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Kathryn A. Phillips The Intersection Of Biotechnology And Pharmacogenomics: Health Policy Implications Health Affairs, September/October 2006; 25(5): 1271-1280. [Abstract] [Full Text] [PDF] [Reprints & Permissions]

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Potential Benefits of Pharmacogenomics Technologies

Christine C. Huttin, John Vernon, UConn/NBER   ( 12 March 2007 )

Potential Benefits of Pharmacogenomics Technologies 12 March 2007
Christine C. Huttin, Professor and health scientist ENDEPUS Research Inc. and ENDEP, University Paul Cezanne (Aix en Provence), John Vernon, UConn/NBER Send comment to journal: Re: Potential Benefits of Pharmacogenomics Technologies chris.huttin{at}comcast.net Christine C. Huttin, et al.	The economic effects of pharmacogenomics are questionable: on one hand, these technologies may lead to substantial reductions in the number of patients with reliable markers; on the other hand, biomarkers can speed up the drug and development process and reduce the costs of bringing a new drug to market (Vernon and Hughen, 2005, 2006). Since this science is poised to revolutionize not only drug discovery but also the economics of insurance, both industry and third-party payers need to defend their economic interests. Critical divergences exist in stakeholders’ economic incentives with respect to the use of biomarkers (and their ability to predict drug response) for policy purposes (Huttin, 2003, 2005). The analytical framework of the paper by Phillips includes four factors that facilitate diffusion of biotech products: (1) the nature of the disease (if a disease is life threatening or has a large target population or high market potential, it is more likely that the diffusion will be quicker); (2) regulation; (3) the value of coverage and reimbursement; and (4) the ability to integrate diagnostics and pharmaceuticals. The author describes several success stories, but her review of cases such as Herceptin, Gleevec, and CYP450 show quite inconclusive evidence of substantial benefits. Her comments are mainly based on evidence provided by FDA and CMS and for the U.S. market. It is not clear that all the relevant cost-effectiveness studies are reviewed (e.g. from international trials or Phase IV studies). Moreover, Phillips does not discuss recent changes of FDA policy to produce new evidence to encourage the process of innovation (evidence in development). Such programmes could possibly change the time frame for evaluating such technologies with limited evidence. Furthermore, the exclusive provision of evidence from the U.S. market limits the potential viability of such technologies. The author does not consider the way such technologies are assessed internationally and how major companies diffuse them in regional markets and approach medical agencies around the world. The diffusion of cost-effectiveness studies remains limited in many countries, and when technologies are sold to niche markets, they require even more attention to ensure that medical staff may consider them as a priority in their review of listing diagnostics, medicines, or other products coming from such technologies. This is particularly the case for trastuzumab (Herceptin) in many European and Middle East markets, where this product adoption was more dependent on efficient training and diffusion of knowledge of cost-effectiveness data than strong economic evidence. It is also hard to identify whether the author's positions on the limited number of current success stories are more due to her lack of access to scientific evidence or the political context that questions the viable economics of more segmented or niche markets especially in the U.S., Europe, and Japan. To communicate or not conclusive evidence is a major political tool for companies, especially if they believe communication of such information stands to harm their commercial interests. Moreover, recent controversy between conventional pharmacogenomics versus use of metabonomics that better integrate system biologics also questions potential positive effects of current pharmacogenomics technologies (Clayton, Lindon, and O’Cloarec, 2006). However, even if current benefits of pharmacogenomics are still limited, access to increased knowledge on individual genetic profiles may in the future provide different bargaining arguments with governmental agencies and payers for the use of more efficient predictive treatment protocols. Governmental agencies facing major transitions in health care financing systems are very sensitive to medical evidence on the lack of treatment efficiency in drug response, and/or the resistance to existing treatments for a substantial proportion of patients. We argue that in the context of major health care financing reforms, such as in the U.S. MMA legislation or the European delisting policies of national formularies, it is very timely to promote evidence on how pharmacogenomic technologies may contribute to optimize drug benefit coverage. They may require better ways to develop a communication strategy or to present strategic interests of various stakeholders. We propose, for instance, integrating and promoting the benefits of such new technologies for existing medicines, and not only for new medicines in order to be more influential on health decisionmakers who make decisions on global budgeting. To illustrate our point, we consider two case studies in pharmacogenomics advances that may allow optimizing drug budgets now covered by the new Medicare drug benefit in place in 2006: Warfarin and asthma corticosteroids. Warfarin: Anticoagulation therapy presents an interesting set of