The healthcare sector has become a key area for the development and application of new technology and, not least, Artificial Intelligence (AI). New reports are constantly being published about how this algorithm-based technology supports or performs various medical tasks. These illustrates the rapid development of AI that is taking place within healthcare and how algorithms are increasingly involved in systems and medical devices designed to support medical decision-making.  The digital revolution and the advancement of AI technologies represent a step change in the way healthcare may be delivered, medical services coordinated and well-being supported. It could allow for easier and faster communication, earlier and more accurate diagnosing and better healthcare at lower costs. However, systems and devices relying on AI differs significantly from other, traditional, medical devices. AI algorithms are – by nature – complex and partly unpredictable. Additionally, varying levels of opacity has made it hard, sometimes impossible, to interpret and explain recommendations or decisions made by or with support from algorithmic decision systems. These characteristics of AI technology raise important technological, practical, ethical and regulatory issues. The objective of this thesis is to analyse the relationship between the EU regulation on medical devices (MDR) and algorithmic decision systems (ADS) used within the medical domain. The principal question is whether the MDR is enough to guarantee safe and robust ADS within the European healthcare sector or if complementary (or completely different) regulation is necessary. In essence, it will be argued that (i) while ADS are heavily reliant on the quality and representativeness of underlying datasets, there are no requirements with regard to the quality or composition of these datasets in the MDR, (ii) while it is believed that ADS will lead to historically unprecedented changes in healthcare , the regulation lacks guidance on how to manage novel risks and hazards, unique to ADS, and that (iii) as increasingly autonomous systems continue to challenge the existing perceptions of how safety and performance is best maintained, new mechanisms (for transparency, human control and accountability) must be incorporated in the systems. It will also be found that the ability of ADS to change after market certification, will eventually necessitate radical changes in the current regulation and a new regulatory paradigm might be needed.

Multi-drug resistance is increasingly becoming a challenge to tuberculosis control programmes globally. Treatment of multi-drug resistance tuberculosis (MDR-TB) includes aminoglycoside antibiotics which are known to cause hearing loss. Ototoxicity monitoring services are often provided to patients undergoing treatment for MDR-TB for early detection of ototoxic hearing loss to facilitate alerting the patients and relevant medical staff about the presence and progression of any hearing loss. Previously, models of managing patients with MDR-TB required mandatory hospitalization for at least 6 months. This made it relatively easy to monitor the hearing status of patients during their stay in the hospital. However, with recent introduction of policy guidelines that support management of patients with MDR-TB on an outpatients basis, ototoxicity monitoring for these patients will need to be reorganized to align with the new policy guidelines. The extent of the uptake of these services when patients are accessing them as outpatients is however, unknown. This study therefore aimed to describe the patterns of utilisation and explore the barriers and factors that facilitate the use of ototoxicity monitoring services when provided on an outpatient basis in the Cape Town Metropolitan area, Western Cape, South Africa.

Artificial intelligence (AI) is the study of science, engineering, and the development of intelligent machines. AI is based on human intelligence with the exception that it is not restricted by biologically observable limitations. AI has developed rapidly over the past few years and has become important all over the world. This Master’s thesis brings up AI as a medical device and the European market. The thesis provides guidance in the form of important aspects to be considered by small and medium-sized enterprises (SMEs) when marketing products in Europe. There is a lack of guidance and clear descriptions regarding AI/ML-based medical devices in Europe. Both MDR and medical devices with AI/ML are relatively new and uncharted. There are no clear guidelines, instructions, or articles that clearly describe what is needed to get an AI/ML-based medical device on the European market. In summary, there is no guidance that SMEs could benefit from when it comes to AI/ML-based medical devices and the European market. With this thesis the subject is enlightened and hopefully, the gap in knowledge about this is reduced. The chosen method to achieve the goal of this thesis is both a literature review and qualitative research in the form of interviews with relevant experts within the field. The results show that there is a lack of guidelines and regulations for AI-based medical devices, it is harder for SMEs to market such devices and it is complicated to put an AI-based medical device on the European market due to MDR. SMEs should consider certain aspects important when developing an AI/ML-based medical device and placing it on the European market. The identified aspects are creating a regulatory plan, using guidelines from example FDA, procuring regulatory competence from the start, risk classification, economics, clinical evaluation, risk management, having end-user in mind during the development, and data management/cybersecurity. The results also show that if guidelines are developed, they should contain thresholds for different characteristics in AI/ML-based medical devices, risk classification of the device, classification requirements, checklists, templates, actions, good manufacturing process description, data management, cybersecurity, patient safety process description, clinical evaluation process description, regional regulatory adaptions, and risk mitigation. The results of this thesis can be used in many ways and by many. By solely using this report for AI/ML-based medical devices, complete compliance with MDR is not fulfilled.

