibility of
applying methodologies and technologies from traditional biotechnology production to cell
therapy manufacturing. Specifically use of bioreactors to scale up cell culture (Chapter 2),
the application of online monitoring and control to PSC culture (Chapter 3), the use of a
design of experiments (DoE) approach to PSC differentiation (Chapter 4) and cell-cell
purification (Chapter 5).
Taken as a whole it is clear that the application of traditional biomanufacturing
technologies and approaches have much potential when applied to cell therapies, and
specifically a PSC derived cell therapy to treat blindness. However much more work is
needed to reduce variability in the process to better understand the impact of process
parameters on critical quality attributes and how best to approach these in an environment
where there is little clinical experience to define the target product profile