Commentary For reprint orders, please contact: [email protected]
Roadblocks preventing personalized medicine from reaching its potential “… to achieve improved uptake of personalized medicines, more favorable reimbursement of companion diagnostics is needed.”
Keywords: biomarkers • clinical utility • personalized medicine • reimbursement
Personalized medicine forges ahead “Personalized medicine is tailoring medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs that are unique to each patient, but rather the ability to classify individuals into sub-populations that differ in their susceptibility to a particular disease or their response to a specific treatment.” – President’s Commission, 2008 [1] . In a 2011 guidance on the codevelopment of therapeutics and companion diagnostics, the US FDA stated that pharmaceutical companies would increasingly adopt a more personalized approach to drug development, involving the use of biomarkers to stratify patient subpopulations [2,3] . Biomarkers can be measured to indicate disease presence or the likelihood of its development. For example, blood glucose levels are a marker for diabetes, as are blood cholesterol levels for heart disease. Diagnostic tests are used to identify and measure biomarkers. Companion diagnostics are molecular tests that stratify a patient population with respect to the likelihood of response to, or the safety of, a pharmaceutical therapy. As such, they are key tools in personalized medicine. Companion diagnostics can be codeveloped with a therapeutic, developed and launched after a drug has been approved (post hoc) or an already existing test can be repurposed for a different therapeutic [4] . Currently, there are 20 FDA-approved companion diagnostics. Furthermore, the FDA lists 136 approved products with pharmacogenomics label information [5] . Labels may denote the likelihood
10.2217/BMM.14.66 © 2015 Future Medicine Ltd
of benefit, the possibility of genetic links to side effects and ways to optimize dosing. Most labels provide information on a (possible) pharmacogenomic link. Approximately 36 of these 136 products have information on the label that either recommends or requires the use of a companion diagnostic (the FDA uses the word ‘require’; however, from a legal perspective, the FDA cannot require the use of a companion diagnostic, just as the agency cannot enforce on-label prescribing). To date, seven drug–diagnostic combinations have been codeveloped (Table 1) . When drugs and diagnostics are linked from the outset of development, the probability of therapeutic success and improved clinical efficacy and cost–effectiveness is increased [6] . Approximately 13% of the total number of drugs in the late-stage pipeline are classifiable as personalized medicines [7] . The personalized drug pipeline contains nearly 70 products in post-Phase II development. These products have been identified as medicines that will likely count as personalized once approved [7] . Approximately 50 of these pipeline drugs are antineoplastics. Scientific and developmental challenges continue to hamper efforts to expedite the personalization of therapeutics. To illustrate this point, many pharmacogenomic links, such as those included on most product labels with pharmacogenomics information, are considered investigational. This implies that the diagnostic test’s specificity and sensitivity are unknown. Here, specificity relates to a diagnostic test’s ability to exclude a condition accurately, while sensitivity relates to the test’s ability to identify
Biomark. Med. (2015) 9(1), 5–8
Joshua P Cohen Tufts Center for the Study of Drug Development, 75 Kneeland Street, Suite 1100, Boston, MA 02111, USA [email protected]
part of
ISSN 1752-0363
5
Commentary Cohen
Table 1. Seven co-developed drug/diagnostic combinations. Drug: brand (generic)
Indication
Biomarker/test
Year of approval
Herceptin (trastuzumab)
Breast cancer
HER-2
1998
Xalkori (crizotinib)
Non-small-cell lung cancer ALK
2011
Zelboraf (vemurafenib)
Melanoma
BRAF V600E
2011
Kalydeco (ivacaftor)
Cystic fibrosis
G551D
2012
Gilotrif (afatinib)
Non-small-cell lung cancer EGFR
2013
Tafinlar (dabrafenib)
Melanoma
BRAF V600E
2013
Mekinist (trametinib)
Melanoma
BRAF V600E
2013
The US FDA uses the word ‘require’. However, from a legal perspective, the FDA cannot require the use of a companion diagnostic, just as the agency cannot enforce on-label prescribing.