Cette mémoire vise à développer une méthode de pondération par l’inverse de le probabilité de traitement (Augmented Inverse Probability of Treatment Weighting; AIPTW) et estimation par maximum de vraisemblance ciblée (Targeted Maximum Likelihood Estimation; TMLE) dans le contexte d'une méta-analyse en réseau avec données individuelles (Individual Patient Data Network Meta-Analysis; IPD-NMA) avec données observationnelles. Nous proposons également des méthodes pour estimer le score de propension généralisé (Generalized Propensity Score; GPS) pour finalement estimer l'effet causal d'une combinaison donnée de traitements (un régime) interprété à partir de d’une population globale. Cette recherche a été motivée par une mise à jour récente des données de patients atteints de la tuberculose multirésistante (Multidrug-Resistant Tuberculosis ; MDR-TB), une maladie infectieuse respiratoire causée par le bacillus mycobactérie avec un taux de mortalité élevé. Une compléxité notable de notre scénario est que toutes les régimes de traitements n'ont pas été observés dans toutes les études. L’inférence causale est définie comme l'étude de l'effet des traitements sur un résultat. Bien que les études cliniques randomisées sont l'étalon-or pour l'investigation des causes et effets, en raison de certaines limitations, leur utilisation n'est pas toujours faisable. Ainsi, l’analyse de données observationnelles est proposée. Donc, il est important de développer des méthodes qui nous permettent d'utiliser les informations provenant des données observationnelles. L'utilisation des informations provenant de plusieurs études individuelles nous permet d'évaluer les associations entre les traitements et les résultats qui sont spécifiques aux sous-populations. Aussi, une méta-analyse en réseau nous permet comparer plusieurs régimes au lieu de seulement deux. Nous estimons le taux de succès d’un régime donné à partir d'un ensemble d'études dans lesquelles le régime était disponible, puis le généralisons à l'ensemble de la population source. La théorie et les résultats d’une étude de simulation démontre que les méthodes développées sont doublement robustes. Cependant, TMLE démontre plus de robustesse, en particulier lorsqu’une méthode nouvellement proposée pour estimer le GPS est utilisée. Le résultat de l'application donne des estimations d’un taux de succès de traitement généralisé entre 50 à 61 % pour le régime {Pyrazinamide,Kanamycin,Ofloxacin,Ethionamide,Cyloserine} tandis que le taux observé de l’ensemble des données était de 59 %. / This thesis aims for developing Augmented Inverse Probability of Treatment Weighting (AIPTW) and Targeted Maximum Likelihood Estimation (TMLE) in the setting of Individual Patient Data Network Meta-Analysis (IPD-NMA) of observational data and propose a method to estimate the Generalized Propensity Score (GPS) to eventually estimate the causal effect of a given combination of treatments (a regimen) and generalize it to a global population. This research was motivated by a recent update on IPD_NMA of Multidrug-Resistant Tuberculosis (MDR-TB) - a respiratory infectious disease caused by bacillus mycobacterium with a high rate of mortality - where not all the regimens observed in all the studies. Although Randomized Controlled Trials (RCTs) are known to be the gold standard in investigating cause-and-effect including in causal inference (defined as the study of the effect of treatments on an outcome), but because of some known limitations using them is not always feasible. Thus, observational data are being proposed. Therefore, developing methods that enable us to use the information from observational data is important. In addition, using the information coming from individual studies allows us to evaluate associations between treatments and outcome which are specific to subpopulations. Also, a network meta-analysis allows us to study the effect of multiple treatments instead of two. We estimate the rate of treatment success for a given regimen from a set of studies where the regimen was available, and then generalize it to the whole network. The simulation result shows that the developed methods are doubly robust, however TMLE shows more robustness specially when the new proposed approach to estimate the GPS is being used. The application result shows a range of 50-61% for the generalized success rate of regimen {Pyrazinamide,Kanamycin,Ofloxacin,Ethionamide,Cyloserine} while the observed rate was 59% from multiple regimens.

