Data & Intelligence June 18, 2020
How data and technology are changing the healthcare landscape
The healthcare and biotech industry is one of the world’s largest and fastest-growing industries. And like most sectors, it is being driven by digital transformation. This isn’t surprising given that the healthcare industry is often at the forefront of technological breakthroughs. Digital transformation is often enabled by the evolution of data and technology. So how will these aspects shape the future of healthcare? This question is best answered using Goldfinch Bio and Foundation Medicine, two medical research companies, as examples.
Data can further medical research and patient care
Biotech and healthcare companies around the world are conducting critical research to discover new therapies and treatments for a variety of diseases, which is even more important in the midst of a global pandemic. They are able to conduct this critical research thanks to the massive influx of data available to them, ranging from in-depth patient data, genetic studies, and clinical trial data.
Goldfinch Bio is one of those companies, focusing on discovering and delivering precision therapies for patients with kidney disease. Like many companies, Goldfinch Bio receives an influx of data that comes from varying sources which then needs to be analyzed, curated, and shared in order to inform clinical trials. The company then translates these discoveries into new therapies that target the molecular causes of kidney diseases and, in doing so, helps create new, innovative treatment options for patients.
Goldfinch has been collecting samples from affected patients, sequencing them, and enrolling them into a Kidney Genome Atlas (KGA) to try to build a data set large enough that the company can use statistical methods to identify potential drug targets with genetic evidence.
Together with Dept, we built a dynamic web-based application that allowed them to surface all of the data they were collecting and producing as part of the KGA to help optimize target identification, patient stratification, and the exploration of the relationship between genotype and phenotype. In short, the application allows their researchers to simplify their complex workflows and create efficient data visualizations which enables them to do better work, faster.
Additionally, Foundation Medicine, a world-renowned molecular insights company that focuses on genomic research, had a mountain of data at its disposal but no tools for researchers and pharmaceutical companies to make sense of it quickly. So Dept created a custom software platform that allows researchers to efficiently query the company’s wealth of data, as well as allow medical professionals to input clinical outcomes. This has led to researchers being able to track genomic abnormalities and how specific target therapies affected those abnormalities.
These are two examples that demonstrate how making data accessible but also easy to manipulate is necessary to enable medical advancements.
Looking towards the future, as the healthcare industry turns away from traditional treatment post-diagnosis towards prevention and early intervention, data becomes of crucial importance. Right now, healthcare systems often see fleeting snapshots of an individual’s life which are not connected to each other. However, by combining existing and new data collection, the medical field’s predictive capabilities will drastically increase. For example, devices like FitBit or Apple Watch could, in the near future, send personal information of our choice to our physicians so they can better monitor our overall health, give us lifestyle recommendations based on our individual needs, and alert us when our health appears to be declining. Ultimately, any data you choose to share can be transformed into actionable insights for both yourself and society at large.
Technology enables digital transformation
To support the complex infrastructure described above, having the right technology stack is a key requirement. Numerous biotech and pharmaceutical companies have tens of thousands of samples in addition to patient information and clinical history. So these companies need to have the infrastructure which not only stores but also shares the information with other databases when needed.
For example, for Goldfinch Bio, our team has built three distinct environments for development, staging, and production of the overall application. To make this reality, a simple storage service (Amazon S3) talks to an API that is built on a mostly serverless stack in AWS. Backing the API is an event-driven pipeline that produces everything the app needs on-demand. Therefore, this means that when someone uploads a new study from the app, the pipeline is kicked off. The data presented to users is derived from petabytes of raw data. This data is processed, refined, and distilled to a much smaller, more manageable data set. This data is supplemented, enriched, and annotated with public data to try to give the end-users everything they need to better understand the genetic drivers of kidney disease and identify potential new drug targets that will help these patients that so desperately need new treatments. In short, this enabled the company’s various researchers to work in a more efficient manner while unearthing important patterns that will inform further research.
By having the right tech stack in place, researchers can easier organize and make sense of the data they have at hand. So, when choosing a platform or software system, keep in mind your unique needs and specific business goals. Your company should also consider cost, performance requirements, and available resources. With this in mind, there are currently numerous architectural options on the market which are capable of handling large amounts of data. For instance, AWS and Microsoft Azure are cloud-based choices that frequently add new service offerings to make the implementation process easier. Regardless of your choice, platforms are and will continue to be the key foundation upon which future collaboration, tracking, and continuous improvement are built.
Accelerating the healthcare industry
Going forward, the ability to evaluate large amounts of data, automate processes with technology, and ultimately speed up one’s workflow is crucial to advance medical research and patient care. The power of data will continue to advance patient care for critical diseases, and powerful digital platforms and applications will be essential to further enhance this process. Though transformation does not happen overnight, it will help the healthcare sector deliver on its short-term needs while accelerating its long-term goals to significantly improve patient care.