a condition accurately. Scientific and development challenges often translate into regulatory hurdles during the approval process. Once the scientific, development and regulatory challenges have been met, only half the battle has been won. In other words, marketing approval is (usually) a necessary condition of patient access to personalized drugs and diagnostics, but not a sufficient condition. Most patients do not pay for drugs or diagnostics out of pocket. Third-party payers reimburse the bulk of drug and diagnostic costs. Payers make their reimbursement decisions with respect to drugs and diagnostics based on a variety of data sources, including the availability of treatment alternatives, acquisition cost, clinical efficacy and cost–effectiveness, budget impact and, in the case of diagnostics, clinical utility. The latter criterion is crucial to assessing the value of companion diagnostics. Clinical utility refers to how effectively test results alter the management of the patient and whether these changes lead to clinically important improvements in health outcomes, measured in terms of the choice of a more appropriate therapy, improved survival, avoided hospitalizations and fewer physician visits, among other measures [8] . As such, generously reimbursed diagnostics tend to be those with high clinical utility (i.e., test results are expected to impact clinical decision-making and lead to improved patient outcomes based on drug selection or dosage). On the other hand, tests with low clinical utility are unlikely to change provider and patient behavior, or the specificity and sensitivity of the test may be unknown, rendering the test of little clinical utility. Ideally, a personalized drug should only be prescribed to an appropriately stratified subpopulation (identified by the companion diagnostic) and reimbursed accordingly [9] . We have seen, however, that even in the case of codevelopment, drugs are being reimbursed while some of their companion diagnostics
6
Biomark. Med. (2015) 9(1)
are not [8] . Restrictions on the reimbursement of companion diagnostics appear to be due to a lack of evidence in some instances. However, even where there is abundant evidence, limits on reimbursement occur because certain diagnostics may lack clinical utility. In other words, diagnostic tests matter to payers only insofar as they influence prescribing patterns and, in turn, impact on health outcomes. Moreover, payers are concerned about the added spending, which is a consequence of testing many individuals to identify relatively few that may benefit from a particular therapy, or from a change in dosing regimen. Policy implications Knowledge of genetic variance can guide drug development or lead to adjustments in dosing of drugs tailored to a patient’s specific set of circumstances. In turn, this may reduce the occurrence of adverse drug reactions, maximize the probability of improved health outcomes and produce cost savings. For example, prescribing crizotinib to those who express the abnormal ALK gene will likely benefit this subset of non-smallcell lung cancer patients, but those who do not express ALK should not use the drug [10] . At 20, the list of FDA-approved companion diagnostics is relatively short, and at seven, the list of codeveloped drug/diagnostic combinations is even shorter. Scientific and regulatory challenges may be holding back development. Furthermore, questions remain with respect to the clinical utility of certain companion diagnostics. The warfarin story illustrates the skepticism providers and payers have towards certain companion diagnostics. In 2009, the FDA relabeled warfarin with genomic information stating that lower doses may be more effective for patients with variations in the CYP2C9 or VKORC1 genes [11] . Warfarin’s companion diagnostics, which test for levels of CYP2C9 and VKORC1, can accurately predict bleeding risk. However, this has not
future science group
Roadblocks preventing personalized medicine from reaching its potential
led to a change in prescribing guidelines by medical specialist societies, such as the American Heart Association, due in part to the lack of sufficient data on the tests’ clinical utility. Moreover, the Centers for Medicare and Medicaid Services (CMS) decided not to routinely cover the CYP2C9 and VKORC1 tests for warfarin users. Medicare officials asserted that the “available evidence does not demonstrate that pharmacogenomic testing of CYP2C9 and VKORC1 alleles to predict warfarin responsiveness improves health outcomes in Medicare beneficiaries” [12] . Here, the issue is not the accuracy of the diagnostic test, but rather the lack of specificity regarding what physicians should do next in terms of adjusting or titrating the prescribing (i.e., dosing) regimen, whether a different anticoagulant should be prescribed or whether any of these adjustments would actually improve health outcomes.