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Yes / Background: Tracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult. Methods: This study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005–2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated. Findings: Our results suggest that clusters based on Spoligotyping could encompass transmission events that occurred almost 200 years prior to sampling while 24-loci-MIRU-VNTR often represented three decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events, e.g. in timespans of up to 10 years for a 5 SNP/allele cut-off. Interpretation: With the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting. / ERC grant [INTERRUPTB; no. 311725] to BdJ, FG and CJM; an ERC grant to TS [PhyPD; no. 335529]; an FWO PhD fellowship to PM [grant number 1141217N]; the Leibniz Science Campus EvolLUNG for MM and SN; the German Centre for Infection Research (DZIF) for TAK, MM, CU, PB and SN; a SNF SystemsX grant (TBX) to JP and TS and a Marie Heim-Vögtlin fellowship granted to DK by the Swiss National Science Foundation. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government – department EWI.

Tumorzellen entwickeln häufig Resistenzen gegen verschiedene strukturell und funktionell unabhängige Zytostatika, was als Multidrug-Resistenz (MDR) bezeichnet wird und die Hauptursache für das Scheitern einer Chemotherapie ist. Mit Hilfe von in vitro-Untersuchungen wurden erhöhte Genexpressionen der ABC-Transporter MDR1, MRP2 und BCRP als maßgebliche Resistenzfaktoren identifiziert, wie z.B. in den Magenkarzinomzellinien EPG85-257RDB (MDR1) und EPG85-257RNOV (BCRP) sowie in der Ovarialkarzinomzellinie A2780RCIS (MRP2). Ziel der Arbeit war die Entwicklung eines auf Ribozym-Technologie basierenden Therapieansatzes, welcher die Expressionen der oben genannten ABC-Transporter simultan inhibiert und dessen Anwendung zur Reversion der zellulären MDR führt. Dazu wurde ein Multitargetmultiribozym (MTMR) entwickelt, das aus in trans-aktiven Ribozymen besteht, die gegen die ABC-Transporter mRNAs gerichtet sind sowie aus in cis-spaltenden Ribozymen und aus Spacer-RNA-Sequenzen. Durch autokatalytische Spaltung in cis konnten die in trans-aktiven Ribozyme aus dem Gesamt-MTMR freigesetzt werden. Die Analyse der kinetischen Parameter des MTMRs ergab, daß die autokatalytisch entstandenen MTMR-Fragmente ihre Substrat-RNAs im Vergleich zu den korrespondierenden Monoribozymen ohne Einbuße an Effizienz spalten können. Darüber hinaus wurde die MTMR-Sequenz stabil in den drei eingangs genannten MDR-Zellinien exprimiert, was in einer signifikanten Reduktion der jeweiligen Ziel-mRNAs (97 % MDR1-, 80 % BCRP-, 96 % MRP2-mRNA) und der entsprechenden Proteine resultierte. Die Multidrug-Resistenz konnte aufgrund der MTMR-Expression um 70% (A2780RCIS), 95% (257RNOV), 100% (257RDB) und die Zytostatikumsakkumulation um 90% (257RNOV-Zellen) sowie 100% (257RDB-Zellen) revertiert werden. Das MTMR stellt erstmalig ein RNA-Konstrukt dar, welches in der Lage ist, simultan mehrere unabhängige Gene funktionell auszuschalten. Es besitzt daher ein großes Potential für zukünftige gentherapeutische Ansätze. / Cancer cells are often insensible against structurally and functionally unrelated drugs that is known as multiple drug resistance (MDR) and the main cause for treatment failure. Overexpression of the ABC-transporters P-gp (ABCB1), MRP2 (ABCC2), and BCRP (ABCG2) is associated with MDR in several cancer cell lines, e.g. in the stomach carcinoma cell lines EPG85-257RDB (P-gp), EPG85-257RNOV (BCRP), and in the ovarian carcinoma cell line A2780RCIS (MRP2). We aimed the development of a novel hammerhead ribozyme-based therapeutic approach capable of simultaneous silencing of the prementioned ABC-transporters, and consequently of reversing MDR phenotypes. We designed a so-called multitarget multiribozyme (MTMR) consisting of trans-acting hammerhead ribozymes directed against the MDR1, MRP2, and BCRP transcripts, of MDR1 homologous spacer sequences, and of cis-acting ribozymes against the spacer sequences. Autocatalytic cleavage in cis excised the full-length MTMR, and released trans-acting hammerhead ribozymes. We also evaluated