The PAHO model for estimating the impact of changes

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The PAHO model for estimating the impact of changes Powered By Docstoc
					The PAHO model for estimating
    the impact of changes in
  Intellectual Property Rights

 Joan Rovira, Universitat de Barcelona
 Ismail Abbas, Universitat Politècnica de Catalunya
                    Content
1.   Justification and objectives of the
     project
2.   Model specification and description
3.   Illustrative results for Colombia and
     Malaysia
4.   Discussion


Acknowledgement:
This project has been funded by the PAHO-WHO


                                               2
Justification and objectives
        of the project



                               3
    The changing environment
         of IPR regimes
   Global trends and pressures towards an
    international upwards harmonization of
    IPR to developed countries’ standards
   Regional agreements: Single European
    Market-EU, NAFTA
   The TRIPS agreement
   Bilateral agreements
   National implementation of agreements
    and other policies

                                             4
        The impact of changes in
     IPR regimes might affect, with
      varying levels of uncertainty:
   Market exclusivity - competition
   Prices
   Expenditure
   Consumption – access – health
   Foreign investment
   Domestic production, employment
   Imports – exports - balance of trade
   R&D and innovation (global and domestic;
    general and on country-specific diseases)
   Technology transfer
                                                5
        The timing of the impacts of
         changes in IPR provisions
   Short-term
       Test data exclusivity
       Conditions for compulsory licensing
       Date of enforcement, transitory periods
       ...
   Long term
    (we’ll all be dead, according to J M Keynes?)
      Duration of patent (>20years)
      Scope of patentability
      ...

                                                    6
    Information needs of decision-makers

   Decision-makers, such as the negotiators of a trade
    agreement, must often consider and take quick decisions
    on proposals related to IPR, which might have a substantial
    impact on the future access to pharmaceuticals and,
    ultimately, on the health status in their countries.
   Although it is increasingly apparent to most developing
    countries’ negotiators that stronger (TRIPS plus) patent
    protection is likely to have negative net effects on drug
    accessibility and health status, trade agreements often
    require trade-offs in a given sector in order to obtain
    advantages (e.g. tariff reductions to agricultural exports) in
    other sectors.
   If concessions have to be considered or made in a given
    sector, it is important to be able to identify and quantify as
    precisely as possible the future impact, in order to compare
    it with the expected benefits from other sectors.
                                                                     7
      Objectives of the project
   To develop a user-friendly tool for
    decision-makers that allows them to
    estimate the future impact of changes in
    IPR and related pharmaceutical policies
   To collect the required information,
    implement and test the model in several
    countries (initially, Colombia, Costa Rica
    and Guatemala, later Malaysia, Vietnam,
    India, … )
   To assess the information and knowledge
    gaps and to propose an agenda for future
    research                                   8
Model specification
 and description




                      9
              Development of a Model to Assess
                the Impact of Changes in IPR
                            Version: 17-11-2006

Content
Justification and objectives of the project.
Introduction
    Literature review
    When to evaluate the impact
    Options to evaluate
    How to evaluate the impact
    Impact variables
Presentation of the model of Impact of Changes in the IPR
    Structure and general characteristics of the model of Impact of Changes in
    the IPR
    Operation of the model
    Translating IPR changes into model parameters
    Definition and calculation of impacts
    Key assumptions of the model


                                                                                 10
              Development of a Model to Assess
                the Impact of Changes in IPR
                             Version: 17-11-2006



Appendix 1: Model Specification

Appendix 2: Data required for the application of the IPR Impact Model to a
            given country

Appendix 3: Suggested Reporting Format for Country Analysis

Appendix 4: Abbreviated User’s manual




                                                                             11
The PAHO IPR Impact Model
   A general model, not a country
    application
   Deterministic (sensitivity analysis)
   Macroeconomic (agreggated)
   Computer assisted simulation model
    (Excel)


                                       12
The model estimates the impact of alternative scenarios
on pharmaceutical expenditure, consumption and market
share of the domestic industry over a defined time
horizon.

