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In interviews, expert consultants and representatives from pharmaceutical and biotechnology companies and CROs cited patient recruitment as one of the most significant barriers to conducting clinical trials in the United States. Failure to recruit sufficient numbers of patients can result in costly delays or even cancellation of the entire trial (

Closely related to the cost of clinical trials is the length of time it takes to complete them, which has also increased in recent years. Between 2000 and 2005, pharmaceutical companies experienced a three percent median increase in development cycle times and a nearly 11 percent increase in regulatory cycle times (Getz K. A., 2006). Though the mo

The largest barrier to conducting clinical research—and the one into which most other barriers feed—is the high cost. Studies estimate that it now costs somewhere between $161 million and $2 billion to bring a new drug to market (DiMasi, Hansen, & Grabowski, 2003; Adams & Brantner, 2006; Morgan, Grootendorst, Lexchin, Cunningham, &

Broadly speaking, the major obstacles to conducting clinical trials in the United States identified through this research include: high financial cost, the lengthy time frames, difficulties in recruitment and retention of participants, insufficiencies in the clinical research workforce, drug sponsor-imposed barriers; regulatory and administrative

Our study suggests that therapeutic area as well as number and types of clinical procedures involved are the key drivers of costs in Phase 1 through Phase 4 studies. The therapeutic areas with the highest per-study costs in Phase 1 is immunomodulation ($6.6 million), in Phase 2 is hematology ($19.6 million), in Phase 3 is pain and anesthesia ($52.

Table 2 presents clinical trial costs by cost component across all therapeutic areas by trial phase. Similar to our evaluation of costs by trial phase discussed in Section 3, when averaging costs across therapeutic areas, we weighted the data by the number of contracts available by therapeutic area. Excluding the All Other Costs and Site Overhe

To compare average costs by phase across all therapeutic areas, we computed a weighted mean cost, , and its weighted standard deviation, s ij , , for each cost component, i , and clinical trial phase, j , where the weights are the total number of contracts (i.e., sum of investigator and contractor contracts contributing to the PICAS ® and

Table 1 presents the total costs for each of the therapeutic areas included in our model by clinical trial phase (assuming one trial per phase and not inclusive of failures). From the table, immunomodulation per-study costs ($6.6 million) are the highest in Phase 1 with costs of studies in ophthalmology ($5.3 million) and respiratory system ($5.2

We worked closely with Medidata to determine the appropriate methodology for aggregating the itemized costs that characterize the overall cost of a clinical trial. To obtain totals for each individual trial within a given phase, we grouped the cost components into per-study costs, per-patient costs, and per-site costs, where:

The clinical trial cost/decision-making model described above requires numerous data points, including phase durations, success probabilities, expected revenues, and a discount rate, as well as a full range of itemized costs associated with clinical trials, broken down by phase and therapeutic area. The model uses a real annual discount rate of 15

Although the decision tree analysis format is invaluable in characterizing a range of clinical trial formulation possibilities, the modeling can become extremely complex as the number of event and decision nodes increases. Thus, while the operational model developed allows the user to enter customized cost scenarios in a certain therapeutic area,

The literature review and discussions described above served to inform the conceptual framework for our model. We modeled the clinical trials decision-making process in the form of a decision tree that looks at the decision process from the point of view of an expected-revenue-maximizing sponsor in the face of uncertainty (or risk).

We used three proprietary databases on clinical trial costs, which are offered by Medidata Solutions, a global provider of cloud-based solutions for clinical research in life sciences, as part of the broad set of solutions available through the Medidata Clinical Cloud ™ :

Some of the information needed to characterize the decision process of a drug sponsor came from semi-structured discussions with our team of experts and other industry experts, FDA personnel, drug sponsors, CROs, and primary clinical research centers, including University of Massachusetts, Johns Hopkins University, University of Michigan, and the

Although the literature on the early stages of the pharmaceutical decision-making process is not extensive, there is some research that has characterized the process. We used this information to help define the components of the model. Some examples are the work performed at the Massachusetts Institute of Technology (MIT) Center for Biomedical Inn

In constructing an operational model of clinical trial decision-making, we compiled information from a variety of sources, including:

The existing literature on clinical trials primarily discusses the process of performing clinical trials—including statistical design issues and coordination problems among multiple centers and disciplines—and results, but few sources offer insights regarding the decision process of the sponsor (Hammons, Hilman, Kahan, & Neu, 1985). From t

In calendar year 2012, Food and Drug Administration (FDA) Center for Drug Evaluation and Research (CDER) approved 39 novel new drugs (i.e., new molecular entities (NMEs) and new biological entities (NBEs), including both novel drugs and biologics). 1 While 39 approvals marks the highest number of NMEs/NBEs approved since 2004, drug companies are

Appendix Table 5: List of Drugs Used in Determining Different Market Size Estimates for CUTI

Appendix Table 6: List of Drugs Used in Determining Different Market Size Estimates for HABP/VABP