American Pharmaceutical Review Supplement, April 2015

The cost of clinical trials has increased dramatically in the last several years, and now accounts for the largest portion of drug development costs. These high costs are not only driving up the cost of therapies that make it into the hands of patients — they are potentially contributing to increased reluctance on the part of pharmaceutical companies to invest in expensive studies that very well may not lead to a marketable drug, and therefore possibly limiting the development of lifesaving treatments.

While a more rapid and efficient process for the evaluation and approval of clinical trial results is clearly needed, drug companies are looking for immediate steps they can take to lower the direct costs of clinical trials. Integrated, cloud-based data capture systems are increasingly recognized to provide greater efficiency from the trial design stage through data collection and monitoring to report generation. Newer software for calculating the numbers of patients, rounds of treatment, and locations needed and forecasting the associated trial budget is also helping sponsor companies plan more efficient studies.

Introduction

Testing new potential drugs to confirm their efficacy and safety is a crucial part of the drug development process. Clinical trials provide invaluable information regarding the performance of drug candidates, but are also time-consuming and costly. It is estimated that a new drug costs approximately $1.3 to $1.7 billion to develop, and this number has been rising at a higher rate than inflation for many years, largely due to increasing clinical trial costs.¹ In 2010, the average costs of Phase 1, 2, and 3 clinical trials were estimated to be $24 million, $86 million, and $61 million, respectively.² Furthermore, a 2012 study revealed that on average 90% or more of a drug’s development costs are incurred in Phase III trials.³

The rapid cost increases can in large part be attributed to the growing size and complexity of clinical trials. Many trials are now designed to compare a drug candidate to an existing commercial product and require more patients to detect any differences. In addition, more drugs are being developed for chronic conditions, and clinical trials for these candidates must be run for sufficient time periods to determine any potential long-term side effects. The increasing use of multicenter trials — which are more expensive due to their size, but also often suffer from disagreements in data interpretation, conservative approaches to monitoring (including numerous site visits), and complex trial protocols — can all lead to delays and higher costs.

That increasing complexity is also driving the need for accurate forecasting of clinical trial budgets given the numerous inputs and resources that contribute to the overall costs of a trial. Although accurate budget estimates are required to secure funding, often the financial management of clinical trials is performed using time-consuming spreadsheet-based programs. This approach leads to very long start-up times for clinical trials, which in turn adds to study costs and further extends the time to market. A recent evaluation of the decision-making process for the design and execution of clinical trials revealed a clear need to increase the efficiency of the regulatory review process and recommended an extension of the priority review processes implemented by the US Food and Drug Administration (FDA) for orphan, breakthrough, and certain other types of drugs. The researchers also recognized, however, that more immediate measures are also needed to alleviate the high costs of clinical trials. The best options included the use of lower-cost facilities/in-home testing and increased use of mobile technologies and electronic data capture (EDC), which were estimated to reduce trial costs from 8 to 24% across all phases⁴.

Benefits of Cloud-Based EDC

The use of EDC is encouraged by the FDA⁵ because this approach to data management offers significant benefits to everyone involved in a clinical trial, including sponsors, investigators, and patients. Overall, EDC helps clinical studies run more smoothly. Perhaps the most obvious benefit is elimination of paper files and the challenges associated with maintaining data in such a format. Digital files can be more readily monitored and updated, and the data in them can be shared much more easily with everyone that needs access to the data. Data entry can be more accurate, too, with automated edit checks and alerts reducing the potential for error. In addition, it is much easier to organize and search digital data. EDC systems also help ensure that increasingly demanding regulatory requirements regarding data capture and reporting can be met with confidence.

Given these advantages, it is not surprising that clinical trial management using electronic data capture systems is much more efficient and cost-effective. EDC tools can also be used to more rapidly design and launch trials and eliminate the need to create paper case report forms (CRFs). Data can also be readily retrieved without the need to search physical files that may or may not be in the same location.

Cloud-based EDC systems provide even more benefits. Most notably, cloud-based software allows the storage of all information, including protocols, assignments, and patient data, for all sites in a clinical trial in one central location. As a result, data monitoring and reporting are even more efficient. In addition, everyone involved in the trial has access to the same data set, providing both greater accuracy from site to site and collaboration between sponsors, contract research organizations (CROs), investigators, and even regulators. Furthermore, this increased communication often leads to a reduction in the overall length of a clinical trial, which in turns means reduced study costs and faster time to market. In fact, integrated, cloud-based EDC systems are ideally suited for the more complex clinical trials studies being performed today, often by CROs.

They provide much more than just data capture and management, and can help track drug supply, manage images, coordinate reporting, or even provide assistance with translation and patient education. They also can be designed to communicate with mobile devices for the convenience of patients, investigators, and others involved in clinical studies. With a single, secure platform covering all of the aspects of a clinical trial, from designing the study to collecting data directly from patients to managing randomization, endpoint adjudication, and final report generation, it is possible to make better decisions in a more efficient, timely, and cost-effective manner because the system provides immediate access to more accurate and complete data. In particular, such integrated online software solutions can provide real-time data visibility and facilitate more efficient endpoint coordination and adjudication processes, streamlining the process.

