CommentaryRisk Assessment

Traversing the Valley of Death: A Guide to Assessing Prospects for Translational Success

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Science Translational Medicine  09 Dec 2009:
Vol. 1, Issue 10, pp. 10cm9
DOI: 10.1126/scitranslmed.3000265



  • Table 1. Questions for self-guided assessment of issues affecting the success of translational research projects.
    CategoryEvaluation questions
    1. Is it worth the effort? Does the new technology’s intended use address a compelling health need?
    Is the scientific rationale strong, and does it suggest a possible medical benefit when compared with existing therapies?
    2. Is there an adequate potential commercial market?Does the size and type of market indicate a high likelihood of economic viability?
    Is the intellectual property protection solid?
    Is the technology likely to be cost-effective?
    3. What can be inferred from human and animal data about likely safety and efficacy?Is there a human genetic disorder that affects the therapeutic target?
    If so, does the phenotype support the efficacy and/or safety of the agent?
    Are the animal models used to assess efficacy and safety convincingly representative of the human disease?
    4. Can the agent be delivered to its target at an adequate concentration?Are the pharmacokinetics and pharmacodynamics acceptable for the intended use, based on direct assessment of the effects on the target molecule or meaningful functional assays?
    5. Is there an industry partner that can develop the technology effectively and efficiently?Is there an industry partner willing to make the development program a high priority?
    Will the industry partner ensure that the preclinical and clinical development groups exchange ideas throughout the development process?
    Is there an industry partner that will refrain from excessive secrecy?
    Can the technology be manufactured easily and at a reasonable price?
    6. Can a pivotal study be designed and completed?Can a study be designed with a medically meaningful endpoint?
    Can the study be designed to reflect clinical equipoise and be attractive to both participants and their clinicians?
    Can a study be designed with sufficient statistical power to detect the endpoint?

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