“
Scientific and developmental challenges continue to hamper efforts to expedite the personalization of therapeutics.
”
Important changes are underway that are supportive of establishing an improved evidence base for the use of companion diagnostics, such as the warfarin companion diagnostics. First, payers are implementing coverage with evidence development programs for several diagnostic tests, including those used in conjunction with warfarin. At the time of product launch, the clinical and economic benefits of a test may not be known with great confidence. Coverage with evidence development allows for patient access to a test, contingent on real-world data collection and patient enrollment in a registry. Consequently, payers will be in a better position to make informed coverage decisions [13,14] . Second, payers have begun asking drug and diagnostic manufacturers to engage with them at Phases II and III, where they can have an impact on clinical trial design end points. As an illustration of this, in a publicly disclosed partnership, the pharmacy benefit manager Express Scripts and Sanofi work together to identify biomarkers to guide patient recruitment, collect proposed clinical end point data and data on comparators for trials and conduct postmarketing trials for certain (undisclosed) Sanofi products. In essence, pharmaceutical manufacturers are now “backing up to Phase III and asking … what payers would like to know about a drug [and its companion diagnostic], while providing outcomes and endpoints, a drug’s effect on quality of life, and results using a control rather than a placebo” [15,16] . Specifically, payers are asking manufacturers about test parameters in Phases II and III, including:
future science group
Commentary
• Which patients should be tested? • What kind of actionable information is contained in the test results and can providers and patients act on the information provided by the test? • Would changes in provider and patient behavior impact on health outcomes? • Is the test affordable, not only per unit and patient, but also if it were to be used by the entire eligible population? Third, evidence generation on the clinical efficacy and cost–effectiveness of companion diagnostics has been driving reform of the coding system for reimbursement and will continue to do so. A coding revolution of sorts began in November 2011, when Palmetto, a Medicare Part B contractor, instituted a new payment system that assigned a unique code to companion diagnostics [17,18] . Traditionally, the coding system did not uniquely identify which test was being performed. Under Palmetto’s payment system, which it calls the Molecular Diagnostic Services Program (MolDx), applicants must demonstrate that diagnostic tests make a difference (i.e., improve patient outcomes and change physician behavior with respect to the management of the patient). Palmetto’s evidence-based program has led in part to an overhaul of the Current Procedural Terminology coding system, with the creation of hundreds of new codes for companion diagnostics [19] . Beginning in 2014, all regional Medicare contractors are to assign each test a unique, analyte-specific code, analogous to International Classification of Diseases 9 codes for drugs. Each analyte-specific code is supposedly reflective of the diagnostic’s ‘value’. In turn, codes are to be priced by individual contractors in accordance with the test’s ‘value’. In conclusion, to achieve improved uptake of personalized medicines, more favorable reimbursement of companion diagnostics is needed. Accordingly, more evidence must be generated regarding the clinical efficacy and cost–effectiveness of companion diagnostics, and an improved coding system for diagnostic reimbursement must be adopted. Financial & competing interests disclosure The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
www.futuremedicine.com
7
Commentary Cohen References 1
2
8
President’s Council of Advisors on Science and Technology. Priorities for personalized medicine (2008). www.whitehouse.gov US FDA. Guidance for Industry and Food and Drug Administration Staff: in vitro companion diagnostic devices (2011). www.fda.gov
10
US FDA. FDA approves Xalkori with companion diagnostic for a type of late-stage lung cancer (2011). www.fda.gov
11
Centers for Medicare and Medicaid Services. Pharmacogenomic testing to predict warfarin responsiveness. www.cms.gov
12
Eisenberg A. Variations on a gene, and tools to find them. New York Times 27 April 2013.