Advantages of Advanced Forecasting Capabilities

As the costs of clinical trials continue to rise, in order to minimize financial risk it is becoming increasingly important to not only find ways to minimize expenses, but also develop an appropriate budget. A 2011 industry survey of financial professionals on study budgeting practices and metrics revealed that for 45% of the respondents, the typical variance (positive or negative) from the original budgeted cost of a clinical study was 11%, and 20% experienced discrepancies of 16% or greater.⁶ As importantly, the development of these often inaccurate budgets was a lengthy process, taking three weeks or more for half of the survey participants. The budget review process fared no better, with 65% of survey participants indicating that five weeks or greater was typical. One of the main causes of these extended processes was found to be a lack of purpose-built forecasting and budgeting software.

Developing an accurate budget for a clinical trial study is not a simple task, of course. For instance, budgeting cannot take place without an accurate forecast of the needs of the study, including the number of sites, enrollment numbers, patient characteristics, length of the study, use of contractors vs. full-time employees, and more. This forecasting and budgeting process is all the more complicated, however, if data are manually collected and enrollment information at various sites is not readily collated and/or stored in different spreadsheet programs, there is often a need to reconcile the information, and in some cases reenter the agreed-upon data.

In addition, because most EDC systems for clinical trial management are focused on data management, they do not include financial forecasting or scenario modeling capabilities, which are required for resource estimation and, consequently, accurate budgeting. Furthermore, for successful resource planning, forecasting, and budget development, it is necessary to have input from upper-level management and the “boots on the ground” using assumptions based on historical activities. Ideally, the resource forecasting, financial, and operating systems are integrated in order to allow seamless transfer of accurate data and results. 

Cloud-based systems designed for clinical trial management therefore present the perfect opportunity to improve resource forecasting and budgeting, whether for one trial or a company’s entire study portfolio. Web-based tools also allow standardization of the forecasting and budgeting models and processes, which increases the efficiency and reduces the time required for both the development and review of clinical trial budgets.

Modular Designs for Multiple Applications

Despite the advantages of EDC systems, and cloudbased systems in particular, many sponsors and CROs, particularly smaller companies, continue to use paper-based systems or rely on a myriad of Excel worksheets to manage their clinical trial data. Most often, the reason is an expectation that the required upfront investment for advanced software solutions is too great and the need to sign long-term contracts is too burdensome.

While that scenario may have been true when EDC systems were first introduced, it need no longer be the case today. Cloud-based platforms designed for clinical trial management are now available as modular systems that can be customized to meet the needs of any given clinical trial, regardless of the size and complexity. With cloud-based modular systems, it is possible to select only the specific databases and workflows that are needed for each clinical trial, allowing for very efficient processes.

Furthermore, the pricing models for modular systems can be much more flexible. For example, with the Merge eClinicalOS (eCOS) platform, there is no multiyear contract or any large upfront capital expenditure required. Instead, the system is configurable, allowing for inclusion of only the capabilities that fit with the dynamics of a given study. Pricing for each module is also transparent, and payment is made based solely on what is used and how long it is used for.

The eCOS platform is also designed to help users with resource forecasting and budgeting of clinical trials before they begin. The Clinical Configurator is a management calculator that can be used to determine study costs based on the total number of patients, rounds of trials, locations, etc. This ability to clearly identify the cost of each component in a study from the beginning can help dramatically speed up the budgeting process and reduce the time needed for budget reviews, which ultimately reduces the time for the study, lowers costs, and gets the drug to the people who need it most—the patients.

References

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2. Adams, C, Brantner, V. Spending on new drug development. Health Economics. 2020;19(2),130-141.
3. Roy ASA. Stifling new cures: the true cost of lengthy clinical drug trials, Project FDA Report, 5. April 2012. http://www.manhattan-institute.org/html/fda_05.htm. Accessed 2/5/2015.
4. Sertkaya A, Birkenbacjh A, Berlind A, Eyraud J. Examination of clinical trial costs and barriers for drug Development. July 25, 2014. http://aspe.hhs.gov/sp/reports/2014/ClinicalTrials/rpt_erg.pdf. Accessed 2/5/2015.
5. US FDA. Guidance for industry: electronic source data in clinical investigations.
   September 2013.
   http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm328691.pdf. Accessed 2/5/2015.
6. Grygiel A. The struggle with clinical study budgeting: industry survey reports problems with accuracy and efficiency. Contract Pharma. October 11, 2011. http://www.contractpharma.com/issues/2011-10/view_features/the-struggle-with-clinical-study-budgeting/. Accessed 2/5/2015.