The baseline scenario estimates the evolution of the
variables under the existing IPR rules.

The alternative scenarios reflect the evolution of the
variables under other combinations of IPR rules that
might result from TRIPS enforcement, bilateral trade
agreements or autonomous IPR and pharmaceutical
policies, in general. The impact of a given alternative
scenario x is defined as the difference in a given outcome
variable between the baseline and the alternative scenario.
                                                         13
14
           Final impact variables

Impact of scenario x:

IMVx: Increase in expenditure/sales/market value

rCx: Relative reduction in consumption (in units)

RMSDx: Reduction in the sales of the domestic industry




                                                         15
The model first computes the number and proportion of
AI under exclusivity for all years over the time horizon:

The data input required includes:

TAPto: Number of AI (active ingredients) on the market
       at the beginning of the initial year
AIi: Number of AI entering the market each year
AOi: Number of AI exiting the market each year
AIPPi: Number of AI entering the market with patent
protection each year
AIDPi: Number of AI entering the market with test data
protection each year

                                                            16
The duration of the effective exclusivity time derived from
a patent is computed as:

EEP = PD – DT + PDE + TTC + DGE,            where:

PD is the nominal patent duration
DT is the time elapsed between patent filling and
       registration/market authorization
PDE is the extension of patent duration due to
       compensation for delays in patent approval, which
       might affect a certain proportion of AI, pPDE)
TTC is the time elapsed between the patent expiration
       time and generic market entry (associated to Bolar
       provision)
DGE is the delay in generic market entry due to the
       linkage between registration and patent, which
       might affect a certain proportion of AI, pDGE)     17
18
The model then computes the average price differential of
medicines between the baseline and any alternative
scenario by means of a price index that takes the value 1
each year of the baseline scenario:

(Alternative scenarios x are indicated by the superindex (x)

Pi = 1
Pxi = [1+( pexi – pei)*(RPec – 1) + (1- pexi)*(pdi- pdxi)*(RPbd – 1)]

pei: Share of the relevant market under exclusivity in year i
RPec: Relative weighted average price of an AI under exclusivity
         (APe) vs. its price under competition (APc)
pdxi: share of branded products in the non-exclusive segment
RPbd: Relative weighted average price of an branded vs. unbranded
         (INN) AI
                                                                        19
Reduction in consumption (quantities demanded) and
expenditure increase are taken as proxis for reduction in
access caused by price increases. The demand function is
assumed to have a constant price-elasticity, e, and the
following expression:

                          q = k pe
  where
q: units demanded
k: constant
p: price (index)
e: price-elasticity of demand; e = (dq/q)/(dp/p)

The price-elasticity of demand indicates the relative
change in the quantity demanded as a response to a 1%
change in price.
                                                            20
The expenditure/sales/market value in the baseline
scenario is computed as:

MVi = MVi-1*(1+α)

The expenditure/sales/market value in the alternative
scenario x is computed as:

MVix = MVxi = MVi* Pxi e+1




                                                        21
Impact of a change of the price on
  consumption and expenditure




                                     22
23
The reduction in market sales of domestic industry under
scenario x, RMSDxi is
computed as:

RMSDx i = MVDi - MVDxi
= kde* pei* MVi + kdc*(1-pei)* MVi
- (kde*pei* MVxi + kdc*(1-pexi)* MVxi)


where
kde: market share of domestic industry in markets under exclusivity
kdc: market share of domestic industry in markets under competition
MVDi: Market sales of domestic industry in year i


                                                                      24
25
The main assumptions of the model are:

1. Under the alternative scenario x, the units of the
products now under exclusivity, (pexi – pei), will attain a
higher relative price than under competition, Rpec.

 2. The market share (in monetary terms) of each AI is the
same for all AI throughout their market life

3. Competition in an AI market begins immediately or
some years after patent protection and test data
exclusivity end.

4. The average price of an AI instantaneously drops by a
given fixed proportion when competition starts.
                                                              26
5. The model assumes that the domestic industry will
maintain all the time and under any scenario the initial
market share in the markets under exclusivity and under
competition.

