Priority Medicines for Europe and the World: an Approach to the Evaluation of Future Medicines

8.2 Approach to the Valuation and Pricing of Future Medicines

Priority Medicines for Europe and the World "A Public Health Approach to Innovation"

Background Paper

Approach to the Valuation and Pricing of Future Medicines

David Henry Danielle Lang Suzanne Hill

Discipline of Clinical Pharmacology WHO Collaborating Centre for Training in Pharmacology and Rational Drug Use Faculty of Health The University of Newcastle, AUSTRALIA

7 October 2004

8.2-1 8.2 Approach to the Valuation and Pricing of Future Medicines

Table of Contents

Introduction...... 3 The International Market for Pharmaceutical Products...... 3 Problems in Middle Income Countries...... 4 Differential Pricing...... 4 Spreading the Burden of Drug Development Costs...... 5 Valuing New Medicines...... 5 A Published Example – Angiotensin Enzyme Inhibitors...... 6 Valuing Future Medicines...... 7 Indicative Prices for a Theoretical New Drug for HIV/AIDS...... 8 Indicative Prices for a Theoretical New Drug for Depression...... 10 Discussion...... 10 References...... 19

Annexes

Appendices

Introduction This section of the report is concerned with the valuation of future medicines; specifically, we show how governments in countries of variable wealth, through their health insurance agencies, can encourage innovation through the appropriate pricing of new medicines. We think reimbursement authorities should become proactive – committing to rewarding genuine medical advances, using cost containment measures such as reference pricing and therapeutic group tendering for non-innovative products. This means rewarding improved clinical performance over other aspects of drug design, such as sophistication in the mode of action or the costs of development. At present, reimbursed prices are determined by each country, often in a black box fashion where country reimbursement authorities set prices to ensure access and control costs.1 This results in an unpredictable lottery for companies who have brought a product to market through a series of regulatory hurdles and still do not know what the final reimbursed price will be. We believe that reimbursement agencies and manufacturers should introduce greater certainty in this process by agreeing on the principles of valuation of future medicines. By rewarding clinical performance and linking prices to national income levels governments and insurers should encourage manufacturers to invest in the discovery of innovative medicines that address priority health care needs. To achieve the full benefits of such an approach the EU will have to review its present policies on parallel trade in medicinal drugs. (See appendices 8.2.8 and 8.2.9)

The International Market for Pharmaceutical Products The international market in which new medicines are developed is characterised by rigorous intellectual property protection and a high degree of regulation of product quality safety and efficacy. Intellectual property protection is mandated by law in developed countries, and is protected by multilateral and a growing number of bilateral trade agreements. There is a high degree of harmonisation of drug regulation2 but not of subsidisation policies, which are more likely to be based on local socio-economic factors and an over-riding desire to contain costs.1

Extensive rationalisation of the industry has been underway for some years, with many mergers.3 (See Appendix 8.2.3) The perceived high prices of drugs have encouraged the growth of the generics industry. There is a trend for successful generic companies to work with research-based companies or to develop ‘branded’ products, because of their higher profit margins. (See Appendix 8.2.2)

The initial discovery process for new drugs is demanding and attended by a high failure rate. (See Appendix 8.2.6) It is not necessarily best done by large multinational companies; increasingly, early development is performed by small start-up companies working with contract research organisations.4 These organisations may choose to sell or share the intellectual property on candidate compounds, which are then developed and marketed by the larger international pharmaceutical companies. 8.2-3 8.2 Approach to the Valuation and Pricing of Future Medicines

There is an expectation of high returns in the research-based pharmaceutical industry, conditioned by shareholders’ experience of profits.3 Historically these have been high. There is a tension between the companies’ expectations of profits (through high prices) and the increasing budget constraints felt by public and private sector organisations that are responsible for funding health care. There is a trend to levy very high prices for new drugs (particularly new biological products and anti-cancer drugs).5 (See Appendix 8.2.1)Reimbursement authorities have responded to these with attempts to ‘channel’ treatment through to those most likely to respond by measuring biomarkers, or by ‘stopping rules’ that determine a threshold response that has to be achieved in order that subsidisation of a medication will continue.5 Although these approaches have a number of positive features they are aimed primarily at limiting budgetary impact rather than rewarding clinical performance or encouraging future development of innovative products.

