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Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.
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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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Fraud in clinical trials in terms of ethics and law
Jedličková, Anetta ; Haškovcová, Helena (advisor) ; Prudký, Libor (referee) ; Strnadová, Věra (referee)
The subject of my dissertation is fraud in clinical trials in terms of ethics and law. The aim of my research was to analyze the frequency of fraud in clinical trials of a given sample of data collected, identify the main fraudsters and to analyze the causes that led participants in clinical trials to commit fraud. In the theoretical part of my dissertation I defined the concepts of clinical trials, deception, ethical issues and the relevant legal framework. The practical part contains the results of the data analysis of the incidence and causes of fraud, the main actors of fraud and conception of recommendations, which appears to be essential for the prevention of fraud in clinical trials. The data analysis and participant observation show that during 107 GCP (Good Glinical Practice) audits conducted during the period of 2008-2013 in 22 countries, 14 revelations of fraud in clinical trials were identified, which represents 13.1 %. Most often fraud was committed by investigators, a total of 47.6 % of all observed groups of cheating clinical trial participants. The main causes that led investigators to commit fraud represent a lack of eligible patients, financial gain and personality traits. Based on the results obtained during my research I highlighted in the practical part of my dissertation the ethical...
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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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Modern phytotherapy - revision of usage of medicinal plants according to clinical trials
Krupová, Olga ; Siatka, Tomáš (advisor) ; Kašparová, Marie (referee)
1 Abstract Charles University, Faculty of Pharmacy in Hradec Králové Department of Pharmacognosy Student: Olga Krupová Supervisor: PharmDr. Tomáš Siatka, CSc. Title of diploma thesis: Modern phytotherapy - revision of usage of medicinal plants according to clinical trials Key words: phytotherapy, medicinal plants, liver diseases, painful joints, nervousness and insomnia, clinical trials The aim of diploma thesis was to review the said effects of the herbs, to make a list of herbs used in popular traditional medicine of selected diseases and to verify their use by giving documented evidence. This thesis addresses in detail three ranges of problems in which the use of herbal therapy could be considered. Following three ranges of problems were selected: liver diseases, painful joints, nervousness and insomnia. Clinical studies were explored to substantiate the effects of individual herbs or their substances. Preclinical studies were used in case of deficiency in clinical studies. The outcome of this thesis was to approve or - on the contrary - to disapprove the effects quoted by the use of folk medicine herbs. From the result of this thesis it emerges, that not all popular quoted herbal indications are verified by sufficient evidence. However, for a considerable part of the quoted herbs their effects were...
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Clinical applications of stem cells for the treatment of neurodegenerative diseases of CNS
Jančová, Pavlína ; Kubinová, Šárka (advisor) ; Heřmánková, Barbora (referee)
Stem cells have a huge therapeutic potential due to their ability to differentiate in multiple tissues. They could be used for neurodegenerative diseases treatment, which are typical for loss of specific groups of neurons, progressive course and lack of effective treatment due to their complicated pathophysiology, only therapies for elongation and simplification of patients' life are available. This thesis summarizes results of completed clinical studies and informs about ongoing studies, in which stem cell treatments are used for selected neurodegenerative diseases. Stem cell therapy for multiple sclerosis and amyotrophic lateral sclerosis have a long history, some of the studies has proven therapeutic efficiency of stem cells. We don't know much about effect of stem cell treatment for patients with Alzheimer's and Parkinson's diseases, because first clinical studies were finished recently. But all clinical trials have proven safety of stem cell treatment. Replacement of damaged neurons haven't been reached yet, just protection of remaining neurons by neurotrophic and immunomodulatory factors secreted by stem cells. Keywords: neurodegenerative diseases, stem cells, clinical trials, multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, Parkinson's disease
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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.
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Cell surface CD47 expression in cancer stem cell-targeted tumor therapy
Kuzmík, Ján ; Drbal, Karel (advisor) ; Černý, Jan (referee)
CD47 is a transmembrane glycoprotein with a high expression in both, healthy and cancer (stem) cells. Level of the CD47 expression is negatively correlated with survival of cancer patients. Binding of CD47 to SIRPα, localized on a phagocyte, triggers intracellular signaling cascade. The final effect of this cascade is dephosphorylation of nonmuscle myosin-IIA, which disrupts its function and accumulation to phagocytic synapse. The blockage of CD47-SIRPα signaling pathway in a presence of the pro-phagocytic signal induces phagocytosis of cancer cells. Afterwards, phagocytes can serve as the antigen presenting cells and prime T cell response. Role of CD47-SIRPα signaling pathway in immunity has established this pathway as a target of cancer therapy testing. Preclinical research has identified a positive therapeutic effect of blocking this signaling pathway. Nowadays, the first phase of clinical trials is being conducted. The most prevalent approach of blocking CD47-SIRPα signaling pathway in therapy is the use of anti-CD47 blocking monoclonal antibodies, which cause mild anemia. However, alternative approaches of blocking this pathway are also being developed. In this bachelor thesis, I have summarized the research related to the blockage of CD47-SIRPα signaling pathway as a cancer therapy.
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