The average time for a drug to gain U.S. Food and Drug Association (FDA) approval can be 10 or more years. The actual dollar amount to bring a compound to the market has been frequently debated with one source reporting that drug development costs have more than doubled in the past decade from about $1 billion to $2.5 billion.[1] Costly amendments due to flawed protocol design and drawn-out searches for sites and suitable patients continue to hamper the clinical trial process.
 
Leveraging the valuable data stored in the growing number of electronic health record (EHR) databases can help eliminate delays, reduce costs, and get new therapies to market faster. Technology now exists to free up EHR data and streamline the clinical trial process.
 
Challenges of the current clinical trial process
Many industries in the consumer business are taking advantage of big data to revolutionize their business processes and uncover insights to deliver products and services faster at reduced costs. The pharmaceutical industry, however, has essentially maintained the same product development process for the past quarter century.
 
Healthcare data, even when electronically available, is locked away in separate database silos. It is difficult to link because of different standards and stringent privacy and security requirements. The lack of access to healthcare data has resulted in enormous obstacles when it comes to drug development and the clinical trial process.
 
Pharmaceutical companies lack real time data so site selection often relies on historical information or is relationship-driven. Contract Research Organizations (CROs) are challenged when inclusion and exclusion criteria are chosen without verifying the impact on availability of a cohort, which can create avoidable amendments.
 
A promising way to overcome these challenges is through the use of real-world EHR data. In addition to their traditional sources of information – literature, recommendations from opinion leaders, or prior studies – protocol authors can now leverage data based on the way patients present themselves in actual medical care settings, i.e. in real world, rather than an artificial experimental environment of a clinical trial.
 
Site selection is also more effective when EHR data are used to ensure viability of eligible patients. Currently, about 20 percent of initiated sites fail to enroll a single patient. Historically, only five to 10 percent of patients initially identified by an investigator are ultimately enrolled.[2] Using EHR data allows investigators to not only see the total number of patients fulfilling specific eligibility criteria, but also to analyze the trend over several quarters for each institution. It also helps investigators fulfill their Good Clinical Practice (GCP) obligation, i.e. to prove study specific patient availability before they accept a clinical trial. At the site, after appropriate approvals, patients can be re-identified and, if allowed by local Institutional Review Board (IRB) procedures and logistically possible, contacted for potential clinical trial participation.
 
Overcoming the obstacles of EHR data use
While there is little doubt the use of EHR data will help dramatically improve the clinical trial process, some obstacles remain.
 
Disparate EHR databases that each have their own clinical data coding must be standardized to enable easy access and research collaboration. This mapping process can be difficult since each database may be at a different level of maturity with diverse levels of support and various tooling options for mapping. The technology now exists to facilitate consolidation that can harmonize the data and make it available for investigator research.
 
Data security is also a major concern due to the strict privacy rules. Any EHR data that is made available for research must be anonymized to protect the privacy of individual patients. This can be accomplished by decentralized archiving of data that keeps the EHR data at the healthcare institution safely behind their firewall (the “federated” model). External queries are then processed within the organization’s database or with the use of a local copy.
 
Long term benefits of EHR data use
Leveraging EHR data from multiple organizations will serve to dramatically broaden the data pool and greatly enhance protocol development as well as site and patient selection. Providing easy, yet secure access to this valuable data will benefit all parties in the clinical trial process – pharmaceutical companies, CROs, and healthcare organizations. This mutually beneficial relationship will enhance collaboration and improve cooperation among all related entities.
 
Increased use of EHR data takes us one step closer to using real world evidence (RWE) in drug development. Current reservations stem from the time when EHR data was exclusively used for billing. With the increased use of more sophisticated EHR systems, which will allow their use for research and quality management, a shift in mindset is to be expected, and EHR will gain a more trustworthy and high quality reputation.
 
Too much of the current clinical trial process relies on opinions, prior experience, or semi-quantitative methods. TriNetX found that using EHR data can help validate these subjective results with real-world data from the documented medical histories of actual patients. It is time for the healthcare industry to unleash its valuable EHR data to enhance the drug development process and bring much-needed therapies to market in a much faster and cheaper way.

---

[1] The Cost of Clinical Trial Delays, Ken Getz, Director, Sponsored Research Programs, Associate Professor, Tufts CSDD, Tufts University School of Medicine, January 2015. https://www.ctti-clinicaltrials.org/files/pgct-session5.1-getz.pdf

[2] Effective Strategies for Patient Recruitment and Retention, by B Harper, UC Davis Clinical and Translational Science Center, December 5, 2014.

---

 Dr. Stapff of TriNetX

Dr. Manfred Stapff is Chief Medical Officer of TriNetX in Cambridge, MA. He is a physician and clinical pharmacologist with over 20 years of experience in the pharmaceutical industry. After his training in internal medicine, he gained extensive knowledge of pharmaceutical development through diverse positions in clinical research, medical services, and regulatory affairs in research-oriented pharmaceutical companies, such as Merck & Co., Inc. and Forest/Allergan., USA. His publication list encompasses articles and contributions in the field of cardiovascular diseases, clinical trials/GCP, EHR as well as books on clinical trials and project management.