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Translational medicine is a new discipline, which covers studies on basic science, on human investigations, non-human investigations, and translational research (Mankoff et al. 2004). Basic science studies address the biological effects of medicines on human beings. Studies on humans discover the biology of disease and serve as foundation for developing therapies. Non-human or non-clinical studies advance therapies for clinical use or use in human disease. And translational research refers to appropriate product development for clinical use. Translational research looks into the identity, purity and potency of a drug product during early clinical trial (Mankoff et al.). Translating the knowledge derived from basic sciences into clinical research and treatments is the task of translational medicine (Nagappa 2006). There is a groaning need for this type of research on account of voluminous information in the information age. Using this information is the challenge encountered by scientists and healthcare providers everywhere in the world today. Clinical research disclosed this limitation in current clinical practice. The situation led to the development of the new discipline of translational medicine (Nagappa). Translational research connects basic research to its application in the clinical setting (Mariani, 2003). The clinical setting consists of the diagnosis and treatment or prevention of disease. It applies a discovery to practice. Edward Jenner is credited for the first clinical experiments in developing a smallpox vaccine in 1830 (Mariani).
A recent survey conducted by the Science Affairs Committee revealed that roughly 1,888 MD PhDs; 3,194 MDs; 5,703 PhDs; and 480 other qualified professionals or a total of more than 11,000 researchers are engaged in basic and clinical oncology research alone in the United States today (Mariani 2003). Developing new therapeutic strategies is lengthy. The research and development phase takes, on the average, 1-3 years; clinical trials phase, 2-10 years; and filings and approvals, 2 months to 3 years. On the whole, it takes 3-16 years to introduce new treatment into clinical practice in the United States (Mariani).
Teamwork is most important in every phase (Mariani 2003). This spans discovery, transfer to the clinic, evaluation of patient samples, rethinking of treatment and delivery. The team may be much more effective under the leadership of a scientifically trained and expert physician. This setup enables the right questions to raise the right questions while designing experimental standards. It will avoid dead-ends. Other factors, which enhance successful translational research, are the availability of mentors, time, rewards and sufficient resources. Factors, which deter or inhibit research success, include distractions from other official duties, the right funding, differences in knowledge among the researchers, technology transfers and strict schedule. Ultimate success, however, rests in high professional standards among those involved in the task. This is a problem at present in that there is a shortage of trained medical personnel in the United States and countries conducting such research. Physician scientists are particularly short of supply in the fields of radiology, pathology and surgery. They are those who can effectively communicate with clinicians. As it is, there is a wide gap between physicians who know the problems and the scientists who know the solutions. The chronic and global shortage of nurses aggravates the problem. The situation may be hinting at a lack of appropriate education and rewards to brilliant, high-performing professionals who observe high ethical standards. It may also be hinting at a lack of adequate resources and processes that will insure accurate and reliable assessments of new treatment strategies evolved (Mariani).
Translational Medicine and Drug Development
Translational medicine is that branch of medical research, which endeavors to directly connect basic research to patient care (Nagappa 2006). It translates basic research into real therapies for real patients. The bench-to-the-bedside concept links laboratory findings to the patient's bedside for treatment. Many pharmaceutical companies have formed groups that will facilitate the interaction. In the past, obstacles have stood between basic research and clinical practice of medicine. New drugs were developed apart of the clinic and then endorsed for safety-testing and the necessary clinical trials. Translational medicine aims at eliminating the gap and obstacles between them, hence the laboratory "bench-to-bedside" of the patient concept. It is a special diagnostics, which provides information on the prognosis and the patient on condition. It is non-invasive and will not cause discomfort in the course of diagnosis. Translational medicine is a technology, which meets these requirements. It identifies future and probable problems, which surface in the process of drug development and its use. It guides the processes of drug development (Nagappa). Theories evolved in the laboratory bench during pre-clinical experimentation are tested on sick subjects in bed. The results of the test are then taken back to the laboratory for the refining of biological principles on human disease already known (TCG 2008). Traditional medicine is a mix of basic science and clinical research aspects. This mix requires skills and resources traditionally different and separate. This is why research institutes, university science departments, clinics, hospitals and other similar entities cannot just accomplish traditional medicine. Organizations or entities, which possess these resources, encounter internal, political and organizational impediments in integrating the functions and departments. Traditional medicine can operate effectively only in places where experts work together and share information (TCG).
This covers the fields of bioinformatics, medical imaging, health informatics, and related disciplines (Landers 2010). It began as a scientific discipline in the early 1970s. It peaked in recent years on account of public access to huge data from the Human Genome Project and other research initiatives. The merger of the different branches of biology with information technology and knowledge has allowed researchers and clinicians access to information to advance biological research and healthcare. The integration led to unprecedented breakthroughs in the healthcare and pharmaceutical fields. Activities, such as modeling, identifying DNA sequences, the analysis of protein structures, and data management, can now be performed with minimal effort and amazing speed. Researchers can now acquire massive information and understanding of the human organism and its environment with ease. Data and knowledge covers the entire gamut of molecular exchanges, cell communication, personal genotypes and group populations (Landers).
The best place for biomedical informatics at present appears to be in personalized medical care (Landers 2010). In this field, biomedical information technology can use existing traditional health data in the person's medical records, individual phenotype information and other sources for improved healthcare delivery. Clinicians may also use all the information in detecting developing diseases in early stages. Advancements in biomedical informatics will also enable healthcare professionals to conduct clearer and more sophisticated medical assessments. These assessments can be sent speedily to patients and their healthcare providers. Other close possibilities include breakthroughs in diagnostic and remedial techniques, which will not only improve the healthcare system but also the effectiveness and efficiencies of the industry itself. Proponents of biomedical informatics foresee further consolidation and development for this branch of science. Sustained study and comprehension of vast amount of data are one way. Other possibilities are the creation of innovative algorithms, specialized software, and more automated processes. It can improve personalized medical services and reduce costs through a commitment of the entire healthcare industry. The industry can make wide and effective use of the data, knowledge and computing systems made available by the technology (Landers).
Biomedical informatics or BI is a set of methodologies that can cross the barriers confronted by translational medicine (Sarkar 2010). Its fundamental aspects are bioinformatics, imaging informatics, clinical informatics, and public health informatics. With these aspects, BI has essentially improved and facilitated in bringing lab findings to the bedside, evaluate the effectiveness of current interventions, and help assess the impact of translational medicine innovations on health policies. BI and translational medicine together can accrue to better patient care through better clinical interventions and treatments and more informed policies and clinical guidelines (Sarkar).
Traditional medicine ultimately aims at developing new treatments and insights into improving the health of populations (Sarkar 2010). The three steps in the process are the identification of appropriate interventions; directed evaluation of the efficacy of these interventions; and the identification of how to appropriately facilitated and applied to an entire population. Current translational barriers exist in translating or converting innovations from bench-based experiments to clinical validation in bedside clinical trials. These ultimately lead to adoption of communities and the creation of policies. Crossing or overcoming these barriers may be enabled by a combination of present and oncoming biomedical informatics strategies and tools. An important feature of the intervention is a trans-disciplinary team. This team will integrate relevant lab findings in identifying breakthroughs in research and clinical interventions, including drug development. BI professionals, also called biomedical informaticians, will be an essential member of the translational medicine team. They will be experts in effective translating concepts and sharing these with other experts in the team (Sarkar).
Translational bioinformatics and clinical research informatics are both fundamentally knowledge-centered (Sarkar 2010). Both are attuned to meet the vast requirements of research and information of basic science, clinical and public health researchers. The development of knowledge management infrastructures…[continue]
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