I am passionate about precision medicine and would like to see omics tools in the hands of clinicians, enabling them to better diagnose and treat patients. Precision medicine has the potential to enable us to be proactive about preventative health. We should be developing tools to detect disease early enough for treatment to be maximally effective. As a bioinformatician at Sengenics, I am responsible for developing software to enable our clients to analysis our array data themselves. Our i-Ome AI app, performs pre-processing, quality control and auto-antibody biomarkers identification. We're dedicated to ensuring our clients get the best quality data possible. Our auto-antibody arrays are at the cutting edge of precision medicine and we are constantly adding additions proteins to our arrays. Previously I was a post-doctoral researcher at the University of Cape Town and a freelance bioinformatician. I received a PhD from the University of Cape Town, describing the differences in the fate specifying signalling mechanisms between human neuroepithelial and foetal neural stem cells. The analysis required the functional annotation and integration of five omics datasets. This work was through collaboration with the Cambridge Stem Cell Institute and the Cambridge Centre for Proteomics. During my bachelors, I majored in Biochemistry, Physiology and Genetics, with additional elective courses in Calculus and Bioinformatics. I have since completed further Bioinformatics training from the National Bioinformatics Node in South Africa. In addition, I attended the Cold Spring Harbour Laboratories Proteomics Workshop and a summer school on High-performance computing at the Virginia Bioinformatics Institute.During my PhD was responsible for running the mass spectrometry facility in the Blackburn Lab. I developed tools to assess the system suitability of the instruments and for the processing and analysis of the data. I have co-authored 12 publications in the proteomics field, where I made significant contributions to data generation and analysis. I intend to use my experience in bioinformatics to make omics data more accessible. Most importantly for clinicians, enabling them to tailor personalised diagnoses and treatment of their patients. We can generate the data, interpreting it, and make it accessible is the next big challenge