@phdthesis{Zeeshan2012,
  author    = {Zeeshan, Ahmed},
  title     = {Bioinformatics Software for Metabolic and Health Care Data Management},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-73926},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Computer Science approaches (software, database, management systems) are powerful tools to boost research. Here they are applied to metabolic modelling in infections as well as health care management. Starting from a comparative analysis this thesis shows own steps and examples towards improvement in metabolic modelling software and health data management. In section 2, new experimental data on metabolites and enzymes induce high interest in metabolic modelling including metabolic flux calculations. Data analysis of metabolites, calculation of metabolic fluxes, pathways and their condition-specific strengths is now possible by an advantageous combination of specific software. How can available software for metabolic modelling be improved from a computational point of view? A number of available and well established software solutions are first discussed individually. This includes information on software origin, capabilities, development and used methodology. Performance information is obtained for the compared software using provided example data sets. A feature based comparison shows limitations and advantages of the compared software for specific tasks in metabolic modeling. Often found limitations include third party software dependence, no comprehensive database management and no standard format for data input and output. Graphical visualization can be improved for complex data visualization and at the web based graphical interface. Other areas for development are platform independency, product line architecture, data standardization, open source movement and new methodologies. The comparison shows clearly space for further software application development including steps towards an optimal user friendly graphical user interface, platform independence, database management system and third party independence especially in the case of desktop applications. The found limitations are not limited to the software compared and are of course also actively tackled in some of the most recent developments. Other improvements should aim at generality and standard data input formats, improved visualization of not only the input data set but also analyzed results. We hope, with the implementation of these suggestions, metabolic software applications will become more professional, cheap, reliable and attractive for the user. Nevertheless, keeping these inherent limitations in mind, we are confident that the tools compared can be recommended for metabolic modeling for instance to model metabolic fluxes in bacteria or metabolic data analysis and studies in infection biology. ...},
  subject      = {Stoffwechsel},
  language  = {en}
}
@phdthesis{Lauton2021,
  author    = {Lauton, Felix},
  title     = {Three Essays on the Procurement of Essential Medicines in Developing Countries},
  doi       = {10.25972/OPUS-22063},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220631},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {The first problem is that of the optimal volume allocation in procurement. The choice of this problem was motivated by a study whose objective was to support decision-making at two procurement organizations for the procurement of Depot Medroxyprogesterone Acetate (DMPA), an injectable contraceptive. At the time of this study, only one supplier that had undergone the costly and lengthy process of WHO pre-qualification was available to these organizations. However, a new entrant supplier was expected to receive WHO qualification within the next year, thus becoming a viable second source for DMPA procurement. When deciding how to allocate the procurement volume between the two suppliers, the buyers had to consider the impact on price as well as risk. Higher allocations to one supplier yield lower prices but expose a buyer to higher supply risks, while an even allocation will result in lower supply risk but also reduce competitive pressure, resulting in higher prices. Our research investigates this single- versus dual-sourcing problem and quantifies in one model the impact of the procurement volume on competition and risk. To support decision-makers, we develop a mathematical framework that accounts for the characteristics of donor-funded global health markets and models the effects of an entrant on purchasing costs and supply risks. Our in-depth analysis provides insights into how the optimal allocation decision is affected by various parameters and explores the trade-off between competition and supply risk. For example, we find that, even if the entrant supplier introduces longer leads times and a higher default risk, the buyer still benefits from dual sourcing. However, these risk-diversification benefits depend heavily on the entrant's in-country registration: If the buyer can ship the entrant's product to only a selected number of countries, the buyer does not benefit from dual sourcing as much as it would if entrant's product could be shipped to all supplied countries. We show that the buyer should be interested in qualifying the entrant's product in countries with high demand first. In the second problem we explore a new tendering mechanism called the postponement tender, which can be useful when buyers in the global health industry want to contract new generics suppliers with uncertain product quality. The mechanism allows a buyer to postpone part of the procurement volume's allocation so the buyer can learn about the unknown quality before allocating the remaining volume to the best supplier in terms of both price and quality. We develop a mathematical model to capture the decision-maker's trade-offs in setting the right split between the initial volume and the postponed volume. Our analysis shows that a buyer can benefit from this mechanism more than it can from a single-sourcing format, as it can decrease the risk of receiving poor quality (in terms of product quality and logistics performance) and even increase competitive pressure between the suppliers, thereby lowering the purchasing costs. By considering market parameters like the buyer's size, the suppliers' value (difference between quality and cost), quality uncertainty, and minimum order volumes, we derive optimal sourcing strategies for various market structures and explore how competition is affected by the buyer's learning about the suppliers' quality through the initial volume. The third problem considers the repeated procurement problem of pharmacies in Kenya that have multi-product inventories. Coordinating orders allows pharmacies to achieve lower procurement prices by using the quantity discounts manufacturers offer and sharing fixed ordering costs, such as logistics costs. However, coordinating and optimizing orders for multiple products is complex and costly. To solve the coordinated procurement problem, also known as the Joint Replenishment Problem (JRP) with quantity discounts, a novel, data-driven inventory policy using sample-average approximation is proposed. The inventory policy is developed based on renewal theory and is evaluated using real-world sales data from Kenyan pharmacies. Multiple benchmarks are used to evaluate the performance of the approach. First, it is compared to the theoretically optimal policy --- that is, a dynamic-programming policy --- in the single-product setting without quantity discounts to show that the proposed policy results in comparable inventory costs. Second, the policy is evaluated for the original multi-product setting with quantity discounts and compared to ex-post optimal costs. The evaluation shows that the policy's performance in the multi-product setting is similar to its performance in the single-product setting (with respect to ex-post optimal costs), suggesting that the proposed policy offers a promising, data-driven solution to these types of multi-product inventory problems.},
  subject      = {Entwicklungsl{\"a}nder},
  language  = {en}
}