As it is likely to have a higher share in the competitive
market, as long as the competitive market decreases in
relative terms, the share of the domestic industry in the
total market will come down. The absolute value of this
market share cannot be unambiguously predicted as it
depends, as well, on the growth of the market.


                                                            27
    Preliminary results for Colombia
   The time horizon for the simulation is 2005-2050.
   In the baseline scenario the share of the market under
    exclusivity rises until 2019 and remains stable thereafter at
    43%
   If patent duration is extended to 21 years, the market share
    under exclusivity levels off a year later, in 2020, at a 47%,
    and pharmaceutical expenditure is 5.7% higher than in the
    baseline scenario.
   Increasing by one year the duration of the exclusivity for
    test data protection would imply a stabilization of the
    market share under exclusivity in 2019 at 44% and a 1.5%
    increase in expenditure over the baseline scenario.
   If Colombia had not enforced product patent protection in
    2000 and test data protection in 2002, it might have saved
    an estimated 69% of the pharmaceutical expenditure over
    the simulated period.
                                                                28
              IPR Impact Model
       Preliminary Results in Malaysia

   Final purpose of analysis was to
    estimate the likely impact a stronger
    IPR protection on medicine prices in
    Malaysia if Malaysia signs the US-
    Malaysia FTA bilateral agreement



                                            29
    Preliminary results based on
      currently available data
   The time horizon for the simulation is 2007-2047
   If all standard USFTA provisions are accepted,
    the worst case scenario simulated would result
    in increase in pharmaceutical expenditure of 46%
    or a reduction in consumption of 56%
   If data exclusivity alone is introduced, the worst
    case scenario simulated would result in a
    reduction of consumption by 50% or an increase
    in expenditure of 38%
   If the proportion of medicines that are patented
    increases, the worst case scenario simulated is a
    reduction in consumption of 36% or an increase
    in expenditure of 28%
                                                     30
                   Discussion
   The model has proved easy to understand and
    use by decision-makers with no previous
    experience in simulation models
   Most of the information required for running the
    model was available and relatively easy to collect
    in the pilot test countries
   The model results are very sensitive to the data
    and assumptions on the initial number of AI, and
    of those entering and exiting the market. The
    number of existing AI should be adjusted in order
    to ensure that it reflects the number of AI in the
    market that have a market share similar to the
    future new entrants.
                                                     31
                        Discussion
   Additional analyses are also required on the price differential
    of AI in competitive markets and in markets under exclusivity
    conditions
   Although the results look plausible, it is necessary to
    improve the evidence base by undertaking systematic
    reviews and, when required, new analyses of the impacts of
    IPR changes.
   The values of some of the parameters that define the
    scenarios in the model directly reflect the options of the
    decision maker, e.g. duration of the patent or year of
    enforcement of pharmaceutical patents.
   For other parameters the values are less straightforward,
    and will require specific studies and subjective technical
    judgments. E.g. how will an hypothetical broader scope of
    patentability affect the proportion of AI that will enter the
    market with patent protection?
                                                                 32
33
        Generic Penetration of Brand Market:
           Units Sales and Price per Unit
    6 Months
   Exclusivity               Generic Price Competition                       Commodity Equilibrium Price Reached
    (Generic)               (More Firms = Lower Prices)                        (Modest Price Inflation Expected)
100%
                          Generic Units as
90%
                          % of Total Unit Sold
80%
70%
60%
50%
40%
30%
                             Generic Price as
20%
                             % of Brand Price
10%
 0%
        0     3     6     9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60

                                    Months after First Generic Entry into Market
                                                                                                               34
       SOURCE: Compiled by the PRIME Institute, University of Minnesota from data found in Kidder, Peabody
    Estimating the price differential
        exclusivity-competition

