Clinical and economic challenges facing pharmacogenomics.

In this paper, we examine the clinical and economic challenges that face developers of and payers for personalized drugs and companion diagnostics. We review and summarize clinical, regulatory and reimbursement issues with respect to eight, high profile personalized medicines and their companion diagnostics. Subsequently, we determine Medicare parts B and D reimbursement of the eight drugs from publicly available databases. Finally, we utilize surveys-each tailored to three key stakeholders; payers, drug and diagnostic developers, and pharmacogenomic expert analysts-to assess reimbursement of diagnostics, analyze the role that different kinds of evidence have in informing prescribing and reimbursement decisions, as well as the specific clinical, regulatory and economic challenges that confront pharmacogenomics as it moves forward. We found that Medicare beneficiary access to physician-administered (Medicare part B) drugs is relatively unfettered, with a fixed patient co-insurance percentage of 20%. More reimbursement restrictions are placed on self-administered (Medicare part D) drugs, which translates into higher and more variable cost sharing, more use of prior authorization and quantity limits. There is a lack of comprehensive reimbursement of companion diagnostics, even in cases in which the diagnostic is on the label and recommended or required by the Food and Drug Administration. Lack of evidence linking diagnostic tests to health outcomes has caused payers to be skeptical about the clinical usefulness of tests. Expert analysts foresee moderate growth in post-hoc development of companion diagnostics to personalize already approved drugs, and limited growth in the concurrent co-development of companion diagnostics and personalized medicines. Lack of clinically useful diagnostics as well as an evidence gap in terms of knowledge of drug and diagnostic clinical effectiveness appear to be hindering growth in personalized medicine. An increase in comparative effectiveness research may help to close the evidence gap.