R&D Investments in Pharmaceutical Markets Abdulkadir Civan Fatih University

Research Agenda 1)Determinants of Pharmaceutical R&D Investments: Potential Profits(Civan and Maloney; 2006, 2009) 2)Benefits of Pharmaceutical R&D Investments: Improve Health and Reduce Health Care Costs (Civan and Koksal; 2009) 3.Methods of Increasing Pharmaceutical R&D Investments: (Civan and Maloney; Work in Progress)

Benefits of Pharmaceutical R&D Investments Too much or too little R&D? Are the patent length and height at the optimum level? Theoretical studies are unlikely to answer those questions.

Two potential effects of innovation in pharmaceutical markets: 1) New drugs enlarge the market size. (improve health outcomes) 2) Influence the health care costs. a) Increase the costs since they are more expensive. b) Decrease the costs since they reduce the demand for other health care services. (hospital, physician etc…)

The effect of utilization of new drugs on health care expenditures (Civan &Koksal, 2009) US Census Region Level Health Care data. The proxy for the utilization of newer drugs: The average age of active ingredients in prescribed drugs in each census region.

Empirical Methodology HCE: per capita real health care expenditure for each category; Drug age: the weighted average age of the active ingredients as described in the previous section; GSP : the per capita real gross state product; GovIns and PrivIns: the government and private insurance coverage; Over65 : the percentage of the population over age 65.

Conclusion The new drugs are so effective They increase drug expenditures but they reduce total health expenditures. Also other researchers showed that new drugs improve health outcomes. We can almost certainly conclude that there is less than efficient amount of innovation in pharmaceutical markets.

Determinants of Pharmaceutical R&D Civan and Maloney(2006): Potential market size:  If a disease is killing a lot of people,  If a disease is killing a lot of wealthy people,  If a disease is killing a lot of people who live in business friendly countries. Pharmaceutical companies heavily invest on that disease. Because, current treatments are  Not effective  Very expensive  Have bad side effects. Thus there is a high profit potential for the new and better drugs.

Current Study 1) Focuses on DALY rather than mortality. WHO’s definition of DALY: Disability-adjusted life year (DALY): A Time-based measure that combines years of life lost due to premature mortality and years of life lost due to time lived in states of less than full health. 2) Uses a better index for business friendliness of the country. Instead of generic freedom index by Heritage Foundation, we use country index of intellectual property rights in pharmaceutical innovations by Liu and Croix (2008) 3) Uses more disaggregated DALY data. 4) Looks at the effect of FDA approval process on R&D.

Dependent Variable: Number of drugs in the pipeline. The Pharmaceutical Research and Manufacturers of America (PhRMA) posts that information on its web site. Normally only a small percentage of drugs which are initially considered reaches the market. Many of them fail because FDA believes they are not safe and/or effective. The estimates of the average cost of introducing a drug to the market range between couple of hundred million dollars to the couple of billion dollars.

Table 5. Effects of DALYs on Pharmaceutical R&D by Income 1 2 High Income Countries DALY 2.60E-07** 1.69E-07*** [2.43] [3.27] Middle Income Countries DALY -1.13E-07* -1.27E-07*** [-1.71] [-4.62] Low Income Countries DALY 2.34E E-08*** [0.18] [4.17] Property Rights Index *** [7.71] Constant *** *** [16.9] [-2.57] Number of obs Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.

Table 6. Effects of DALYs on Pharmacuetical R&D by Subregions 1 2 Developed Countries DALY 6.86E-07***3.43E-07** [3.18] [2.08] South-eastern Europe DALY -3.47E E-06 [-1.47] [-1.23] CIS DALY -2.84E E-07 [-1.09] [-0.83] Northern Africa DALY -3.75E-06**-2.79E-06* [-1.98] [-1.66] Sub-Saharan Africa -4.50E E-08 [-1.3] [-1.06] Caribbean DALY 9.19E E-06*** [1.5] [2.6] Latin America DALY -6.33E E-07 [-0.85] [-1.24] Eastern Asia DALY -1.67E-07**-1.47E-07** [-2.11] [-2.51] Southern Asia DALY -2.66E-07***-2.46E-07*** [-2.9] [-3.47] South-eastern Asia DALY 5.26E E-07 [0.93] [1.52] Western Asia DALY 4.04E-06***3.20E-06*** [3.11] [2.62] Oceania DALY *** [0.88] [2.7] Property Rights Index *** [6.37] Constant *** ** [14.71] [-2.02] Number of obs Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.

Table 7. Effects of DALYs on Pharmacuetical R&D by Regions 1 2 America+Europe DALY 2.17E-07**1.19E-07** [2.3] [2.16] Africa DALY 2.03E E-08*** [1.11] [4.53] Eastern Mediterrenean DALY 1.16E E-08 [0.44] [0.09] Southeast Asia DALY -1.16E E-08 [-0.87] [-0.4] Western Pacific DALY -8.65E E-07* [-0.75] [-1.77] Property Rights Index *** [7.43] Constant *** *** [17.09] [-2.57] Number of obs Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.

Table 8. Effects of FDA Approval Process on Pharmacuetical R&D by Income 1 2 High Income Countries DALY 8.67E-08**6.76E-08** [2.04] [2.51] Middle Income Countries DALY -6.27E-08** -8.67E-08** [-2.13] [-2.16] Low Income Countries DALY 1.56E E-08** [0.25] [2.08] Property Rights Index ** [2.27] FDA Approval Length [-1.35] Constant *** [20.55] [-0.38] Number of obs. 32 Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.

Table 9. Effects of FDA Approval Process on Pharmacuetical R&D by Subregions 1 2 Developed Countries DALY 5.14E-07* 3.37E-07 [1.84] [2.01] ** South-eastern Europe DALY -9.67E-06**-1.09E-05 [-2.43] [-3.06] *** CIS DALY 4.23E-07**6.39E-07 [2.22] [3.16] *** Northern Africa DALY -2.97E E-06 [-1.58] [-1.44] Sub-Saharan Africa 6.24E E-08 [1.53] [1.61] Caribbean DALY -8.70E E-05 [-1.07] [-1.24] Latin America DALY 5.36E E-06 [0.85] [1.68] * Eastern Asia DALY -1.14E E-07 [-1.11] [-1.94] * Southern Asia DALY -3.71E-07***-3.05E-07 [-3.54] [-3.36] *** South-eastern Asia DALY 5.63E E-07 [1.12] [2.08} ** Western Asia DALY 4.87E-06***2.38E-06 [2.84] [1.27} Oceania DALY 8.23E [0.2] [0.97] Property Rights Index ** [2.55] FDA Approval Length *** [-3.36] Constant *** [14.85] [-0.39] Number of obs. 32 Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.

Table 10. Effects of FDA Approval Process on Pharmacuetical R&D by Regions 1 2 America+Europe DALY 1.83E-07***1.28E-07*** [5.49] [3.01] Africa DALY 4.07E-08***4.89E-08*** [4.72] [3.47] Eastern Mediterrenean DALY 8.15E-07***5.84E-07*** [4.95] [2.58] Southeast Asia DALY -4.65E-07***-3.11E-07** [-5.03] [-2.36] Western Pacific DALY 1.23E-07**5.47E-08 [2.12] [0.64] Property Rights Index [1.39] FDA Approval Length [-1.59] Constant *** [17.54] [0.15] Number of obs. 32 Dependent Variable is the number of drugs in the pipeline for each disease category. Negative binomial method is used and robust standard errors are reported in parentheses. ***, ** and * denotes significance levels at the 1%, 5% and 10% levels, respectively.