3
US FDA. Paving the way for personalized medicine: FDA’s role in a new era of medical product development (2013). www.fda.gov
13
Tunis S, Pearson S. Coverage options for promising technologies: Medicare’s ‘coverage with evidence development’. Health Aff. 25(5), 1218–1230 (2006).
4
Cohen J. Overcoming regulatory and economic challenges facing pharmacogenomics. N. Biotechnol. 29(6), 751–756 (2012).
14
NIH. Reimbursement models to promote evidence generation and innovation for genomic tests (2012). www.genome.gov
5
US FDA. Table of pharmacogenomic biomarkers in drug labeling (2014). www.fda.gov
15
Twachtman G. With personalized medicine, payers want a role in early development. The Pink Sheet (2013). www.pharmamedtechbi.com
6
Reinke T. Targeted medications: new focus on companion tests. Manag. Care 21(2), 35–38 (2012).
16
7
Milne C-P, Garafalo S, Bryan C et al. et al. Trial watch: Personalized medicines in late-stage development. Nat. Rev. Drug Discov. 13, 324–325 (2014).
Edlin M. Drug manufacturers seek payer feedback. Managed Care Executive (2013). http://managedhealthcareexecutive.modernmedicine.coml
17
8
Cohen J, Felix A. Personalized medicine’s bottleneck: diagnostic test evidence and reimbursement. J. Pers. Med. 4, 163–175 (2014).
Palmetto’s Molecular Diagnostic Services Program (MolDx) program. www.palmettogba.com
18
Usdin S. Coding for utility. BioCentury 15 July 2013.
19
9
Ansari M. The regulation of companion diagnostics: a global perspective. Ther. Innovat. Reg. Sci. 47, 405–415 (2013).
Quinn B, Hoag F. Current issues and options: coverage and reimbursement for molecular diagnostics: Department of Health and Human Services (HHS) ASPE Workgroup (2011). http://aspe.hhs.gov
Biomark. Med. (2015) 9(1)
future science group
Roadblocks preventing personalized medicine from reaching its potential “… to achieve improved uptake of personalized medicines, more favorable reimbursement of companion diagnostics is needed.”
Keywords: biomarkers • clinical utility • personalized medicine • reimbursement
Personalized medicine forges ahead “Personalized medicine is tailoring medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs that are unique to each patient, but rather the ability to classify individuals into sub-populations that differ in their susceptibility to a particular disease or their response to a specific treatment.” – President’s Commission, 2008 [1] . In a 2011 guidance on the codevelopment of therapeutics and companion diagnostics, the US FDA stated that pharmaceutical companies would increasingly adopt a more personalized approach to drug development, involving the use of biomarkers to stratify patient subpopulations [2,3] . Biomarkers can be measured to indicate disease presence or the likelihood of its development. For example, blood glucose levels are a marker for diabetes, as are blood cholesterol levels for heart disease. Diagnostic tests are used to identify and measure biomarkers. Companion diagnostics are molecular tests that stratify a patient population with respect to the likelihood of response to, or the safety of, a pharmaceutical therapy. As such, they are key tools in personalized medicine. Companion diagnostics can be codeveloped with a therapeutic, developed and launched after a drug has been approved (post hoc) or an already existing test can be repurposed for a different therapeutic [4] . Currently, there are 20 FDA-approved companion diagnostics. Furthermore, the FDA lists 136 approved products with pharmacogenomics label information [5] . Labels may denote the likelihood
10.2217/BMM.14.66 © 2015 Future Medicine Ltd
of benefit, the possibility of genetic links to side effects and ways to optimize dosing. Most labels provide information on a (possible) pharmacogenomic link. Approximately 36 of these 136 products have information on the label that either recommends or requires the use of a companion diagnostic (the FDA uses the word ‘require’; however, from a legal perspective, the FDA cannot require the use of a companion diagnostic, just as the agency cannot enforce on-label prescribing). To date, seven drug–diagnostic combinations have been codeveloped (Table 1) . When drugs and diagnostics are linked from the outset of development, the probability of therapeutic success and improved clinical efficacy and cost–effectiveness