R

1
RD Investments in Pharmaceutical Markets

• Abdulkadir Civan
• Fatih University

2
Research Agenda

• Determinants of Pharmaceutical RD Investments
  Potential Profits(Civan and Maloney 2006, 2009)
• Benefits of Pharmaceutical RD Investments
  Improve Health and Reduce Health Care Costs
  (Civan and Koksal 2009)
• Methods of Increasing Pharmaceutical RD
  Investments (Civan and Maloney Work in Progress)

3
Benefits of Pharmaceutical RD Investments

• Too much or too little RD?
• Are the patent length and height at the optimum
  level?
• Theoretical studies are unlikely to answer those
  questions.

4
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)

5
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.

6
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.

7
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.

8
Determinants of Pharmaceutical RD

• 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.

9
Current Study

• 1) Focuses on DALY rather than mortality.
• WHOs 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
  RD.

10
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.

11
Table 5. Effects of DALYs on Pharmaceutical RD by Income
  1 1   2 2
High Income Countries DALY 2.60E-07   1.69E-07
High Income Countries DALY 2.43   3.27  
Middle Income Countries DALY -1.13E-07   -1.27E-07
Middle Income Countries DALY -1.71   -4.62  
Low Income Countries DALY 2.34E-09   3.32E-08
Low Income Countries DALY 0.18   4.17  
Property Rights Index     1.590573
Property Rights Index     7.71  
Constant 3.534302 -1.786302
Constant 16.9   -2.57  
Number of obs. 79     78  
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. 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. 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. 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. 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. 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.
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Table 6. Effects of DALYs on Pharmacuetical RD by Subregions
  1 1   2 2
Developed Countries DALY 6.86E-07 3.43E-07
Developed Countries DALY 3.18   2.08  
South-eastern Europe DALY -3.47E-06   -2.56E-06  
South-eastern Europe DALY -1.47   -1.23  
CIS DALY -2.84E-07   -1.68E-07  
CIS DALY -1.09   -0.83  
Northern Africa DALY -3.75E-06 -2.79E-06
Northern Africa DALY -1.98   -1.66  
Sub-Saharan Africa -4.50E-08   -2.38E-08  
Sub-Saharan Africa -1.3   -1.06  
Caribbean DALY 9.19E-06   9.59E-06
Caribbean DALY 1.5   2.6  
Latin America DALY -6.33E-07   -6.70E-07  
Latin America DALY -0.85   -1.24  
Eastern Asia DALY -1.67E-07 -1.47E-07
Eastern Asia DALY -2.11   -2.51  
Southern Asia DALY -2.66E-07 -2.46E-07
Southern Asia DALY -2.9   -3.47  
South-eastern Asia DALY 5.26E-07   4.64E-07  
South-eastern Asia DALY 0.93   1.52  
Western Asia DALY 4.04E-06 3.20E-06
Western Asia DALY 3.11   2.62  
Oceania DALY 0.0000107   0.0000184
Oceania DALY 0.88   2.7  
Property Rights Index     1.429837
Property Rights Index     6.37  
Constant 3.161094 1.566323
Constant 14.71   -2.02  
Number of obs. 79     78  
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. 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. 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. 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. 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. 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.
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Table 7. Effects of DALYs on Pharmacuetical RD by Regions
  1 1   2 2
AmericaEurope DALY 2.17E-07 1.19E-07
AmericaEurope DALY 2.3   2.16  
Africa DALY 2.03E-08   5.22E-08
Africa DALY 1.11   4.53  
Eastern Mediterrenean DALY 1.16E-07   1.66E-08  
Eastern Mediterrenean DALY 0.44   0.09  
Southeast Asia DALY -1.16E-07   -3.59E-08  
Southeast Asia DALY -0.87   -0.4  
Western Pacific DALY -8.65E-08   -1.11E-07
Western Pacific DALY -0.75   -1.77  
Property Rights Index     1.615017
Property Rights Index     7.43  
Constant 3.543168 -1.860474
Constant 17.09   -2.57  
Number of obs. 79     78  
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. 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. 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. 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. 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. 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.
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Table 8. Effects of FDA Approval Process on Pharmacuetical RD by Income
  1 1   2 2
High Income Countries DALY 8.67E-08 6.76E-08
High Income Countries DALY 2.04   2.51  
Middle Income Countries DALY -6.27E-08   -8.67E-08
Middle Income Countries DALY -2.13   -2.16  
Low Income Countries DALY 1.56E-09   3.13E-08
Low Income Countries DALY 0.25   2.08  
Property Rights Index     1.551528
Property Rights Index     2.27  
FDA Approval Length     -0.0006072  
FDA Approval Length     -1.35  
Constant 4.203138 -0.9472049  
Constant 20.55   -0.38  
Number of obs. 32     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. 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. 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. 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. 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. 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.
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Table 9. Effects of FDA Approval Process on Pharmacuetical RD by Subregions
  1 1   2 2
Developed Countries DALY 5.14E-07   3.37E-07  
Developed Countries DALY 1.84   2.01
South-eastern Europe DALY -9.67E-06 -1.09E-05  
South-eastern Europe DALY -2.43   -3.06
CIS DALY 4.23E-07 6.39E-07  
CIS DALY 2.22   3.16
Northern Africa DALY -2.97E-06   -2.41E-06  
Northern Africa DALY -1.58   -1.44  
Sub-Saharan Africa 6.24E-08   5.19E-08  
Sub-Saharan Africa 1.53   1.61  
Caribbean DALY -8.70E-06   -1.12E-05  
Caribbean DALY -1.07   -1.24  
Latin America DALY 5.36E-07   1.06E-06  
Latin America DALY 0.85   1.68
Eastern Asia DALY -1.14E-07   -1.77E-07  
Eastern Asia DALY -1.11   -1.94
Southern Asia DALY -3.71E-07 -3.05E-07  
Southern Asia DALY -3.54   -3.36
South-eastern Asia DALY 5.63E-07   9.03E-07  
South-eastern Asia DALY 1.12   2.08
Western Asia DALY 4.87E-06 2.38E-06  
Western Asia DALY 2.84   1.27  
Oceania DALY 8.23E-06   0.0000335  
Oceania DALY 0.2   0.97  
Property Rights Index     1.485386
Property Rights Index     2.55  
FDA Approval Length     -0.0014042
FDA Approval Length     -3.36  
Constant 3.765198 -0.7990164  
Constant 14.85   -0.39  
Number of obs. 32     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. 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. 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. 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. 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. 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.
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Table 10. Effects of FDA Approval Process on Pharmacuetical RD by Regions
  1 1   2 2
AmericaEurope DALY 1.83E-07 1.28E-07
AmericaEurope DALY 5.49   3.01  
Africa DALY 4.07E-08 4.89E-08
Africa DALY 4.72   3.47  
Eastern Mediterrenean DALY 8.15E-07 5.84E-07
Eastern Mediterrenean DALY 4.95   2.58  
Southeast Asia DALY -4.65E-07 -3.11E-07
Southeast Asia DALY -5.03   -2.36  
Western Pacific DALY 1.23E-07 5.47E-08  
Western Pacific DALY 2.12   0.64  
Property Rights Index     1.090278  
Property Rights Index     1.39  
FDA Approval Length     -0.0006514  
FDA Approval Length     -1.59  
Constant 3.851634 0.4151548  
Constant 17.54   0.15  
Number of obs. 32     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. 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. 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. 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. 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. 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.