Shaping healthcare’s future with genomic data
The knowledge management rigors associated with computational molecular biology and one of its most promising manifestations, genomic sequencing, are formidable. Managing genetic data involves:
- integrating myriad databases—Hundreds of databases detailing the virtually endless varieties of genetic data abound in the public and private sectors. Clinicians and researchers alike are tasked with integrating and aggregating relevant information for their own specific use cases.
- accounting for unstructured text analytics—According to Lawrence Hunter, director of the Center for Computational Biology and the Computational Bioscience Program at the University of Colorado School of Medicine, there are “millions of peer-reviewed papers each year” directly informing clinical and research efforts in molecular biology. The data aggrandizes the quantity of data sources involved, adding to the overall complexity.
- parsing through patient records—Considered one of the principal sources of genetic data applications, patient records require daily updating with any variety of techniques before cross-referencing them with other sources. According to Hunter, the University of Colorado has an entire research warehouse encompassing such records and other pertinent data.
- the evolving nature of biology—Computational molecular biology is very much a work in progress. New discoveries, connotations, implications and contradictions emerge almost daily, requiring a flexibility of classifications exceeding that of other disciplines.
“Biology might have some of the biggest big data, if not in absolute count—there’s probably more phone calls in the world than there is knowledge of biology—but in the semantic richness of it,” Hunter acknowledged. “The relationships among the entities are very complicated.”
Those complex relationships are the basis for some of the most indispensable applications of big data in contemporary healthcare. Genomic sequencing is primarily used in three fundamental ways, including:
- determining hereditary risk factors for disease—Genetic information is one of the telltale markers of predispositions toward harmful hereditary healthcare conditions such as cancer.
- detecting rare diseases—Genome sequencing is particularly useful for diagnosing diseases that are otherwise too anomalous to detect. Because of the rarity of those conditions, it’s difficult for many healthcare practitioners to recognize their symptoms.
- developing effective pharmaceuticals—Genome sequencing affects the development of pharmaceuticals in two ways. It’s used to personalize drug treatment options for patients and to “analyze specific illnesses to then tailor-make a drug” for treatment, said Waqaas Al-Siddiq, CEO of Biotricity. Moreover, pharmaceuticals based on genomic data can target specific mechanisms for mutations that are common across diseases to affect a wider scope of patients. Kathy Reinold, AstraZeneca life sciences project manager, said, “Recently the FDA approved, I believe, it’s first drug that was not focused on a specific disease but rather on a mechanism of action, which is very promising for patients. Instead of a serial process of [a drug] being tested in clinical trials on multiple diseases [or] multiple types of cancer, we are maybe in a position to start treating it across lots of different cancers based on that specific mutation.”
Personalization is the common theme for each of those use cases, which quite possibly represents the future objective of healthcare services. The future is directly influenced by the past hereditary information contained in genetic data.
The growing relevance of genetic data in the modern healthcare landscape is attributed to multiple factors, the most prominent of which is likely cost. Prices for genome sequencing have been greatly reduced in the past two decades, making genetic information much more accessible than it previously was. Genomes are “all of your genes combined,” Hunter noted. “They’re the whole complement of your DNA.”
According to Hunter, the first instance of human genome sequencing took place in 2000 for approximately $10 million. “Sequencing has gotten really cheap,” Hunter added, referring to the cost today. “It is now practical. A whole human genome is roughly $1,000, depending on what kind of clinical volume you’re doing.”