is increased [6] . Approximately 13% of the total number of drugs in the late-stage pipeline are classifiable as personalized medicines [7] . The personalized drug pipeline contains nearly 70 products in post-Phase II development. These products have been identified as medicines that will likely count as personalized once approved [7] . Approximately 50 of these pipeline drugs are antineoplastics. Scientific and developmental challenges continue to hamper efforts to expedite the personalization of therapeutics. To illustrate this point, many pharmacogenomic links, such as those included on most product labels with pharmacogenomics information, are considered investigational. This implies that the diagnostic test’s specificity and sensitivity are unknown. Here, specificity relates to a diagnostic test’s ability to exclude a condition accurately, while sensitivity relates to the test’s ability to identify
Biomark. Med. (2015) 9(1), 5–8
Joshua P Cohen Tufts Center for the Study of Drug Development, 75 Kneeland Street, Suite 1100, Boston, MA 02111, USA [email protected]
part of
ISSN 1752-0363
5
Commentary Cohen
Table 1. Seven co-developed drug/diagnostic combinations. Drug: brand (generic)
Indication
Biomarker/test
Year of approval
Herceptin (trastuzumab)
Breast cancer
HER-2
1998
Xalkori (crizotinib)
Non-small-cell lung cancer ALK
2011
Zelboraf (vemurafenib)
Melanoma
BRAF V600E
2011
Kalydeco (ivacaftor)
Cystic fibrosis
G551D
2012
Gilotrif (afatinib)
Non-small-cell lung cancer EGFR
2013
Tafinlar (dabrafenib)
Melanoma
BRAF V600E
2013
Mekinist (trametinib)
Melanoma
BRAF V600E
2013
The US FDA uses the word ‘require’. However, from a legal perspective, the FDA cannot require the use of a companion diagnostic, just as the agency cannot enforce on-label prescribing.
a condition accurately. Scientific and development challenges often translate into regulatory hurdles during the approval process. Once the scientific, development and regulatory challenges have been met, only half the battle has been won. In other words, marketing approval is (usually) a necessary condition of patient access to personalized drugs and diagnostics, but not a sufficient condition. Most patients do not pay for drugs or diagnostics out of pocket. Third-party payers reimburse the bulk of drug and diagnostic costs. Payers make their reimbursement decisions with respect to drugs and diagnostics based on a variety of data sources, including the availability of treatment alternatives, acquisition cost, clinical efficacy and cost–effectiveness, budget impact and, in the case of diagnostics, clinical utility. The latter criterion is crucial to assessing the value of companion diagnostics. Clinical utility refers to how effectively test results alter the management of the patient and whether these changes lead to clinically important improvements in health outcomes, measured in terms of the choice of a more appropriate therapy, improved survival, avoided hospitalizations and fewer physician visits, among other measures [8] . As such, generously reimbursed diagnostics tend to be those with high clinical utility (i.e., test results are expected to impact clinical decision-making and lead to improved patient outcomes based on drug selection or dosage). On the other hand, tests with low clinical utility are unlikely to change provider and patient behavior, or the specificity and sensitivity of the test may be unknown, rendering the test of little clinical utility. Ideally, a personalized drug should only be prescribed to an appropriately stratified subpopulation (identified by the companion diagnostic) and reimbursed accordingly [9] . We have seen, however, that even in the case of codevelopment, drugs are being reimbursed while some of their companion diagnostics
6
Biomark. Med. (2015) 9(1)