Problems in Middle Income Countries The trends to high prices and more selective use are a particular disadvantage for low and middle income countries trying to fund the purchase of new products. The fate of middle income countries in particular will be of concern in the expanded European Community. While there is acceptance of the need to improve access to essential medicines in low income countries, the same urgency is not apparent for middle income countries, which may pay the same (or higher) prices as the richest and most developed nations.6,7 Effectively, they are being asked to shoulder a high proportion of drug development costs, in relation to their ability to pay. Under the present system they can only do this by limiting access as there has been little prospect of differential pricing for middle income countries.

Differential Pricing To a degree, differential pricing (sometimes known as tiered pricing) has been introduced internationally, and is supported by both the World Trade Organization and World Health Organization in the case of essential medicines.8 Differential pricing is possible with pharmaceutical products because the marginal cost of manufacture is often much less than the average selling price. A number of pharmaceutical companies have made effective use of differential pricing for products such as vaccines, oral contraceptives anti-malarial drugs and insulin.9 In low income countries these products sell for a fraction of the price of developed countries.

Differential pricing should not be seen only as a mechanism to be used for essential medicines in the lowest income countries. Differential pricing has a wider application across low and middle and perhaps even high income countries, which vary substantially in their national measures of wealth. For instance, the World Bank reports that the Gross National Income (previously known as gross domestic product, GDP) per capita in 2003 was $37,610 in the USA, compared with $15,870 in New Zealand. Differential pricing should not be viewed primarily as a cost cutting measure. Applied properly it should ensure that the 8.2-4 8.2 Approach to the Valuation and Pricing of Future Medicines

opportunity cost of purchasing medicines and investing in pharmaceutical R&D (through drug purchasing and subsidisation) is roughly equivalent across countries of variable wealth.10 (See Appendix 8.2.4)While improving the affordability of medicines in different countries, it is also a mechanism for maximising the profit of manufacturers, who may otherwise only sell to the rich elite in low and middle income countries. Economics theory indicates that where the true marginal costs of a product are low (as with most medicines, or the few remaining empty seats in a commercial flight), price discrimination will increase the total revenue of a company, so long as parallel trade (arbitrage) can be minimised.11 A number of technical solutions have been proposed to limit parallel trade, such as unique presentation and country-specific labelling and packaging measures.12 These are made possible by the regulatory requirements imposed on pharmaceutical manufacturers.(See Appendix 8.2.9)

Spreading the Burden of Drug Development Costs Drug development costs are high (just how high is disputed3) and companies have come to expect a relatively high rate of return to compensate for the research and development costs that are incurred early in the development cycle. It is unfair to expect these costs to be spread equally across countries of variable wealth. It is inevitable that high income countries will bear the majority of drug development costs in an absolute sense. However, the fraction of GNI committed to research and development varies surprisingly little between countries of different wealth levels.13 National investment in drug research comes in two forms: the work of national research councils and (more important in an absolute sense) the money countries pay for the drugs that they need, particularly those that are patent-protected. However, departments and agencies with responsibility for purchasing and subsidisation of medicines probably view their activities as budget control rather than encouraging research into new medicines. As a consequence, they have developed a range of tools that are designed to limit their costs but not to encourage innovation.

Budget control initiatives that have become popular include limited lists of subsidised drugs, generic substitution (after patent expiry), reference pricing (a form of cost-minimisation analysis), and the use of cost-effectiveness and cost utility analysis to determine the cost- effectiveness of drugs in the local setting. 1 Selective tendering for particular therapeutic classes of drugs does not appear to be widely practised in high income countries (an exception being New Zealand14). To a degree, middle income countries in Europe have introduced a number of these strategies (eg. Hungary and the Baltic states).15 However, it is a bigger challenge in these countries as the funding base is small and pharmaceutical companies appear reluctant to negotiate differential prices, even though the national income levels of these countries is closer to low income countries than the highly developed industrialised nations.