the catalytic features of the MTMR using large RNA target molecules. Comparison of the kinetic values of the autocatalytically derived MTMR fragments with those of corresponding mono-ribozymes demonstrated an MTMR-mediated substrate cleavage without distinct loss in catalytic efficiency. Moreover, the MTMR was stably expressed in the prementioned multidrug-resistant cancer cell lines, and decreased the targeted transcripts about 97% (MDR1), 80% (MRP2), and 96% (BCRP) as well as the corresponding protein levels, respectively. Cellular MDR could be reverted about 70% (A2780RCIS), 95% (257RNOV), and 100% (257RDB). Additionally, the MTMR reversed mitoxantrone accumulation entirely, and daunorubicin accumulation about 90% in stomach carcinoma cells, respectively. Taken together, the MTMRs capability of simultaneous silencing of multiple genes provides an effective instrument to knockdown genes of interest.

P-Glykoprotein als Produkt des MDR1-Gens stellt einen gut untersuchten Mediator der Multidrugresistenz (MDR) in humanen Malignomen dar. Die Überexpression dieses ABC-Transporters steht in Korrelation zu einer erniedrigten Tumorremission und einer kürzeren Überlebensrate der Patienten. Bisherige Versuche, das Protein über niedermolekulare Substanzen (MDR-Modulatoren) zu inhibieren, vermochten in allen bisherigen klinischen Studien nicht zu überzeugen, so daß diese bis heute keinen Eingang in Standardtherapieschemata gefunden haben. Ziel dieser Arbeit war es, mittels RNA-Interferenz Strategien die Expression von MDR1 zu hemmen und eine Reversion der zellulären Chemoresistenz sowohl im Zellkultur- als auch im Tiermodell zu erreichen. Für die in vitro Untersuchungen an drei humanen multidrug-resistenten Karzinomzellinien wurden verschiedene siRNA (short interfering) Duplexe und shRNA (short hairpin)-exprimierende Vektoren gegen die MDR1 mRNA entwickelt. Die Behandlung der Zellen mit siRNAs führte zu einer bis zu 91 %igen Inhibition der MDR1 mRNA-Expression und zu einer Sensitivierung der Zellen gegenüber dem Anthrazyklin um 89 %. Diese Effekte konnte über einen Zeitraum von drei bis fünf Tagen aufrechterhalten werden. Die stabile Expression von anti-MDR1 shRNAs führte in zwei der untersuchten Zellmodelle zu einer dauerhaften und kompletten Überwindung des MDR1-abhängigen Resistenzphänotyps. Im Mausmodell konnte durch intratumorale Applikation des anti-MDR1 shRNA-kodierenden Vektors mittels low-volume Jet-Injektion eine komplette Reversion der MDR1-Überexpression sowie eine Wiederherstellung der Chemosensitivität gegenüber Doxorubicin in dem resistenten Tumormodell erreicht werden. Die Effizienz der kombinierten Gen- und Chemotherapie wird durch die Verminderung des in vivo Tumorwachstums auf das Volumen des von der sensiblen Zellinien-abgeleiteten Tumors reflektiert. / Multidrug resistance (MDR) is the major cause of failure of effective chemotherapeutic treatment of disseminated neoplasms. The "classical" MDR phenotype of human malignancies is mediated by drug extrusion by the adenosine triphosphate binding cassette (ABC)-transporter P-glycoprotein (MDR1/P-gp). For stable reversal of "classical" MDR in three human cancer cell lines by RNA interference (RNAi) technology, two small interfering RNA (siRNA) constructs and four H1-RNA gene promoter-driven expression vectors encoding anti-MDR1/P-gp short hairpin RNA (shRNA) molecules were constructed. In all cellular systems, siRNAs could specifically inhibit MDR1 expression up to 91% at the mRNA and protein levels. Resistance against daunorubicin was decreased to a maximum of 89%. The introduction of anti-MDR1/P-gp shRNA expression vectors leads in two of the three human cancer cell lines to a complete reversion of the MDR phenotype. The reversal of MDR was accompanied by a complete suppression of MDR1/P-gp expression on mRNA and protein level, and by a considerable increased intracellular anthracyline accumulation in the anti-MDR1/P-gp shRNA-treated cells. In a mouse xenograft model a complete in vivo restoration of MDR1 overexpression and chemosensitivity to doxorubicin could be obtained by intratumorally jet-injected anti-MDR1 shRNA in a multidrug resistant human cancer tumor model.

