Examination of Clinical Trial Costs and Barriers for Drug Development. 2 Clinical Trial Decision-making Model


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 the perspective of a drug sponsor operating under uncertainty, we postulate that the decision to undertake a clinical trial to demonstrate safety and efficacy is likely influenced by a variety of factors including:

  • Potential market size for the drug, which in turn depends on:
    • Type of condition(s) (acute versus chronic, severity) the drug would treat;
    • Size of the patient population (current and future);
    • Number of existing drugs currently on the market that treat the same condition(s) and advances in treatment;
  • Existing incentives, such as the Orphan Drug Act, and fast track FDA review that affect how quickly the drug can be brought to market and offer financial incentives;
  • Clinical stage (Phase 1, Phase 2, and Phase 3) costs that are dependent on a variety of factors, including but not limited to:
    • Patient accrual rates that depend upon selection criteria, the relative ease of screening eligible patients, and physician interest;
    • Administrative, physician, registered nurse (RN), and clinical research associate (CRA) capacity (i.e., number of protocols per RN/physician, number of patients per RN/physician);
    • Number of patients needed for the desired statistical precision;
    • Number of protocols;
    • Number of institutional review boards involved;
    • Number of investigator sites and their locations;
    • Cost of clinical data collection, management, and analysis;
    • Technologies for data collection and verification;
  • Projected manufacturing costs upon FDA approval which would be influenced by whether the drug is a small molecule or a biologic.

The decision process for pursuing a clinical trial is also likely to vary by type of sponsor. A large established pharmaceutical company with deep pockets may be less risk averse and better positioned to undertake costly clinical trials whereas a small emerging company may find it difficult to allocate funding to clinical research, especially if the trials require a large patient population and multiple sites.

Further, some of the clinical trial pathway formulation decisions, such as which indication within a therapeutic category to target and how to time/sequence the trials, are inextricably linked to business realities. Research objectives coupled with financial circumstances can force a sponsor down a specific clinical trial pathway. For example, large established pharmaceutical companies often try to allocate resources based on the research portfolio and the potential to market the product. In contrast, small companies can be focused on whether they can finance the development and up to what point. Small companies are also often subject to results pressures from their investors, which can lead to inappropriate or “short-cut” development approaches.

The approach adopted in this study looks at the decision process from the point of view of an expected-revenue-maximizing sponsor in the face of uncertainty (or risk). As described in the following sections, the simplified clinical decision-making model incorporates the following considerations:

  • Therapeutic area,
  • Potential market size/revenues for the drug, and
  • Clinical stage (Phase 1, Phase 2, Phase 3, and Phase 4) costs that are dependent on a variety of factors, including but not limited to:
    • Physician and RN costs;
    • Number of patients needed for the desired statistical precision;
    • Number of IRBs involved;
    • Number of investigator sites;
    • Cost of clinical data collection, management, and analysis; and
    • Cost of clinical procedures.
  • The following sections describe the data sources used (Section 2.1) in constructing the model, the conceptual framework (Section 2.2), the operational model (Section 2.3), and the model parameters (Section 2.4) in further detail.

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