diagnostic and treatment options (e.g. INR and genetic tests) in a context of rapid advances in pharmacogenomics to identify safe and efficacious doses especially for the elderly (Eichelbaum et al. 2006). However, this drug has been controversial for many years because of the high risk of bleeding (leading to it total exclusion from some national formularies, such as in France). Advances in pharmacogenomics in that case may lead to circumvent the life-threatening side effects for patients at risk. Daly et al., for instance, in the U.K. conducted a trial on Warfarin and the effect of CYP2C polymorphism, with possible review by NICE to demonstrate the interest of biomarkers to better control bleeding risks and possible increase of emergency hospital budgets. This medicine presents a major case study to review the current policy issues around genotyping, new genetic tests in clinical practice (William, Lutter, and Nardinelli, 2006) and the effects on the economics of pharmaceutical markets, including budget optimization for both new and current medicines. In the U.S., it could address some costs associated with the emergency medicine crisis (Twanmoh and Cunningham, 2006). Asthma corticosteroids: A case study on the economics of pharmacogenomics technology on asthma in elderly patients can be also very useful for the current policy agenda even if asthma prevalence is higher for younger generations. The epidemic has been increasing for 20 years, and delays in diagnosis and pharmacotherapy may also lead to substantial increases in the number of chronic cases instead of acute patients and increased complications (especially with COPD). Moreover, the estimated cost for adverse drug reactions is over $100 billion in the U.S. and over 100,000 deaths a year. Genetics can explain from 20 to 95 percent of the variability in drug disposition. According to Hawkins et al. (2005), the number of nonresponders to current asthma drug therapy can reach up to half of asthmatic patients for B2 antagonists or inhaled corticosteroids. The case study on asthma also provides a good example of the importance of epigenetics as well as conventional pharmacogenomics studies to ensure the production of reliable biomarkers (Ober and Thompson, 2005). Statistical significance advances are available through this case study for instance to show how a better understanding of the interactions of environmental factors and genes can reduce the number of false positives in study designs -- for example, the impact of the environmental level of antitoxin exposure on CD14 genotype in Baldini and Vercelli (2003) or Vercelli (2003). Due to the uncertainties around the economics of pharmacogenomics, policymakers tend to favor the use of case studies to initiate new policy for using them in clinical practice. The context of the new Medicare drug legislation could largely benefit from such initiatives in areas where reliable biomarkers could help optimize the use of drugs in elderly populations. The two examples discussed in this letter show how they can be useful either to changes in the type of economic arguments between insurers/payers and industry or to ways of promoting scientific advances toward reliable biomarkers. An international collaboration, for instance, between the U.S. and Europe on this topic may contribute to the policy debate: European systems are driven more by budget savings. They tend to invest more in postmarketing studies, such as Warfarin, to show the benefits of using reliable biomarkers on drugs that have been on the market for a long time. On the contrary, in the U.S., the focus has mainly been so far on the economics of drug development and new drug promotion. It could be useful to establish a center for policymakers, to inform negotiating bodies and ethics committees on the effects of such advances, especially in the context of complex clinical stages of chronic diseases. Relevant references Baldini M, Vercelli D, Martinez FD. CD14: an example of gene by environment interaction in allergic disease. Allergy 2002, 57:188-192. Clayton TA, Lindon JC , O Cloarec et al. Pharmaco-metabonomics: a new approach to personalizing drug treatment, Presentation to the Metabonomic Society meeting, June 2006. Daly AK, King BP. Contribution of CYP2C9 to variability in vitamin K antagonist metabolism. Expert Opin Drug Metab Toxicol. 2006 Feb; 2(1): 3-15. Eichelbaum M, Ingelman-Sundberg M, Evans WE. Pharmacogenomics and individualized drug therapy. Annu Rev Med 2006. 57:119-37. Hawkins GA et al. Asthma pharmacogenomics, Immunology Allergy Clin N Am 25 (2005) 723-742. Huttin C. Pharmacogenomic technologies and the health industry model, Journal of Biolaw and Business, vol 8, n.4, 2005. Huttin C. Strategic decisions and pharmacogenomics, Journal of Biolaw and Business, December 2003, 61-64. McWilliam A, Lutter R, Nardinelli C. Health care savings from personalizing medicine using genetic testing: the case of Warfarin. AEI-Brookings Joint Center for Regulatory Studies, Working Paper 6-23, November 2006. Ober C and Thompson EE. Rethinking genetic models of asthma: the role of environmental modifiers. Current Opinion in Immunology 2005, 17:670-678. Twanmoh JR, Cunningham GP. When overcrowding paralyzes an emergency department. Managed Care 2006 Jun, 15 (6): 54-9. Vercelli D. Learning from discrepancies: CD14 polymorphisms, atopy and the endotoxin switch. Clin Exp Allergy 2003. Vernon JA and Hughen WK. The future of drug development: the economics of pharmacogenomics. Working paper, NBER, 11875, December 2005. Vernon JA, Johnson SJ, Hughen WK, Trujillo A. Economic and development considerations for pharmacogenomics technology. Pharmacoeconomics 2006;24(5):335-43.