Valuing New Medicines Even if the principle of differential pricing is agreed to, a question remains as to the actual price that should be applied to new medicinal drugs. In this report we argue that pharmaco- economics can act as a guide to pharmaceutical manufacturers by indicating what price they can expect to sell future products at and what insurers should be prepared. The guiding principles are to provide encouragement for genuine innovation, at the same time ensuring that new medicines remain affordable in countries of variable wealth. ‘Innovation’ must be determined by measurable health gains, not just the sophistication of a drug’s mode of action or production technique. Here we use illustrative examples to show that it is possible to combine the principles of pharmacoeconomic analysis and differential pricing to value future medicines. This approach indicates the extent to which low and middle income countries should be expected to contribute to R&D through the prices they pay.

In this paper we outline an extension of a method we have previously published in which we combine cost-effectiveness analysis with a measure of national wealth to generate indicative prices at which an established class of drugs might be considered to be cost-effective.10 We show how this methodology could be used to generate indicative prices for new drugs.

A Published Example – Angiotensin Enzyme Inhibitors We have published details of this approach to valuing medicines, using the example of ACE inhibitors.10 The principles embodied in this work were: 1. that the price of ACE inhibitors should be linked to formal measures of the performance of the product. 2. that the clinical outcomes should be expressed in acceptable natural units – eg life years or quality adjusted life years gained 3. that these natural units should be valued in a manner that reflects the opportunity cost of committing resources in countries of variable wealth. In this exercise we valued each unit of benefit (life year gained) as a multiple of a country’s GNI per capita. 4. that by setting these values as thresholds in cost-effectiveness analysis it is possible to generate a series of indicative prices at which the drugs represented ‘value for money’ in cost/performance terms, and generate opportunity costs that were roughly equal across different countries.

Although we published the ACE inhibitor example as an illustrative exercise it should be noted that a version of this approach was used as the basis of pricing of ACE inhibitors for the Australian Pharmaceutical Benefits Scheme. That exercise was carried out with considerable skill by members of the Australian Department of Health and Ageing and staff from pharmaceutical companies. It remains the basis on which these drugs are priced in Australia.

At a practical level the ACE inhibitor pricing exercise involved a number of steps. The first was to identify and retrieve systematic reviews of the trials of ACE inhibitors in the treatment of hypertension, congestive heart failure and after myocardial infarction.10 These provided estimates of the reduction in mortality that could be expected in these patient groups. These were translated into survival gains using conservative assumptions. A cost- effectiveness model was developed that included equations for each of the three main clinical indications for the drug class. Using threshold analyses that employed GNI per capita values for different countries indicative prices were derived for the different clinical indications. These were relatively low in the case of hypertension (cheap effective products from other drug classes available) and considerably higher in the case of heart failure and myocardial infarction (where they prolonged life compared to existing treatments). Based on epidemiological estimates of the relative use of ACE inhibitors in these different clinical indications we calculated a weighted price that reflected ‘value for money’ for this mix of conditions.

Valuing Future Medicines In the exercises described here we address clinical problems that have been identified as priority areas: new drugs for HIV/AIDS and new drugs for depression. Both are major public health problems and, untreated, contribute greatly to lost life years and lost DALYs. 16 They affect individuals living in low, middle and high income countries and both require long- term treatment, meaning they will be a major financial burden to insurance programs.

By adapting the methodology used in the ACE inhibitor project we have tried to provide an indication of what return on investment a company could expect if the prices they negotiated were based on both the clinical performance of the product and the capacity of countries to afford the medication (as reflected in their per capita gross national income).

