Generating Evidence for Genomic Diagnostic Test Development Workshop Summary (2011) / Chapter Skim
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4 Overcoming Barriers for Evidence Generation
4 Overcoming Barriers for Evidence Generation
Pages 43-52
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From page 43... ...
BALANCING STAKEHOLDER NEEDS The purpose of comparative effectiveness research is to provide patients, clinicians, and payers with information that is useful in making treatment and coverage decisions. Many, if not most, comparative effectiveness studies will require a conscious decision to sacrifice internal validity in order to increase generalizability, relevance, feasibility, and timeliness, said session moderator Sean Tunis of the Center for Medical Technology Policy.
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From page 44... ...
To move rapid evaluation forward, new data must be evaluated systematically as they emerge, and decision makers must be willing to stop coverage when it becomes clear that a product does not work as originally thought. It was noted that this is what already happens in many systems, such as the Ontario experience that was presented.1 PUBLIC-PRIVATE PARTNERSHIPS One organizational model that can help address issues of funding, knowledge generation, and social change in the area of data sharing is a public-private, pre-competitive research partnership, said Aled Edwards of the Structural Genomics Consortium.
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From page 45... ...
Edwards said that the only way to develop a truly robust pipeline of genomic diagnostic tests flowing into the clinic will be to share the risk between the public sector, payers, and industry. The Structural Genomics Consortium was begun by stakeholders, including the pharmaceutical companies, the Wellcome Trust, and the Canadian government, declaring a certain area of scientific research as pre-competitive.
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From page 46... ...
Eric Larson of the Group Health Research Institute added that it is often assumed that every new test adds value because it provides information. Genetic testing is not different from other diagnostic testing, and the current focus on genetic tests may provide an opportunity to reframe the overall diagnostics process and highlight the need for the same rigor in developing and evaluating diagnostic tests that are used in developing and evaluating therapeutic products.
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From page 47... ...
The pharmaceutical industry can better afford clinical trials, as the payoff for a new drug can be quite significant compared to research and development costs. Hayes suggested that if markers were more highly valued for their roles in preventing unnecessary treatment of patients who are unlikely to benefit and in identifying those patients who will benefit, it would create an incentive and a revenue stream for diagnostic device developers to carry out prospective trials.
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From page 48... ...
There is no way that provisional device approval could be done in the United States without changes to the existing device law. In Canada, Levin explained, most of the tests that are provided as an insured service need to have been previously approved, by either Health Canada or by the provincial jurisdiction, in order to be regarded as medically necessary; the Centers for Medicare and Medicaid Services play a similar role in the United States.
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From page 49... ...
Two to five percent of the NIDDK clinical trial budget is devoted to the repositories, Germino said, and, while this may seem small, it is actually a substantial draw on the budget. This may also be a factor, he suggested, in why many other institutes have not incorporated biobanks into their study designs.
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From page 50... ...
The potential treasure in biobanking clinical trial samples will not be fully realized unless there is sufficient support for acquiring it. Larson supported merging biobanks with electronic medical records and cited as an example the Electronic Medical Records and Genomics (eMERGE)
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From page 51... ...
In those cases, the investigators met with their institutional review boards to discuss whether the original consents would allow subsequent use by NIDDK. These specimens have had identifiers removed so that they are anonymous, and while they are linked to the clinical outcomes data, there are no Health Insurance Portability and Accountability Act identifiers.
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