Genetic Medicine Essay

1521 Words4 Pages

Dr. Jon Schiller describes genetic medicine as the newer term for medical genetics and incorporates areas such as gene therapy, personalised medicine and a new emerging speciality, predictive medicine. Medical genetics is the specialty of medicine that involves the diagnosis and management of hereditary disorders (Dr. Jon Schiller, 2010). We have reached the forefront where systems biology and the digital revolution are together transforming healthcare to a proactive P4 medicine that is predictive, preventive, personalized and participatory (Hood and Flores 2012). P4 medicine is a plan that utilizes biotechnology to radically improve the quality of human life. It is a term coined by biologist Leroy Hood and states that medical practise will be revolutionised to manage a person's health, instead of managing a patients disease.(email p4 medicine) Ciftci and Trovitch in 2000 described how a mutation in just one gene will cause irregular cell behaviour thus leading to a dysfunctional protein (Ciftci and Trovitch 2000). It is the purpose of genetic medicine to rectify such genetic disorders by delivering the correct gene version (Ciftci and Trovitch 2000) such as gene therapy or deliver optimized therapeutic care to the patient (Crommelin et al. 2011) as in personalized medicine. The scope that encompasses genetic medicine is broad, including multiple areas, such as genetic counselling, clinical physicians, nutritionists, clinical diagnostic laboratory activities and research into the inheritance and causes of genetic disorders. This wide scope therefore includes conditions such as birth defects, mental retardation, cancer, skeletal dysplasia, autism and connective tissue disorders (Dr. Jon Schiller, 2010). It is my goal i... ... middle of paper ... ...1.3. Predictive Medicine Currently present are non invasive computational modelling techniques, these are very informative and display results with high levels of accuracy but they do have some drawbacks. It requires a long and dreary approach of formulating math equations which must then be followed by substantial computational efforts. Besides that, model preparations also involve time consuming efforts. In order to minimize computational run-time, certain assumptions have to be made in order to simplify the governing equations and hence expose a certain uncertainty in the results generated. It has reached the day and age where accurate and real time prediction tools are needed in modern clinics and hospitals. To utilize predictive medicine it is important to use the right trends of data mining methodologies to get accurate results (Paramasivam et al. 2014).

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