Methods This approach to valuing future medicines employs the established tools of evidence-based medicine and clinical economics, and incorporates a measure of national wealth (in the form of GNI per capita). In conventional cost-effectiveness analysis the acquisition cost of a drug is determined by the manufacturer, and is used as an input during the calculation of the incremental cost-effectiveness ratio (ICER).17 Here, we set a threshold ICER (in cost/life year gained) for each of a series of representative countries as a multiple of the per capita GNI and use threshold analysis to determine an indicative ‘cost-effective’ price as an output of the analysis. The World Bank has suggested that health care interventions may be considered 'cost-effective' if they buy a year of healthy life for less than the national average per capita GDP.18 The Macroeconomics Commision on Health has discussed the implications of using a range of threshold values for DALYs.19 In the examples given here we have set the threshold at 1 x GNI per capita, but this can be varied. For instance, a higher multiple could be used to encourage development of drugs for a neglected disorder and lower multiples could be used in the case of drugs for disorders for where a number of effective alternatives exist.

The approach described here differs from the example of ACE inhibitors; although it starts by generating indicative prices for existing treatments it goes on to estimate the benefit and monetary value of a new hypothetical drug class. The hypothetical drug and existing treatments are valued by comparison with a ‘counterfactual’ – a (hypothetical) situation in which no effective treatment is available to treat the condition. If new (or hypothetical) treatments are valued only at the margin generated by existing treatments it is possible to over or under-value the new product. This is because the economic performance of the comparator has not been established (and it may be inefficient). The WHO has recommended the use of this ‘counterfactual’ when making economic analyses of health care programs as it enables a full analysis of the impact of a wide range of interventions.20

In these analyses we are trying to illustrate what rate of return (through differential pricing) might be anticipated by manufacturers of new drugs that represent advances in the treatment of the two conditions of interest: depression and HIV/AIDS. In the illustrative examples here we have stopped at the point where indicative prices are estimated. To calculate the total return would require more complex calculations of the numbers of eligible recipients (based on disease and indication prevalence estimates) in different countries. This would be an extremely useful but complex exercise. In order to estimate the likely clinical impact of future therapies we have used as our starting point the estimated benefits of existing treatments and have postulated realistic improvements from theoretical new drugs.

Indicative Prices for a Theoretical New Drug for HIV/AIDS Anti-retroviral drugs, more than any other class of compound, highlight the problems of achieving equitable access in countries of varying wealth and with huge variations in burden of disease. The delay in access to effective multi-drug therapy was in part due to the high prices of drugs when they were available only from the international research-based manufacturers. 21 The decline in price of generic combination products towards the true marginal costs of production, and the availability of quality assurance data from WHO and FDA, has encouraged a rapid scaling up of the distribution of these drugs.21 The development of effective treatments has been incremental, with zidovudine monotherapy being followed by dual nucleoside reverse transcriptase inhibitors (NRTIs), and then triple therapy from around 1996. The latter usually consists of 2 NRTIs combined with a protease inhibitor or non-nucleoside reverse transcriptase inhibitor (NNRTI). The greater efficacy of triple antiretroviral (ARV) therapy over mono or dual therapy has been demonstrated in multiple trials, in meta-analyses and in large cohort studies, which have demonstrated major improvements in survival.22, 23,24 Despite this, there are apparently few new anti-retroviral drugs in the pipeline and the most recent arrival on world markets (enfuvirtide) is extremely expensive.

We adapted the model for ACE inhibitors described earlier to determine the indicative price for existing combination ARV treatments in different countries. An image from the

spreadsheet model is represented below, using Mali (GNIPC $290US in 2003) as the country example.

We first estimated the survival gain from existing highly active anti-retroviral therapy (HAART) compared with no treatment (the only choice for many HIV-infected patients in low income countries). In making these calculations we assumed an equal survival gain in countries of varying national wealth. This may be inaccurate but differentiation discriminates against countries with poor existing health infrastructure, by assigning a smaller survival gain and thus making treatment appear less cost-effective.