are not [8] . Restrictions on the reimbursement of companion diagnostics appear to be due to a lack of evidence in some instances. However, even where there is abundant evidence, limits on reimbursement occur because certain diagnostics may lack clinical utility. In other words, diagnostic tests matter to payers only insofar as they influence prescribing patterns and, in turn, impact on health outcomes. Moreover, payers are concerned about the added spending, which is a consequence of testing many individuals to identify relatively few that may benefit from a particular therapy, or from a change in dosing regimen. Policy implications Knowledge of genetic variance can guide drug development or lead to adjustments in dosing of drugs tailored to a patient’s specific set of circumstances. In turn, this may reduce the occurrence of adverse drug reactions, maximize the probability of improved health outcomes and produce cost savings. For example, prescribing crizotinib to those who express the abnormal ALK gene will likely benefit this subset of non-smallcell lung cancer patients, but those who do not express ALK should not use the drug [10] . At 20, the list of FDA-approved companion diagnostics is relatively short, and at seven, the list of codeveloped drug/diagnostic combinations is even shorter. Scientific and regulatory challenges may be holding back development. Furthermore, questions remain with respect to the clinical utility of certain companion diagnostics. The warfarin story illustrates the skepticism providers and payers have towards certain companion diagnostics. In 2009, the FDA relabeled warfarin with genomic information stating that lower doses may be more effective for patients with variations in the CYP2C9 or VKORC1 genes [11] . Warfarin’s companion diagnostics, which test for levels of CYP2C9 and VKORC1, can accurately predict bleeding risk. However, this has not
future science group
Roadblocks preventing personalized medicine from reaching its potential
led to a change in prescribing guidelines by medical specialist societies, such as the American Heart Association, due in part to the lack of sufficient data on the tests’ clinical utility. Moreover, the Centers for Medicare and Medicaid Services (CMS) decided not to routinely cover the CYP2C9 and VKORC1 tests for warfarin users. Medicare officials asserted that the “available evidence does not demonstrate that pharmacogenomic testing of CYP2C9 and VKORC1 alleles to predict warfarin responsiveness improves health outcomes in Medicare beneficiaries” [12] . Here, the issue is not the accuracy of the diagnostic test, but rather the lack of specificity regarding what physicians should do next in terms of adjusting or titrating the prescribing (i.e., dosing) regimen, whether a different anticoagulant should be prescribed or whether any of these adjustments would actually improve health outcomes.
“
Scientific and developmental challenges continue to hamper efforts to expedite the personalization of therapeutics.
”
Important changes are underway that are supportive of establishing an improved evidence base for the use of companion diagnostics, such as the warfarin companion diagnostics. First, payers are implementing coverage with evidence development programs for several diagnostic tests, including those used in conjunction with warfarin. At the time of product launch, the clinical and economic benefits of a test may not be known with great confidence. Coverage with evidence development allows for patient access to a test, contingent on real-world data collection and patient enrollment in a registry. Consequently, payers will be in a better position to make informed coverage decisions [13,14] . Second, payers have begun asking drug and diagnostic manufacturers to engage with them at Phases II and III, where they can have an impact on clinical trial design end points. As an illustration of this, in a publicly disclosed partnership, the pharmacy benefit manager Express Scripts and Sanofi work together to identify biomarkers to guide patient recruitment, collect proposed clinical end point data and data on comparators for trials and conduct postmarketing trials for certain (undisclosed) Sanofi products. In essence, pharmaceutical manufacturers are now “backing up to Phase III and asking … what payers would like to know about a drug [and its companion diagnostic], while providing outcomes and endpoints, a drug’s effect on quality of life, and results using a control rather than a placebo” [15,16] . Specifically, payers are asking manufacturers about test parameters in Phases II and III, including:
future science group
Commentary
