The use of mobile technologies and basic clinical electronic data capture (EDC) systems, both of which are encouraged by the Food and Drug Administration (FDA), is helping to streamline the clinical trial process and reduce costs. More advanced, integrated cloud-based platforms are achieving further gains with Web-based tools that track drug supply, manage images, coordinate reporting, and provide assistance with translation, endpoint adjudication, and more.
The growing interest of major technology companies in advancing automation in the healthcare industry signals even greater changes to come. The result will be increasingly effective medications and more personalized healthcare.
Costs and Timelines Continue to Rise
Using traditional methodologies, clinical trial timelines have lengthened and costs have risen dramatically in recent years. Phase I, II, and III trials were estimated to cost on average more than $170 million ($24 million, $86 million, and $61 million, respectively) in 2010.1 More data are being generated and must be collected, monitored, managed and shared. Those involved in managing trials — from sponsor companies to contract research organizations (CRO) and academic institutions — must continuously strive to reduce complexity, streamline business processes and workflows, and increase efficiencies at all scales.
Regulatory Support Encourages EDC Adoption
Clinical EDC systems have proven to streamline workflows and increase data management efficiencies. The FDA has recognized EDC as an important enabling technology,2 and the agency is strengthening requirements for its use.3
The FDA is encouraging the use of EDC systems because they support more accurate collection, analysis, and sharing of data. Moreover, EDC platforms help increase compliance with regulatory requirements and lower overall costs. Such tools also help spur adoption of the adaptive clinical trial model,4 which can save sponsor companies between $100 and $200 million annually through early termination of unsuccessful studies.5
The FDA also is shifting its focus from one that stresses compliance above all to one that places quality first.6 More and more, the FDA is emphasizing the use of quality metrics that can be readily obtained through advanced EDC software. The FDA has mandated that, beginning in 2017, all marketing application submissions for drugs and biologics be made using the electronic Common Technical Document (eCTD). Commercial INDs (clinical trial applications) will need to be submitted electronically by May 5, 2018.7
Cloud-based platforms are helping to meet these new requirements with central data files that are automatically updated and accessible for even greater collaboration. As companies like Google, Apple, and IBM explore solutions that speed decision-making at all levels, the implementation of efficient data management systems is crucial.
Replacing the Burden of Paper
EDC software helps improve clinical studies by optimizing communication and workflows and increasing accuracy of data entry, organization, and monitoring. By eliminating the need to manually create, track, search, and analyze thousands of paper case-report forms (CRFs), EDC can be used to more rapidly design and launch trials (sometimes in as little as 10 days).
Cost savings result from the diminished need for on-site monitoring as well as the decreased time required to rectify data errors.8 But the elimination of paper CRFs has perhaps the greatest impact on increasing trial efficiencies.9 One study found that study periods were reduced on average by more than 300 days10 and trial costs by as much as 24 percent11 when an EDC system was implemented. It’s little surprise that nearly half of all new trials now use EDC.12
Functionality Drives Increased Efficiency
Beyond EDC, many cloud-based solutions comprise Interactive Web Response (IWR) tools for tracking inventory, images, reporting, and endpoint adjudication. For example, the endpoint adjudication module from Merge eClinical gives sites, coordinators, and adjudicators online access to all files and automatically compiles electronic dossiers of required endpoint details and source documents. The timeliness and quality of endpoint data capture are enhanced, making faster adjudication possible. In addition, the levels of standardization and consistency are increased, helping to minimize process-driven variability that can influence endpoint outcomes.13
For many early clinical EDC systems, management of randomization was not included, and EDC and IWR systems were often disparate and difficult to link. This problem has largely been solved as the majority of today’s systems address all randomization and data-capture needs through a single platform. Many cloud-based systems go even further, letting users conduct randomization and inventory-management tasks across the entire supply chain from any Web-enabled device.
Empowering Users to Do More
The growing use of software-as-a-service (SaaS) data management systems by small- to mid-size sponsors, CROs, and academic institutions also suggests that such solutions help distribute the benefits of IT more equitably across the clinical research landscape. When organizations of all sizes use advanced data management tools, researchers can bring safer, more efficacious therapies to the market more quickly and at lower costs.14
At the same time, many CROs wish to expand their ability to build studies independently and develop the capability to provide this service to clients. Some systems are therefore designed to facilitate internal study building and help customers automate their workflows. Through consistent and intuitive user interfaces, such systems simplify the study design process and make it possible for researchers without programming skills to build and deploy a trial within weeks.