We have presented the analyses with and without estimates of productivity gains. These economic gains are likely to be realised in sub Saharan Africa where HIV/AIDs has decimated workforces, but will be less important in middle and high income countries where pools of unemployed but healthy workers can substitute for infected individuals. The data sources and assumptions are given in the spreadsheet. We used survival gains from large studies of the survival of cohorts of HIV-infected individuals before and after the introduction of effective anti-retroviral treatments. The productivity losses due to illness that might be averted by effective treatment were estimated from data published by the Cote D’Ivoire Electricity Company.25 The data on GNI per capita are those published by the World Bank for 2003. 26 The effectiveness of HAART was assumed to be the difference in survival between untreated and treated cohorts. The benefit of a hypothetical new antiretroviral drug was assumed to be an additional survival gain of 1.8 years (compared with HAART). This is equivalent to an additional 1.57 QALYs (these data are theoretical).

Quality of life data were obtained from published data and the assumptions are provided in the spreadsheet.27 As with the ACE example mentioned above we set the threshold value for one quality adjusted life year at 1 x GNI PC for each country and calculated an ‘indicative price’ that represented ‘value for money’ on this scale. These values are presented for existing HAART and for the theoretical new drug with the additional survival benefit. The exclusion of the economic productivity gains lowers the value of treatment substantially.

It is important to understand that the results given here illustrate what can be achieved by this approach to the valuation of new medicines. It should not be assumed that the ‘indicative’ prices given here are accurate; a full pricing exercise would require access to local data on benefits and costs for each country included in the model. Because this exercise is illustrative and is not designed to inform decision-making we have not performed sensitivity analyses.

As can be seen from the spreadsheet, the indicative ‘value for money’ price for HAART in Mali is $267 US annually with productivity gains included and $157 without productivity gains. By contrast in Australia (GNIPC 2003 $21650 US) the indicative price is $11699 annually, assuming no productivity gains. The value of a hypothetical drug capable of a further modest prolongation in life expectancy is greater than that of HAART, although the 8.2-9 8.2 Approach to the Valuation and Pricing of Future Medicines

overall differences are modest. In this example we have made no assumptions about whether the hypothetical treatment represents a regimen containing existing drugs or (less likely) is a new monotherapy. Illustrative data for other countries are displayed in Table 8.2.1 and Figure 8.2.1. The apparent non-linearity of the curves in Figure 8.2.1 is because of the scaling of the horizontal axis to ensure that it fitted the page.

These examples are illustrative only, and are based on simple calculations using readily available data. However, they reveal the wide variations in prices of effective drugs that are justified by measures of performance and international variations in income. The overall advantages and disadvantages of this approach are discussed after the section on depression.

Indicative Prices for a Theoretical New Drug for Depression Depression is one of the leading causes of non-fatal burden of disease in the world. 28 In some respects it is more difficult than HIV/AIDS to characterise in a model. This is because there is no easily quantified increase in survival with treatment for most patients (except for a proportion who commit suicide – and the effects of treatment on this are uncertain). Instead, we have assigned a modest improvement in efficacy with a hypothetical new drug, which translates into days free of depression and thus an increased quality of life. The model is simple and translates a proportional measure of efficacy (maintenance of remission of depression)29 into a number of days free of depression and thus a gain in the number of quality-adjusted days achieved with treatment. Although the improvements in efficacy may seem modest, the model translates them into a 0.1 quality adjusted life year (QALY) gain during each 6 months of treatment (or 0.2 QALY gain for each year of treatment). This gain reflects the profound impact of depression on quality of life. It has been shown that even in resource poor settings 1 DALY can be averted by efficient depression treatments that cost less than 1 year of average per capita income.30 In the hypothetical example given here we have omitted the costs of consultations and other forms of treatment, but these can impact on the final measure of cost-effectiveness. In addition, we include no productivity gain because in a general sense mental depression does not have the major economic impact of HIV/AIDS on low income countries. However, at an individual level we do not doubt that return to work will be facilitated by effective treatment. As with the HIV/AIDS example the indicative price of anti-depressant treatment varies with GNI PC. However as the figure shows the total difference between the indicative prices for the hypothetical anti-depressant agent in the highest and lowest income countries is less than was estimated for a new antiretroviral treatment.