• Which patients should be tested? • What kind of actionable information is contained in the test results and can providers and patients act on the information provided by the test? • Would changes in provider and patient behavior impact on health outcomes? • Is the test affordable, not only per unit and patient, but also if it were to be used by the entire eligible population? Third, evidence generation on the clinical efficacy and cost–effectiveness of companion diagnostics has been driving reform of the coding system for reimbursement and will continue to do so. A coding revolution of sorts began in November 2011, when Palmetto, a Medicare Part B contractor, instituted a new payment system that assigned a unique code to companion diagnostics [17,18] . Traditionally, the coding system did not uniquely identify which test was being performed. Under Palmetto’s payment system, which it calls the Molecular Diagnostic Services Program (MolDx), applicants must demonstrate that diagnostic tests make a difference (i.e., improve patient outcomes and change physician behavior with respect to the management of the patient). Palmetto’s evidence-based program has led in part to an overhaul of the Current Procedural Terminology coding system, with the creation of hundreds of new codes for companion diagnostics [19] . Beginning in 2014, all regional Medicare contractors are to assign each test a unique, analyte-specific code, analogous to International Classification of Diseases 9 codes for drugs. Each analyte-specific code is supposedly reflective of the diagnostic’s ‘value’. In turn, codes are to be priced by individual contractors in accordance with the test’s ‘value’. In conclusion, to achieve improved uptake of personalized medicines, more favorable reimbursement of companion diagnostics is needed. Accordingly, more evidence must be generated regarding the clinical efficacy and cost–effectiveness of companion diagnostics, and an improved coding system for diagnostic reimbursement must be adopted. Financial & competing interests disclosure The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
www.futuremedicine.com
7
Commentary Cohen References 1
2
8
President’s Council of Advisors on Science and Technology. Priorities for personalized medicine (2008). www.whitehouse.gov US FDA. Guidance for Industry and Food and Drug Administration Staff: in vitro companion diagnostic devices (2011). www.fda.gov
10
US FDA. FDA approves Xalkori with companion diagnostic for a type of late-stage lung cancer (2011). www.fda.gov
11
Centers for Medicare and Medicaid Services. Pharmacogenomic testing to predict warfarin responsiveness. www.cms.gov
12
Eisenberg A. Variations on a gene, and tools to find them. New York Times 27 April 2013.
3
US FDA. Paving the way for personalized medicine: FDA’s role in a new era of medical product development (2013). www.fda.gov
13
Tunis S, Pearson S. Coverage options for promising technologies: Medicare’s ‘coverage with evidence development’. Health Aff. 25(5), 1218–1230 (2006).
4
Cohen J. Overcoming regulatory and economic challenges facing pharmacogenomics. N. Biotechnol. 29(6), 751–756 (2012).
14
NIH. Reimbursement models to promote evidence generation and innovation for genomic tests (2012). www.genome.gov
5
US FDA. Table of pharmacogenomic biomarkers in drug labeling (2014). www.fda.gov
15
Twachtman G. With personalized medicine, payers want a role in early development. The Pink Sheet (2013). www.pharmamedtechbi.com
6
Reinke T. Targeted medications: new focus on companion tests. Manag. Care 21(2), 35–38 (2012).
16
7
Milne C-P, Garafalo S, Bryan C et al. et al. Trial watch: Personalized medicines in late-stage development. Nat. Rev. Drug Discov. 13, 324–325 (2014).
Edlin M. Drug manufacturers seek payer feedback. Managed Care Executive (2013). http://managedhealthcareexecutive.modernmedicine.coml
17
8
Cohen J, Felix A. Personalized medicine’s bottleneck: diagnostic test evidence and reimbursement. J. Pers. Med. 4, 163–175 (2014).
Palmetto’s Molecular Diagnostic Services Program (MolDx) program. www.palmettogba.com
18
Usdin S. Coding for utility. BioCentury 15 July 2013.
19
9
Ansari M. The regulation of companion diagnostics: a global perspective. Ther. Innovat. Reg. Sci. 47, 405–415 (2013).
Quinn B, Hoag F. Current issues and options: coverage and reimbursement for molecular diagnostics: Department of Health and Human Services (HHS) ASPE Workgroup (2011). http://aspe.hhs.gov
Biomark. Med. (2015) 9(1)
future science group