   The price of original drug under exclusivity is 100
   The average price of the generics after three
    years of patent expiration is 25
   Market share of generics after three years is 85%
    and that of the original product, 15%
   The final average price of the AI is:
   100 x 0,15 + 25 x 0,85 = 38,75
   The price of the AI under exclusivity is 2,5 times
    that of the price under competition

                                                      35
Source: Danzon and Furukawa, Health Affairs, 2003
                                                    36
             Estimation of relative
            average prices of drugs
       Sales of unbranded generics (UBG) / Total sales
       --------------------------------------------------------------------- =
       Units of unbranded generics (UBG) / Total units


   Units of UBG x average UBG price / Total units x average price
= -------------------------------------------------------------------------------------------- =
           Units of unbranded generics (UBG) / Total units

      average UBG price
    = --------------------------- = RELATIVE PRICE OF UBG
          average price
                                                                                           37
    Estimation of potential
  savings from an INN policy
POTENTIAL SAVINGS (in % of total sales) =

    SHARE OF BRANDED GENERICS SALES
    x ( 1 - RELATIVE PRICE OF UBG / RELATIVE PRICE OF BG )
    x 100

Assumptions:
    In the absence of brand names, competition would reduce
    the present prices of BG to the level of UBG.


                                                          38
Diferenciales de precios de los medicamentos con patente y con marca de fantasia

                                      Canada Chile Francia Alemania Italia Japón México R.U. U.S.

Precio relativo marca                    0,43    1,62   0,52    0,58    0,63   0,50    0,80    0,92   0,57
Precio relativo DCI                      0,45    0,35   0,43    0,50    0,50   0,25    0,33    0,32   0,23
Diferencial de precio marca/DCI          0,97    4,60   1,22    1,16    1,25   2,00    2,40    2,83   2,51
Reducción potencial del precio          -0,03    0,78   0,18    0,14    0,20   0,50    0,58    0,65   0,60
Ahorro potencial en % de las ventas     -0,45   32,88   2,00    3,50    4,00   8,00   14,00    7,11   4,82

Precio relativo proveedor único           2,84 3,25 1,86        2,67    1,52 1,97      1,39    3,38 2,50
Precio relativo competencia               0,95 1,92 0,56        1,08    0,88 0,81      1,09    0,69 0,93
                                          2,98 1,69 3,35
Diferencial de precio proveedor único/competencia               2,46    1,72 2,44      1,28    4,92 2,69
Reducción potencial del precio            0,66 0,41 0,70        0,59    0,42 0,59      0,22    0,80 0,63
Ahorro potencial en % de las ventas      39,64 33,17 26,11     41,17   18,45 28,98    14,70   64,54 20,43

                                                                                                 39
Impact of generic competition on
   pharmaceutical prices (1)
   (A substantial share of) the reduction of
    ARV annual treatment costs between 2000
    and 2003 from US$ 10.000 to 300 should
    (probably) be accounted to generic
    competition.
   A recent WHO-HAI study, The price of
    medicines, shows ratios between generic
    and branded originals in the range of 1:2
    (Armenia), 1:3 (Sri Lanka), and from 1:2
    up to 1:7 in Kazakhstan
                                           40
    Impact of generic competition on
       pharmaceutical prices (2)
   A recent study applied WHO-HAI
    methodology in Malaysia
   Survey was conducted from October-2004
    to January 2005.
   48 drugs were surveyed by using
    systematic sampling technique in four
    geographical regions of Malaysia

   Babar et al, A survey of medicine prices in
    Malaysia by using WHO/HAI methodology.
    UCSI-USM, October 2005.
                                              41
   Median MPRs of IB, MSG and LPG in Public for
Procurement Sector, Private Sector Retail Pharmacies
          and Dispensing Doctors Sector


  Drugs        Public        PSRP           DDS
               Sector
Innovator       2.41         16.35         15.40
Brands
Most Sold       1.56          6.89          7.76
Generic
Lowest          1.09          6.57          7.76
Price
Generic                                         42
Private Retail Pharmacies