The indicative prices generated by the model may seem high. It must be remembered that these estimates are illustrative only and are based on an assumption that patients are suffering from fairly severe depression. However, the data indicate that, used properly and channelled to patients with more severe disease, effective antidepressant therapy is valuable and certainly worth the investment of research dollars. Note that these calculations do not take account of the controversy currently surrounding the putative effects of selective

serotonin re-uptake inhibitors, particularly the claim that these drugs may increase suicidal ideation early in the course of therapy, particularly in adolescent patients. For the purpose of this exercise we have not distinguished between pharmacological classes and have concentrated on the impact of successful treatment on quality of life.

Discussion These exercises show that from a computational point of view it is relatively straightforward to incorporate measures of performance and national wealth in determining indicative prices for pharmaceuticals that have a range of beneficial effects on human disease. Of course this does not mean that the indicative price is the ‘right’ price, the lowest possible price or an affordable price. Furthermore, there is no guarantee that manufacturers will be interested in manufacturing products on this basis. However, performed in a more comprehensive manner, with appropriate data-sets, and with inclusion of local data, this type of exercise can provide a manufacturer with estimates of a fair rate of return and a ‘value for money’ price for products that are being considered for development. The use of this approach would provide some assurance that drugs capable of providing benefits for unresponsive diseases will be reimbursed appropriately by insurance programs. This is essential for companies to invest in the development of drugs for diseases that respond sub-optimally to current therapies. It is important that insurance agencies recognise the importance of rewarding truly innovative products. In order to facilitate the development of drugs for neglected disorders the multiple of the GNI PC that is used in the threshold analyses can be increased as a form of risk sharing between the government and the manufacturers. This would be a matter of policy based on an assessment of national health priorities and it is probably unrealistic to expect private insurance companies to enter such arrangements.

The realisation of a more predictable system that encourages drug development and achieves affordability of access in countries of variable wealth requires reconsideration of current policies towards parallel trade. Parallel imports tend to favour high income countries, which can benefit from the prices paid in lower income countries. Achievement of differential pricing, as described here, requires a reduction in parallel trade. Perhaps high income countries may be prepared to forgo the short-term financial gains if they realise that this will improve affordability in lower income countries, and that the higher prices they are being asked to pay are justified by a rational assessment of the value for money offered by the drugs and their national income levels.

There are a number of technical criticisms that can be made of this work. The perspective should be societal but that is difficult without a range of cost data that are not readily available. We are reliant on data on efficacy that may not apply to all of the countries being studied. We are constrained by the short-term nature of many of the data relating to efficacy. We have used a single estimate of national wealth that takes no account of the variations in wealth within countries. We accept these criticisms but feel that they are largely concerned with the technical aspects of the exercise. All we propose here is that manufacturers and

insurers of pharmaceutical products should consider the value of future medicines in both clinical and economic terms and agree on an equitable system for rewarding true innovation while ensuring access by those who need them.

See Appendix 8.2.5 See Appendix 8.2.10

Table 8.2.1: GNI PC values (World Bank 2003) and indicative prices for HAART and a hypothetical treatment for HIV AIDS (12 months) Prices are given with and without assumed productivity gains

Antiretroviral Annual price Antiretroviral Indicative price HAART Indicative price per annum exc productivity per annum Per HAART HAART New Drug Capita excl productivity GNI Mali 290 267 157 285 Nigeria 320 294 173 314 Zimbabwe 480 441 259 471 India 530 487 286 521 Cote D'Ivoire 660 607 357 648 Georgia 830 763 448 815 Sri Lanka 930 855 503 913 Philippines 1080 993 584 1061 Morocco 1320 1214 713 1297 Kazakhstan 1780 1637 962 1748 Bulgaria 2130 1959 1151 2092 Romania 2310 2125 1248 2269 Russia 2610 2401 1410 2564 South Africa 2780 2557 1502 2731 Turkey 2790 2566 1508 2740 Malaysia 3780 3477 2043 3713 Latvia 4070 3744 2199 3998 Croatia 5350 4921 2891 5255 Czech 6740 6199 3642 6620 Republic Slovenia 11830 10881 6392 11620 Greece 13720 12620 7414 13476 Spain 16990 15627 9181 16688 Italy 21560 19831 11650 21177 France 24770 22783 13385 24330 Germany 25250 23225 13644 24802 UK 28350 26076 15319 27847

