By most accounts, a slow approval process, miles of red tape and administrative hurdles are the chief obstacles in getting new medicines moved through the drug development process and into the market.
Certainly the extremely meticulous testing, trails and data required are vital to patient safety, and no one would argue this should be the top priority.
However, behind the scenes, one of the largest hurdles that significantly inflates both the time and cost of bringing new drugs to market could be solved with better data management.
The Data Dilemma
Expedient drug development and delivery depends on researchers having access to accurate, reliable data at scale. Yet, efficient data management remains a significant challenge for pharmaceutical companies in orchestrating expeditious, yet thorough and scientifically sound, clinical trials. One key problem for drug manufacturers is accessing and integrating the important patient data they need cleanly, quickly and reliably to gain actionable insight.
The widespread adoption of EMR systems among providers has created a tremendously valuable data repository that could help pharma companies better understand patient populations. In addition, the growing use of fitness trackers, online health systems and health-related mobile apps, by which consumers now willingly share their own data for tracking, trend monitoring and intelligence gathering, could give pharma researchers unprecedented visibility into this often mysterious side of the equation.
But, greater amounts of data from an increasing number of applications and sources means that even more work is needed to integrate the data and make it useful. Each source and application has its own proprietary system for collecting, storing and visualizing the data. This makes integration a challenge and often results in data silos and "dirty" or duplicate data
Expanded over thousands of individuals at potentially hundreds of sites, the data dilemma explodes on a massive scale. Instead of focusing on developing new formulations, highly skilled—and highly compensated— Pharma researchers often become data janitors, forced to spend the vast majority of their time preparing and cleansing their data for analysis. Complex integration is required to break down the data silos and harmonize the data. This takes a tremendous amount of time and costs a fortune, which adds significantly to the expense and time required to bring new drugs to market. In turn, it contributes to the rising costs of drugs for consumers.
The dPaaS Rx
Pharma is certainly not alone in the Big Data dilemma. The volume, variety and velocity of data available to every industry today makes it more difficult for most companies to effectively integrate and use data for greater insights.
Fortunately, a new method of integrating and managing data—including health care information-- is helping pharma companies expedite time to market and reduce the cost of developing and introducing new drug therapies.
Data Platform as a Service, or dPaaS, is a new unified, cloud-based approach that enables pharma companies to put data at the center of integration efforts. The solution supports end-to-end integration and data management workflows on a single, multi-tenant cloud platform.
dPaaS is the only platform to offer integration as a fully managed service while giving organizations full access and control at the data layer. With this approach, pharma companies are freed from the time/resource- intensive work of integrating data sources and are assured of sound data governance and utmost data quality. Drug manufacturers are also empowered to spend the maximum amount of time on gaining quality insights faster from the data that traverses their enterprises and is now available to them through the healthcare ecosystem and marketplace. In addition, pharma companies also gain full visibility into their data lineage with dPaaS.
Because dPaaS focuses on integrating and managing data at the data level, independent of the application, the platform enables drug manufacturers to integrate, harmonize and aggregate data from virtually any source, without the need for highly skilled data scientists, nor their pharma researchers, to spend valuable time in cleansing and preparing data for analysis. And, because dPaaS operates in the cloud, pharma companies benefit from virtually unlimited scale and flexibility for data analysis and investigation.
Maximum Relief, No Negative Side Effects
Unlike conventional data systems that segregate integration and data management into two separate functions, dPaaS's holistic, unified approach marries the two into a seamless data-centric system that eases and accelerates data handling from aggregation to insight significantly.
With conventional systems, bringing in data from new sources or adding new visualization tools requires the manual programming of each integration, typically by a team of people at both the pharma company and the trial site—a provider or hospital. This manual effort is not only a tremendous drain on resources across the board, but also typically requires each project to start from scratch, because no two are exactly the same.
dPaaS streamlines the process, providing a tight relationship between the integration and management of data that can scale rapidly as the volume, velocity and number of data sources increases. Unlike self-service solutions that require researchers to methodically chip away at data silos, dPaaS provides a data-driven foundation that integrates and syncs with any application, storage method and security protocol.
Because of dPaaS's holistic focus on integration and data management, drug developers can overcome data management hurdles with exceptional efficiency and scale, shepherding their new formulations into the approval process faster, more economically and with the confidence of more accurate, sound data.
In short, dPaaS enables scientists to be scientists, not data janitors, shortening the drug development lifecycle and simplifying the process of clinical trial design, development and deployment. With the power, flexibility and scale to tap into the insights now available from EMR and consumer-supplied health data, Pharma experts can now more efficiently identify new patient populations for trials, refine study parameters and better understand the patient-side impact, efficacy and compliance of drugs once they hit the market.
The result? Both pharma companies and patients benefit from the Big Data boom thanks to better drugs brought to market faster, more safely and more economically.
Gary Palgon is vice president of healthcare and life sciences solutions at Liaison Technologies. In this role, Gary leverages more than two decades of product management, sales, and marketing experience to develop and expand Liaison's data-inspired solutions for the healthcare and life sciences verticals. Gary's unique blend of expertise bridges the gap between the technical and business aspects of healthcare, data security, and electronic commerce. As a respected thought leader in the healthcare IT industry, Gary has had numerous articles published, is a frequent speaker at conferences, and often serves as a knowledgeable resource for analysts and journalists. His prolific and consistent contributions to the advancement of healthcare IT earned him a prominent spot on the crowdsourced #HIT100 list in 2012 and 2013. Gary is a Certified Information Systems Security Professional (CISSP®) and holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida from 2012-13. Gary is a Certified Information Systems Security Professional (CISSP®) and holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida.
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