                            43
44
   For additional information, please
    contact Joan Rovira
            joanrovira@ub.edu




    Thanks for your attention


                                         45
                  Fixed parameters
   YI: Initial year of simulation period
   YL: Last year of simulation period
   TAPtn: Number of existing active ingredient (AI) in the market in year
    tn; tn <YI
   AIi: Number of AI entering the market in year i; i > tn
   AOi: Number of AI exiting the market in year i; i > tn
   DT: Time from patent filling (or approval) of an AI to market
    registration (approval) of the original product
   MVto: Total sales/expenditure of the relevant market in year to
   α: annual rate of growth of MV
   RPec: Relative weighted average price of an AI under exclusivity (APe)
    vs. its price under competition (APc)
   d: discount rate
   kde: market share of domestic industry in markets under exclusivity
   kdc: market share of domestic industry in markets under competition
                                                                        46
   Scenario-dependent parameters

YP: initial year of product patent enforcement
pp: Percentage of patented (product patent) AI entering the
   market in year i
PD: Patent duration in years
YDP: initial year of data protection enforcement
AIDPi: Number of AI entering the market in year i with test
   data protection
DE: Duration of exclusivity due to test data protection
TTC: Time from patent expiration to generic competition
e: price-elasticity of demand
                                                              47
             Impact variables

Impact of scenario x:

IMVxi: Increase in total sales/expenditure of the
  relevant market in year i.

RICi: Reduction in consumption (units) in year i

RMSDxi: Reduction in market sales of domestic
 industry in year i

                                                    48
49
ASEF ASIA-EUROPE FOUNDATION
CULTURES &CIVILISATIONS DIALOGUE
“8th Talks on the Hill”
Re-righting Intellectual Property: Economic and
  Social policy challenges in Asia and Europe

Singapore, 7th-9th of May 2006

SELECTED ASEF ROUND TABLE
 RECOMMENDATIONS:

                                            50
        Allowing for greater
    flexibilities in using TRIPS
   Many of the Europeans felt that their
    governments should be more
    forthcoming about telling the
    developing countries that it is
    acceptable for them to use the
    flexibilities that TRIPS provides. In
    addition to governments, companies
    should also start to recognise the
    flexibilities that are built in TRIPS –
    for example parallel imports.           51
     Releasing the Pressure

   The group also called upon
    governments and patent companies
    to refrain from using pressure tactics
    that result in developing countries
    adopting higher standards of
    intellectual property protection and
    enforcement than they need to or are
    able to.
                                         52
Understanding the depth of
   Intellectual Property
   Many of the participants from
    developing countries recognised the
    need to gain more concrete advice
    before signing on the treaties such
    as the Patent Cooperation Treaty
    (PCT) and indicated that their
    governments need to realise that
    intellectual property is far more
    important and pervasive than
    previously thought.                 53
     Distinguishing between
    obligations and pressures
   Linked to this point was the need for
    developing countries to focus on
    dissecting much of the information that
    they are receiving from the various
    international organisations as well as
    other governments into obligations and
    pressures. In doing so, the countries
    would be better able to more positively lay
    out their policy in alignment with their
    priorities and national interest.
                                              54
    Diversifying the decision-
        making process
   National governments should diversify the
    decision-making process on treaties and
    other agreements linked to intellectual
    property. This comes with a growing
    recognition that this issue can no longer
    be limited to a few specialists. For
    example, professionals and decision-
    makers from the health sector should be
    involved in the discussion and negotiation
    of both FTA and internal policies when
    they are likely to have an impact on the
    price and access to medicines and health 55
    services.
      Value in involving civil
      society at multilateral
              forums
   Members of the group recognised
    that independent civil society has a
    useful role to play at the multilateral
    level and their involvement and
    views should be better taken into
    consideration in the decision-making
    processes within the WTO and WIPO.
                                          56
   For additional information, please
    contact Joan Rovira
            joanrovira@ub.edu




    Thanks for your attention


                                         57