Table 8.2.2: GNI PC values (World Bank 2003) and indicative prices ($US/annum) for a hypothetical treatment for depression

Indicative price Indicative Existing price Per Capita GNI treatment New Drug Mali 290 46 57 Nigeria 320 50 63 Zimbabwe 480 76 94 India 530 83 104 Cote D'Ivoire 660 104 130 Georgia 830 131 163 Sri Lanka 930 146 183 Philippines 1080 170 213 Morocco 1320 208 260 Kazakhstan 1780 280 350 Bulgaria 2130 335 419 Romania 2310 364 455 Russia 2610 411 514 South Africa 2780 438 547 Turkey 2790 439 549 Malaysia 3780 595 744 Latvia 4070 641 801 Croatia 5350 842 1053 Czech Republic 6740 1061 1325 Slovenia 11830 1862 2328 Greece 13720 2160 2700 Spain 16990 2674 3343 Italy 21560 3392 4240 France 24770 3899 4874 Germany 25250 3975 4968 UK 28350 4491 5614

Spread sheet showing the calculation of an indicative ‘value for money’ prices for existing highly active anti-retroviral treatment and a hypothetical new drugs. The calculations are given for Mali (GNI PC $290) with and without assumed productivity gains resulting from effective treatment Antiretroviral efficacy Estimate Average Assumptions: survival Survival with no treatment 6.6 - 7.7 years 7.20 The survival without ARV treatment (natural history) has been estimated from published Survival with existing HAART 13.9-14.5 years 14.20 sources and does NOT assume a lower survival (off or on treatment) in low income Survival with hypothetical new drug 16 years 16.00 countries. For reasons of equity we assume that the therapeutic benefit does not vary with wealth Assumptions - utility Average Utility QoL HIV infection 0.75; AIDS 0.25; Untreated With no treatment 0.66 HIV infection on treatment with toxicity or disease progression 0.5 With existing HAART 0.88 HIV infection without symptoms or toxicity 1.0 With a hypothetical new drug 0.88 For references for survival and utility estimates see foot of document In calculating the average utility in the untreated state we assumed that an individual spent 1/3 of their time in each of three health states with utility values of 1.0, 0.75 and 0.5 respectively QALYs In calculating the average utility with HAART we assumed that an individual spent 75% of their time With no treatment 4.752 with a utility of 1.0 and 25% with a utility of 0.75, We made the same assumptions for a new With existing HAART 12.43 theoretical drug; ie it only varied from HAART in respect of survival With a hypothetical new drug 14

QALYs Gained Increment Estimation of Quality adjusted life years With no treatment 0.00 These were calculated from the product of the average survival and the average utility With existing HAART compared with no treatment 7.67 With hypothetical new drug compared with no treatment 9.25 With a hypothetical new drug compared with HAART 1.58 Life Years Gained With no treatment 0.00 With existing HAART compared with no treatment 7.00 With hypothetical new drug compared with no treatment 8.80 With a hypothetical new drug compared with HAART 1.80

Productivity Gains months Months This assumes that 60% of the treated individuals are capable of being gainfully employed if their With no treatment 0.00 health allows and this estimate applies to the extra survival experienced by treated individuals. With existing HAART (lifetime) 64.66 The actual figures for AIDS related absenteeism were the estimates provided in a study of the With a hypothetical new drug (lifetime) 77.62 Electricity Company of Cote D'Ivoire

Productivity Gains $ $ With no treatment 0.00 The productivity gains from HAART and a theoretical new drug were derived from the absenteeism