Para avaliar a influência dos polimorfismos de nucleotídeo único (SNPs) do CYP2B6, CYP3A5, GSTM1, GSTP1, GSTT1, PON1, NQO1 e MDR1 na resposta ao tratamento com R-CHOP e CHOP, 82 pacientes com Linfoma Difuso de Grandes Células B, sem evidências de infecção por HIV, foram selecionados nesse estudo. Amostras de sangue periférico foram coletadas para extração de DNA. Os SNPs foram analisados por PCR-RFLP. Em relação aos pacientes que apresentaram resposta completa (RC) ao tratamento (70%), 51% foram tratados com R-CHOP. Sobre o tratamento, 50% dos pacientes com RC apresentaram classificação de ECOG 0-1 (p=0,0193) e a maioria desses pacientes (41%) não apresentaram envolvimento extranodal (p=0,0377). Não houve associação entre os SNPs do CYP2B6, CYP3A5, GSTT1, NQO1 e MDR1 (C3435T) e as variáveis estudadas. Apenas CYP3A5 (sexo p=0,0519), GSTM1 (idade p=0,016; tratamento p=0,0372), GSTP1 (envolvimento extranodal p=0,0307), PON1 (sintomas B p=0,0201; Bulky p=0,0148) e MDR1 C1236T (sexo p=0,0316) mostraram associação. Em relação à sobrevida global, apenas tratamento (p=0,0129), IPI (p=0,000342), idade (p=0,0155), estadiamento (p=0,00281) e ECOG (p=0,00869) apresentaram resultados significantes. Quanto à sobrevida livre de doença (SLD), apenas idade (p=0,0292), estadiamento (p=0,0402) e ECOG (p=0,0142) apresentaram resultados significantes / To evaluated the influence of single nucleotide polymorphisms (SNPs) of CYP2B6, CYP3A5, GSTM1, GSTP1, GSTT1, PON1, NQO1 and MDR1 in the treatment response with R-CHOP and CHOP, 82 patients with Diffuse Large B-cell Lymphoma, without evidence of HIV infection, were enrolled in this study. Peripheral blood samples were collected for DNA extraction. The SNPs were analyzed by PCR-RFLP. In relation the patients that showed complete response (CR) to the treatment (70%), 51% were treated with R-CHOP. About the treatment, 50% of the patients with CR showed ECOG classification of 0-1 and the most of these patients (41%) did not showed extranodal involvement (p=0,0377). There was no association between CYP2B6, CYP3A5, GSTT1, NQO1 and MDR1 (C3435T) SNPs and the variables studied. Only CYP3A5 (gender p=0,0519), GSTM1 (age p=0,016; treatment p=0,0372), GSTP1 (extranodal involvement p=0,0307), PON1 (B symptoms p=0,0201; Bulky p=0,0148) e MDR1 C1236T (gender p=0,0316) showed association. In relation to overall survival, only treatment (p=0,0129), IPI (p=0,000342), age (p=0,0155), stadiament (p=0,00281) and ECOG (p=0,00869) showed significant results. To disease-free survival, only age (p=0,0292), stadiament (p=0,0402) e ECOG (p=0,0142) showed significant results