Examination of Clinical Trial Costs and Barriers for Drug Development. 5 Analysis of Barriers to Clinical Trials


Using information gathered in the literature searches and drug sponsor interviews, we developed a list of potential approaches to reducing or eliminating many of the barriers discussed above. This list of strategies to mitigate barriers was then further refined based on discussions with the working group. In order to select a set of barriers/alternatives to analyze, the working group considered whether each proposed strategy could be alleviated by policies, whether the appropriate policies could be implemented or encouraged by FDA, and whether there was evidence in the literature that could be used to quantify the potential impacts of those policies on clinical trial costs. Based on these criteria, we selected the following barrier mitigation strategies for analysis:

  • Use of electronic health records (EHR)
  • Looser trial enrollment restrictions
  • Simplified clinical trial protocols and reduced amendments
  • Reduced source data verification (SDV)
  • Wider use of mobile technologies, including electronic data capture (EDC)
  • Use of lower-cost facilities or at-home testing
  • Priority Review/Priority Review vouchers
  • Improvements in FDA review process efficiency and more frequent and timely interactions with FDA

In the context of the clinical trials decision-making framework described above, the barriers can be thought of as those factors that contribute to the cost of each event node and/or those that affect the probability of success. All of the barriers discussed previously ultimately increase the total cost of clinical trials, thus reducing the eNPV of drug development from the point of view of the drug sponsor. In the clinical trials cost model, implementation of policies to alleviate these barriers is captured in the form of reduced clinical trial costs, reduced duration, or changes to other relevant parameters. Within the model interface, users have the option to select one or more approaches from the above list to see the impact on expected trial costs. In general, if the multiple strategies selected impact the same cost parameters, the effects are assumed to be additive, meaning that the associated percentage reductions are summed and then applied to the default values. The individual barrier mitigation strategies and their impacts on model parameters are discussed in further detail below.

Our estimates of the impacts of each approach are based on data available in the published literature and may therefore omit certain other impacts where data do not exist. In the detailed descriptions of each strategy below (Table 3), we discuss the impacts on model parameters that we were able to quantify using published estimates and also list any other parameters that are likely to be impacted but for which we do not have a basis to estimate the magnitude of effect. Given these data limitations, it is therefore necessary to note that the impacts of each strategy on clinical trial costs are likely to be underestimates.

Table 3: Barrier Mitigation Measures and Associated Modeling Approach for Analysis

Barrier Mitigation Measures Approach to Modeling Notes/Sources
Encourage more widespread use of electronic health records (EHR) for clinical research purposes
  • Patient Recruitment Costs (per patient): Reduced by 35.9%
  • Number of Patients (per site): Reduced by 12.3%
Notes: Adoption rate of 16% in 2009 has been used to adjust the percentages/effects reported in the literature. Source: U.S. Department of Health & Human Services, 2012; Deloitte, 2009.
Encourage sponsors to carefully consider their trial enrollment restrictions
  • Patient Recruitment Costs (per patient): Reduced by 21.3%
Source: Getz, 2008.
Encourage sponsors to simplify clinical trial protocols and plan carefully to avoid costly amendments, whenever possible; ensure that they have a clear understanding of what is required by FDA and what is superfluous
  • Data Collection, Management and Analysis Costs (per study): Reduced by 22.5%
  • Number of IRB Amendments (per study): Reduced by 33%
  • Clinical Procedure Total (per patient): Reduced by 22.3%
Source: Tufts, 2012; Getz, 2010b; Getz, 2008.
Engage sponsors in discussions on the topic of data and site monitoring to ensure that they are aware of the FDA guidance stating that 100% source data verification is not required
  • SDV Cost (per data field): Reduced by 11.6% and 14.3% in Phases 2 and 3, respectively, for cardiology, and 16.7% and 23.5%, respectively, for oncology. For other therapeutic areas, simple averages (14.2% and 18.9%) are used. SDV costs will not be reduced for Phases 1 and 4. Using 100% SDV rates from Medidata, we adjust these impacts depending on how prevalent 100% SDV is by phase and therapeutic area.
Notes: Adoption rates by phase and therapeutic area used to adjust effects. Sources: Tantsyura, et al., 2010; Medidata
Encourage sponsors to make wider use of mobile technologies, centrally available data to evaluate site performance, electronic data capture (EDC), and other efficiency-improving options
  • Phase Time (in years): Reduced by 17.6% in Phases 1, 2, 3, and 4.
  • Number of Site Management Months, Number of Project Management Months, Number of Site Monitoring Days: Reduced by the same percentage as Phase Time (in years)
Notes: Adoption rate of 50% in 2007-2008 has been used to adjust the percentages/effects reported in the literature. Source: Neuer, Warnock, & Slezinger, 2010.
Encourage sponsors to utilize lower-cost facilities (such as local clinics and pharmacies) or athome testing for data collection purposes whenever possible
  • Phase Time (in years): Portion of trial time attributed to enrollment (assumed to be one year each for Phases 1, 2, and 3) reduced by 67%
  • Number of Site Management Months, Number of Project Management Months, Number of Site Monitoring Days: Reduced by the same percentage as Phase Time (in years)
Source: Shapiro, 2008; Marks & Power, 2002.
Grant developers of treatments for neglected diseases a “priority review voucher”
  • Phase Time (in years): Review phase reduced to 0.5 years (6 months)
Source: Ridley, Grabowski, & Moe, 2006.
Conduct internal reviews of efficiency within the FDA and make improvements where possible (also engage in more frequent and timely interactions with industry)
  • Phase Time (in years): Review phase reduced to 0.833 years (10 months)
Source: U.S. Food and Drug Administration, 2012c.


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