With existing HAART compared with no treatment 1562.52 data referred to above; annual wages were assumed to be same as the GNI per capita for the country With a hypothetical new drug compared with nothing 1875.72 With a hypothetical new drug compared with HAART 313.20 0 GNI Per capita $ 290

Indicative price ($US) Lifetime Annual Annual Cost Cost cost exc productivity HAART 3788 267 157 New Drug (compared with no treatment) 4558 285 168

Figure 8.2.1: Indicative annual prices $US of existing anti-retroviral therapy and a hypothetical new drug

30000 United Kingdom

France 25000 Italy

Spain S 20000 U $

e c i r p

15000 e Slovenia v i t a c i Czech Republic d 10000 n I

Latvia 5000 Russia Kazakhstan Philippines Mali India Georgia 0 7 4 1 7 7 3 5 3 4 9 7 4 1 0 7 3 5 6 7 5 1 6 7 1 9 1 4 6 8 2 2 2006 9 5008 0 5 10009 1 3 20005 2 0 25005 6 7 4 50002 9 2 15000 200003 8 250007 2 2 4 4 6 7 8 9 2 9 5 7 8 6 6 7 2 0 6 1 4 5 4 9 1 8 0 5 3 1 1 1 2 2 2 2 3 3 4 6 2 9 2 6 1 1 1 1 2 2 2 Per Capita GNI $US

Indicative price existing treatment Indicative price new drug

Spread sheet showing the calculation of an indicative ‘value for money’ prices for existing antidepressant treatment and a hypothetical new drug. The calculations are given for South Africa with and without assumed productivity gains resulting from effective treatment

Antidepressant efficacy Estimate Range Assumptions Efficacy of no treatment 0% Efficacy of existing treatments 60% For simplicity, patients are assumed to be 100% compliant with their medication Efficacy of new treatment 75% 65%-85% Efficacy defined as proportion of patients with ≥50% reduction in HAM-D Disease duration # days Untreated depression 182 Efficacy data based on: Einarson TR, Arikian SR, Casciano J and Doyle JJ. Comparison of extended Successfully treated depression 56 release venlafaxine, selective serotonin reuptake inhibitors and tricyclic antidepressants in the treatment Unsuccessfully treated depression 182 of depression: a meta-analysis of randomized controlled trials. Clinical Therapeutics 1999; 21(2):296-308.

Quality of life Estimate Range 6 month duration, based on recommended duration of maintenance therapy following successful 8 Untreated depression 0.62 week acute phase Successfully treated depression 1.00 (0.7-1.0) Unsuccessfully treated depression 0.62 For simplicity, if patients fail their first choice treatment, they do not try other treatments

QALYs Time depressed Time well QALYs QoL estimates based on: Chisholm D, Sanderson K, Ayuso-Mateos JL and Saxena S. Reducing the global QALYs no treatment 182.00 0.00 0.31 burden of depression. British Journal of Psychiatry 2004; 184:393-403. (Weighted average assuming QALYs existing treatments 106.40 75.60 0.39 23% patients severe (QoL=0.24), 47% moderate (QoL=0.65) and 30% mild depression (QoL=0.86)) QALYs new treatment 87.50 94.50 0.41 New and existing treatments assumed to have no impact on suicide rates, therefore mortality from QALYs Gained Increment suicide not included in the model. With existing treatments compared with no treatment 0.08 With new treatment compared with no treatment 0.10

Goal seek Country's GNI per capita in USD (South Africa) $2,780

Indicative price (USD) Annual cost of drug Existing treatments (compared with no treatment) $438 New treatment (compared with no treatment) $547

Figure 8.2.2: Indicative annual prices $US of existing anti-depressant therapy and a hypothetical new drug

$6,000 United Kingdom

France $5,000

Italy $4,000 S U $ Singapore e c i r P

$3,000 e v i t a c i d n

I $2,000

Spain $1,000 Greece Czech Republic Slovenia India Mali Latvia $0 0 5 10 15 20 25 30 Per Capita GNI $000US

Indicative price existing treatment Indicative price new drug

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