Read paragraphs and then answer the question below.

Efforts to personalize medicine in oncology have been limited by reductive characterizations of the intrinsically complex underlying biological phenomena. According to (Ma Stingo & Hobbs, 2016). Future advances in personalized medicine will rely on molecular signatures that derive from synthesis of multifarious interdependent molecular quantities requiring robust quantitative methods. However, highly parameterize statistical models when applied in these settings often require a prohibitively large database and are sensitive to proper characterizations of the treatment-by-co variate interactions, which in practice are difficult to specify and may be limited by generalized linear models. Cancer is a complex, dynamic micro evolutionary process. It was the cause of more than 580 thousand deaths in the U.S. alone in 2013 and has remained the second leading cause of death for more than half a century. Effective treatment requires an understanding of the alterations within cell signaling pathways that enable cancer cells to evade routine cell death and to proliferate and migrate. The study of individual candidate genes, signaling pathways, behaviors, or environmental exposures in lieu of better approximations of the intrinsically complex biological phenomena has limited our understanding of many areas of oncology. For example, after nearly two decades of biomarker investigations in colorectal cancer, only one biomarker has been sufficiently validated to warrant its inclusion in clinical practice: KRAS gene mutations that are predictive of resistance to anti-EGFR therapy in metastatic disease.

The genomics revolution has generated an unprecedented number of assets to propel innovation. According to (Jimenez-Sanchez & Scoles 2015), initial availability of genomics-based applications shows a significant potential to contribute addressing global challenges, such as human health, food security, alternative sources of energies, and environmental sustainability. In the last years, most developed and emerging nations have established bioeconomy agendas where genomics plays a major role to meet their local needs. Genomic medicine is one of the most visible areas where genomics innovation is likely to contribute to a more individualized, predictive, and preventive medical practice. The genomic revolution driven by the Human Genome Project has significantly advanced our knowledge of the biology on living organisms. The widespread access to genomic technologies and information resources is transforming multiple fields very quickly, introducing an emerging generation of innovations that offer new opportunities and challenges to contemporary societies.

Physicians are increasingly working with genomic big data in their research and clinical work. According to (Chow-White & Laskin 2017), physicians have begun to adopt genomic data and technologies into clinical practice, and single gene tests have become integrated into the standard of care for the treatment of some specific cancer types. Like many big data technologies, discovery takes time and translation from scientists to doctors is typically incremental. One of the main challenges is a lack of familiarity and understanding of cancer genomics among healthcare professionals. Physicians often report their level of genomic knowledge is inadequate in order to make treatment decisions based on a patients genome sequencing information. Despite limited genomic knowledge, physicians express a positive attitude toward increasing their genomic knowledge, and a desire to adopt genomics into their practices. This is an early stage of adoption as genomics moves from scientist stakeholders to medical practitioners and the public. Put another way, genomics is moving from the research bench to the clinical bedside. It is critical to update our understanding of doctors perspectives and experiences during the adoption process. This knowledge can be fed back to clinical trial researchers to help develop clinical genomic technologies. The purpose of this study was to understand doctors genomic literacy and help direct pedagogy for medical students and practicing doctors.

1. Why is collaboration between physicians and health systems important in developing innovative and cost-effective processes of care for predictive genomics? Provide an example of a potential new business line. Is this the trend in the future of healthcare delivery?