Balancing Innovation and Access: Insights from AIM's Fair Pricing Model and Its Current and Future Applications.

Key Points for Decision Makers

Fair prices remain substantially lower than net prices despite confidential discounts, indicating that reliance on rebates alone is insufficient to ensure affordability. The AIM fair price model can strengthen buyers’ negotiating positions and inform pricing and reimbursement discussions. Applying this model could generate substantial savings, of up to €27 billion annually across Europe.

Introduction

The right to healthcare, including access to essential medicines, is a fundamental human right and is a pillar of individual well-being and societal welfare. However, healthcare systems around the world face significant challenges not only due to the growing number of patients and aging populations, but also because of the increasing number of treatment options and rising costs of new medicines. Between 2008 and 2021, the mean launch prices of new drugs in the USA increased exponentially by 20% per year. By 2020–2021, nearly half (47%) of newly released drugs came to the market, with annual prices exceeding $150,000. Even after factoring in manufacturer discounts and shifts in the types of drugs being introduced (such as the recent surge in oncology treatments and high-cost specialty medicines), mean net prices still increased by about 11% annually [ 1 ]. High drug prices are driven by high profit margin [ 2 ], patent-based monopoly power, limited competition and lack of regulation, the sequential or combination use of therapies, and strong pressure from patients and clinicians for reimbursement in serious diseases, further amplified by industry lobbying power. Therefore, government and/or payer intervention is needed to address these market failures [ 3 ].

There is continuous debate over whether new medicines justify their costs and whether they might divert resources from other healthcare services or broader societal priorities. A systematic evaluation of oncology approvals (2009–2013) by the European Medicine Agency (EMA) found that most drugs entered the market without evidence of survival or quality-of-life benefit, and after at least 3.3 years post-approval, conclusive benefit remained absent for most indications [ 4 ]. Likewise, the Belgian Health Care Knowledge Centre (KCE) evaluated the impact of new cancer treatments across 12 indications since 2004, comparing patient survival outcomes with related health insurance costs over a 15-year period. The findings indicated that despite rising expenditures, meaningful gains in survival were often lacking. The KCE highlighted ongoing uncertainties regarding the added value of these therapies both at the time of approval and post-marketing. Challenges also included difficulties in assessing quality of life, reliance on surrogate endpoints, and lack of pricing transparency [ 5 ]. Given these challenges, health systems are increasingly conducting health technology assessments (HTA), such as the recently implemented joint clinical assessments (JCAs) at the EU level [ 6 ], and through these assessments, determine whether a technology meets minimum effectiveness criteria and cost-effectiveness thresholds. However, complementary approaches, such as fair pricing models [ 7 ] and managed entry agreements (MEAs), may still be needed to address challenges posed by new drugs with a high budget impact [ 8 ].

Managed entry agreements typically involve confidential discounts and rebates that remain undisclosed [ 9 ]. As a result, countries with a lower gross domestic product (GDP) per capita may pay more, as they base their prices on inflated list prices through International Reference Pricing (IRP), thus benchmarking against undiscounted and artificially high prices [ 10 ]. Therefore, such confidential financial arrangements are not a sustainable solution and can further exacerbate inequalities in access to medicines between member states [ 11 ]. An opposite and more constructive approach is cross-country collaborations to strengthen negotiating positions and share resources and knowledge, such as, e.g., the Baltic Procurement Initiative, BeNeluxA Initiative, Fair and Affordable Pricing, Nordic Pharmaceutical Forum, or Valletta Declaration [ 12 ]. In the future, Joint EU HTA will hopefully not only help reduce uncertainties but also support joint price negotiations, thereby improving access to therapies across a broader region. It is, however, important that countries be able to initiate joint price negotiations themselves, and not only companies, as is currently the case with BeNeLuxA [ 13 ]. Knowledge of realistic R&D and production costs, alongside cost-effectiveness evaluations, would be beneficial for price negotiations worldwide [ 2 ]. The International Association of Mutual Benefit Societies (AIM) developed a Fair Pricing Model (FPM) in 2019 aimed at recalibrating pharmaceutical pricing dynamics and encouraging transparency [ 14 ]. This tool aims to establish an objective and transparent pricing framework for decision-makers using an algorithm proposing how to factor in the underlying research and development (R&D), production, sales, and medical information costs while reflecting therapeutic value and allowing fair returns for pharmaceutical companies (Fig. 1 ). Fig. 1 Parameters of the AIM fair pricing model (FPM). The FPM uses a straightforward and transparent algorithm to calculate an average European price for the treatment of one patient in a specific indication. The model is designed to recoup incurred research and development (R&D) on the total number of patients who will be treated with the medicine during a 10-year period, cover production costs for the treatment, allow limited expenditure on sales and medical information, and provide a reasonable profit, potentially increased with a substantial bonus for medicines with added therapeutic value. As shown in the figure, each cost element is either included as a lump sum (of €250 million for any new active substance for global R&D and ranging from €10 to €750 per treatment month for production) or as a fixed share (20% of R&D for sales/medical information and 8% of all costs for profit). Lump sum elements can be replaced by real documented costs with a cap of €2.5 billion for global R&D. To reflect the reality of potential sales, the model considers that only 50% of the European target population calculated on the basis of the prevalence or incidence of the disease will be treated (e.g., due to prescription restrictions or lack of infrastructure) and the potential competition with a maximum of two competitors. The innovation bonus meant to stimulate innovation is rooted in the cost elements (range from 5% to 40% of additional profit) and is based on objective criteria such as curative effect, overall survival gains, or absence of alternative treatment. The innovation bonus is considered a strength of the model, serving as a motivation for companies to innovate, while allowing Member States and patients to spend their money on added value and health benefits.

