In a blog post this week, Ralf Huss, chief medical officer of Definiens, a tissue-based-diagnostics company, identified the promise of Big Data for precision medicine, especially in the field of oncology; the importance of data reduction to make Big Data usable; and the need for oncologists to get comfortable with data in general so that using it becomes an integral part of their discipline.
First, the author explains that while the genomics process doesn’t paint a complete picture of “cancer behaviours and identify vital biomarkers that help determine what types of treatments patients will respond to,” he maintains high hopes for Big Data’s potential to address this, and notes that oncology-field stakeholders are now incentivising hospitals and researchers to administer effective treatments yielded from Big Data analysis.
Next, Huss explains that, to zero in on the factors that “are most vital for achieving desired outcomes,” data reduction is critical, as it converts incomprehensible “patterns and formats in order to diagnose and develop personalised treatments for patients.”
After that, the author calls on the healthcare sector “to reevaluate the required education for oncologists in this era of Big Data-based innovation” so that they can use data to make spontaneous decisions and treat their patients both quickly and accurately.
In his conclusion, Huss reiterates the importance of data reduction and lauds the federal government’s Precision Medicine Initiative as an effort that promises to effectively capitalise on Big Data’s promise by “strapping it down to develop individualised treatments as we continue to see the ‘one size fits all’ method be ineffective.”
Read the full article here.
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