Personalizing Healthcare
The “recent development of large-scale biologic databases, powerful methods for characterizing patients (such as proteomics, metabolomics, genomics, diverse cellular assays, and even mobile health technology) and computational tools for analyzing large sets of data” are now fueling the Precision Medicine Initiative (PMI), according to Francis Collins and Harold Varmus in “A New Initiative on Precision Medicine,” a Perspective published in the New England Journal of Medicine in February 2015. This initiative will revolutionize healthcare and generate the scientific evidence needed to move the concept of precision medicine into clinical practice.15 By considering genetic variability, these technologies are making personalized disease treatment and prevention viable.
Conclusion
Automated technology, including advanced data management software, is pushing the boundaries of what can be achieved in healthcare, from bench to bedside. New approaches to data generation, management, and analysis are enabling the use of enormous data sets, thereby empowering researchers and medical professionals to make faster and more reliable decisions. Similarly, data sharing and collaboration tools are making it possible to more rapidly determine the safety and efficacy of potential drug candidates for different patient populations, heralding an era of personalized healthcare.
References
- Adams C., Brantner V., “Spending on new drug development,” Health Economics, 19 (2), pp. 130-141 (2010).
- U.S. FDA, “Guidance for Industry: Electronic Source Data in Clinical Investigations,” September, 2013. http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm328691.pdf.
- U.S. FDA, ”Providing Regulatory Submissions In Electronic Format —Standardized Study Data: Guidance for Industry,” December 2014, http://www.fda.gov/downloads/Drugs/.../Guidances/UCM292334.pdf.
- U.S. FDA, “Guidance for Industry: Adaptive Design Clinical Trials for Drugs and Biologics.” February 2010.
- Getz K., Stergiopolous S., and Kim J. (2013). The Adoption and Impact of Adaptive Trial Designs. Tufts Center for the Study of Drug Development, Tufts University. Retrieved from http://csdd.tufts.edu/files/uploads/tuftscsddbrief1final_new.pdf.
- Public Law 112–144 Food and Drug Administration Safety and Innovation Act http://www.fda.gov/RegulatoryInformation/Legislation/FederalFoodDrug
andCosmeticActFDCAct/SignificantAmendmentstotheFDCAct/FDASIA/ucm20027187.htm - Infotehna, “FDA Sets Date for Mandatory eCTD Submissions,” May 8, 2015, http://www.infotehna.com/news-items/items/fda-sets-date-for-mandatory-ectd-submissions.
- Global Clinical Trials: Effective Implementation and Management 471 (Chin and Bairu eds., 2011).
- Safer, Faster, Cheaper: Improving Clinical Trials and Regulatory Pathways to Fight Neglected Diseases”, Report of the Center for Global Development’s Working Group on Clinical Trials and Regulatory Pathways; Chair Thomas Bollyky, 2011.
- Thompson Reuters, Information Technology is Improving Clinical Practice (2011).
- Sertkaya A., Birkenbacjh A., Berlind A., Eyraud J., “Examination of Clinical Trial Costs and Barriers for Drug Development,” July 25, 2014.
- Parekh S., “Electronic Data Capture in Clinical Trials,” App. Clin. Trials, 22 (9), (2013).
- Tyner C. and El-Assi Z., “Electronic Endpoint Adjudication,” Supplement to App. Clin. Trials, Mar 1, 2010.
- El-Assi Z. “Catch a Wave and You’re Sitting on Top of the World: How Information Technology is Leveling the Playing Field,” Pharmaceutical Business Review, November 19, 2014, https://pharmaceutical.businessreviewonline.com/suppliers/merge-eclinical-smart-research/whitepapers/catch-a-wave-and-youre-sitting-on-top-of-the-worldhow-information-technology-is-leveling-the-playing-field.
- Collins F. S., Varmus H., “A New Initiative on Precision Medicine,” N. Engl. J. Med., 372, 793-795 (2015).