BOX 7-1
Major Proposals Made by Individual Speakers

•    Eliminate laboratory developed tests and have all genomic diagnostic tests undergo FDA review and approval. (Hayes)

•    Base FDA approval on analytical validity and clinical utility, not clinical validity and intended use. (Hayes)

•    Consolidate the review of all oncologic products within a single FDA office. (Hayes)

•    Base reimbursement on the value of a genomic diagnostic test to patients, payers, and society. (Hayes)

•    Clarify the regulatory and reimbursement pathways for genomic test development. (Siegel)

•    Preserve physician discretion in ordering, interpreting, and delivering diagnostics, therapies, and other forms of care. (Conti)

•    Ensure that agency decision making is transparent, with rulemaking by notice and comment rather than through guidelines. (Conti)

•    Standardize the validation of protocols and enhance quality control to improve the efficiency of test development. (van ‘t Veer)

•    Provide guidance for IRBs on how to review genomic tests. (van ‘t Veer)

•    Provide opportunities and incentives for guidelines committees and regulatory bodies to harmonize their definitions of clinical utility. (van ‘t Veer)

•    Reform reimbursement to recognize the value of diagnostic tests, their impact on health care, and the resources needed to develop and validate tests. (Enns)

•    Establish reliable and accurate performance standards for new genomic tests.(Enns)

of the possible and promising tests can be developed, so the system should enable more to be developed, not fewer.

With regard to the distinction between CLIA-regulated tests and FDA-approved tests, Shak said that “the devil is in the details.” Either route could yield regulation that is fit for purpose. In that respect, looking at the purpose of a test and then deciding on the proper kind of regulation may be more appropriate than the opposite.

Leonard said that it may be inaccurate to contrast an FDA path with an LDT path because there are many different LDT paths. For example, the path is much different in academia than in industry. “Maybe we need to start talking about different LDT pathways and think about the benefits of each.” van ‘t Veer agreed and also observed that the complexity of tests varies greatly. Some require many levels of analysis, data integration, and bioinformatics, while others are relatively simple molecular tests. In addi-

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