Gradientech AB is a company that develops a new ultra-rapid system for antibiotic susceptibility testing and their product will hopefully be used in health care for more efficient diagnosis of sepsis. Today the product has difficulties with the analysis of polymicrobial tests. For our project, the task is therefore to examine the market and the demand for the ability to detect polymicrobial infections. Our project is meant to provide ideas for improvements on their current method for the feasibility to detect several types of bacteria in the same test. Through literature studies, we have received an overview of how optical methods using image analysis can work and how they could be implemented in Gradientech's product. Image analysis can make the identification of bacteria possible. Interesting objects in the image can be distinguished from each other with filters that handle, for example, size, shape and light intensity. A potential improvement in the classification of bacteria by optical methods may be to test several different angles and wavelengths. This is to get more training data for machine learning and thus more accurately detect and analyze samples. The results from literature studies and interviews with clinicians, a microbiologist, and professor in image analysis have led to a conclusion that techniques that contribute to a decrease of antimicrobial resistance will be crucial for the future. In Sweden, the development of resistant bacteria is pretty low, but in many other parts of the world, there is a different reality. The product’s greatest potential will probably be in countries with a high incidence of resistant bacteria and with educated personnel available to use the product. Ultra-rapid systems for AST can contribute to saving lives by making sure that the right type of antibiotics is given directly. Detection and identification of polymicrobial samples in sepsis are also relevant, but it will not contribute to reduced antibiotic use since the patient's health will always be prioritized as of now. Finally, we reached the conclusion that identification of polymicrobial tests is not a necessary feature for the success of the product. This is above all due to the mass spectrometry method MALDI-TOF, a technique that is already well-established in health care systems. It can quickly and cheaply identify bacteria in clinical samples.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-384703 |
| Date | January 2019 |
| Creators | Jansson, Linnéa, Johnson, Gustav, Wallskog, Amanda, Svalberg, Linn, Svärd, Karl, Engström Kindmark, Hedvig, Dost, Maryam |
| Publisher | Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala universitet, Institutionen för biologisk grundutbildning |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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