Big Data is helping to bring the vision of Precision Medicine to life
What is Big Data?
Big Data is all around us. We generate over 2.5 quintillion bytes of it every day. In fact, we have managed to create about 90% of the world’s total data reserve in just two years.
So what makes Big Data so special, and why should you care? Continue reading to find out how Big Data is revolutionizing various fields, especially healthcare.
According to the McKinsey Global Institute, Big Data refers to datasets whose size are beyond the ability of typical database software tools to capture, store, manage, and analyze. The term “big” may however be misleading since while some datasets are huge, others tend to only be complex.
The analysis of Big Data is used to reveal trends and associations, especially relating to human behavior and interactions. In recent times, the term has evolved with our increased ability to capture and process it. This has led to its growing application in various industries, such as healthcare, where it is being used to drive the discovery and development of precision medicines.
Discussions around Big Data’s definition have resulted in the conclusion that ‘Big’ is no longer a defining parameter of the term, but rather how ‘smart’ the data is. This smartness focuses on the insights that the volume of data can reasonably provide, an aspect that has become fundamental in the health sector.
In 2016, a specific definition of Big Data in health research was proposed by the Health Directorate of the Directorate-General for Research and Innovation of the European Commission.
It states that:
“Big Data in health encompasses high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.”
For example, by diving into insights such as medication type, symptoms, and the frequency of medical visits, and so on, it’s possible for healthcare institutions to provide accurate preventative care, and ultimately, reduce hospital admissions. This level of risk calculation not only results in reduced spending on in-house patient care, but also ensures that resources are available for those who need it most.
Application in Precision Medicine
As an emerging field in healthcare, precision medicine aims to provide personalized care based on a person’s unique genetic composition. This relies largely on the ability to detect patterns and turn high volumes of data into actionable knowledge for precision medicine and decision makers such as healthcare personnel.
The process of Big Data analysis involves combining different types of information, which are electronically captured such as those from electronic healthcare records, genomic and pharmaceutical data, and many more.
These data have the potential to be analyzed and used in real-time to prompt changes in behaviors that can reduce health risks, reduce harmful environmental exposures or optimize health outcomes. They can also be mined to gather patterns, for example, genetic variants shared across individuals with a similar disease, which in turn can point towards possible therapeutic targets.
Currently, data derived through genomic sequencing also plays a critical role in advancing precision medicine by uncovering hidden patterns and unknown correlations that would otherwise be difficult to detect using traditional methods of data analysis.
These derived patterns, such as those associated with disease risk factors, the development of new diagnostic tests, or creation of personalized treatments and therapies ultimately help to improve patient treatment outcomes, reduce treatment cost and increase healthcare efficiency.
Application in Genomics Research
Precision medicine or genomic medicine uses information about genetics and genomics to provide an accurate path to medical care for individuals. As such, precision medicine is made possible primarily by Big Data, which provides the necessary information, down to the most minute detail, to make well-informed decisions about an individual’s health.
Years ago, sequencing a single genome took weeks and cost tens of thousands of dollars, and it was simply not feasible to sequence more than a handful of genomes.
Now, with the advent of next-generation sequencing technologies, it is possible to sequence an entire human genome in just a few hours at a fraction of the cost. The sheer volume of data generated by this process has created the need for new data-management and analysis techniques. Here is where Big Data and large scale analytics comes in – its analytical power provides efficient ways to handle and make sense of these large amounts of data.
Application in Drug Discovery
Currently, the process of drug discovery is long, expensive, and inefficient, with a success rate of less than 0.01% as a result of the high failure rates of clinical trials. Big Data is playing a critical role in speeding up this process by helping researchers to identify new genetic markers with increasing confidence and better understand the role of genetics in disease.
For example, with the aid of whole-genome sequencing to cover larger portions of the genome, and larger cohorts which help in improving the power to detect variants of interest, we are able to build large genomic datasets which aid our understanding of disease mechanisms.
By analyzing large datasets, Big Data has the potential to identify possible drug targets, and assess the safety and efficacy of new drugs before they are even tested in humans. This would allow for the elimination of many early-stage drug candidates, saving both time and money, and also to identify individuals that may not respond favorably to certain therapies (adverse drug reactions).
Application in Diagnostics
Big Data is helping to improve diagnostics by providing a more accurate and complete picture of patient health status. This is possible because Big Data captures all the available information, including interactions between different data types. By integrating data from contrasting sources, Big Data can provide healthcare providers with a more holistic view of the patient, and lead to more accurate diagnoses, personalized clinical decisions and ultimately better treatment outcomes.
Potential in African Healthcare
The potential for Big Data in healthcare is limitless, and its application will no doubt have a profound impact on healthcare in Africa. With the ever-growing prevalence of chronic and life-threatening conditions such as cancer, heart disease, and diabetes, Big Data has the potential to play a critical role in improving patient outcomes and reducing the cost of care by personalizing care.
Big Data can also contribute to patient care in Africa by providing healthcare practitioners with relevant information needed to make better-informed decisions about treatment and prevention. Additionally, Big Data may just be the catalyst needed to help Africa leapfrog traditional healthcare systems and as a result, improve access to care for millions of people.
How 54gene uses Big Data
Early last year, we partnered with Illumina to create our world-class genomics facility in Lagos, Nigeria. We also established two integral departments – Genomics & Data Science, and Drug Discovery, to help us drive novel target discovery in Africa.
Both arms, together with our Molecular Genomics and Biobank Operations department, have begun human whole-genome sequencing and genotyping efforts with the aim of uncovering novel genetic variants in the African population that can be influential in global drug discovery and development efforts.
With viable genomic research contributions from the African population being considered in both processes, there will be an increasing development of more efficacious treatments, diagnostics and therapies well-tailored to people of African descent.
The benefits of Big Data in precision medicine are vast and continue to grow every day. By harnessing the power of Big Data, we can improve our ability to treat diseases and provide patients with the best possible care.
In Africa, where dependable data is often scarce, the era of Big Data could be used to improve healthcare outcomes by providing insights into disease trends and treatment efficacy. Big data has the potential to revolutionize healthcare in Africa as we know it, and we have to be prepared for it.
Lastly, nowhere is the term “Big data” more suitable than in the analysis of “Big genomes”. The typical African genome is significantly richer in variation and information than genomes from most other human populations. This will add to the discovery potential of Big Data and how it can be leveraged to inform on disease susceptibility and to drive target insights that will ultimately benefit both African and global populations.