The model calculates a price aligned with the World Health Organization’s (WHO) definition of a fair price: “one that is affordable for health systems and patients and that at the same time provides sufficient market incentive for industry to invest in innovation and the production of medicines” [ 15 ]. Moreover, the model enables medicine pricing that is transparent, equitable, and based on the value of treatments according to the health system, rather than the so-called value-based pricing used by companies, which focuses narrowly on the perceived value.

To explore the model’s potential, to assess discrepancies between calculated fair prices and actual market prices, and to estimate the potential savings for healthcare systems, we conducted research on ten market-protected medicines across six European countries: Belgium, Estonia, Germany, the Netherlands, Slovenia, and Switzerland. These countries have different populations and economic sizes.

Methods

The list of new medicines for human use with marketing authorization, granted between 2015 and 2018, was extracted from the EMA database. Starting the inclusion period in 2015 is justified by the milestone of the arrival of antiviral treatments for hepatitis C with costs exceeding €40,000 per patient, putting high pressure on health expenditure [ 16 ]. Medicines entering the market after 2018 were excluded as they had not yet been reimbursed in all participating countries during the study year (2020). The top 5 medicine classes (ATC 1 level 4) in terms of expenditures and the top 5 classes in terms of volume growth for Belgium in 2020 and 2019 were selected and subsequently analyzed in all participating countries. For each of the ATC classes selected, a list of new medicinal products was extracted from the database, when feasible, choosing the first-in-class and if possible, excluding the medicines with more than one indication in the original registration. Additional criteria for the final selection of ten medicines included a mix of high- and low-budget-impact medicines, the use of the medicine in monotherapy treatments, new modes of action, a mix of orphan and non-orphan indications, and relevance for all participating countries. As much as possible, medicines not subject to confidential pricings were favored. A final decision on selecting ten medicines from the list was made by all authors, most of whom represent participating countries.

The fair price for each medicine was calculated using the Fair Price Calculator [ 17 ] through the publicly accessible webtool ( https://fairpricingcalculator.eu ). Lump sums as recommended by the AIM model were used for R&D and production cost. The R&D lump sums represent a range of plausible scenarios: €250 million reflects the minimum estimated cost required to bring a drug to market. €2.5 billion serves as an upper cap on the basis of documented real costs and confidential data, as reported by DiMasi [ 18 ]. €800 million is used as a mid-range estimate, aligning with publicly available data on average R&D costs specific calculations [ 19 , 20 ].

The lump sums for production could accommodate the production costs of any new drug. Literature analyzing real production costs of specific medicines suggest that these lump sums are generous and could potentially be reduced [ 2 , 21 – 25 ].

The prevalence and incidence, the posology, and the duration of a standard treatment are taken from the reimbursement files of the Joint Federal Committee in Germany (G-BA), the decision-making body of the German healthcare system regarding reimbursement of medicines. We calculated the full standard treatment duration, as well as the gross and net costs for 1 month’s treatment for each medicine in each participating country using the average posology per month and the list prices applied in 2020, as provided by AIM members. Since some medicines are reimbursed through confidential discounts, net costs were not publicly available and required an estimation for each country. Switzerland and Slovenia could not disclose estimated net prices. The fair price was calculated at ex-factory level. The national list and net prices and expenses could include VAT, mark-ups, and co-payments, depending on the (public) availability of the data.

To determine the savings on the health budgets, the following method was applied. For the ten selected medicines, the difference between fair and actual price was determined to calculate the savings on the expenditure per medicine when a fair price was applied. The combined savings of the ten medicines divided by the total expenditure of the ten selected medicines generated a reduction percentage that was applied on the total 2020 expenditure of new, market-protected medicines marketed between 2015 and 2018.

Lastly, a large language model (ChatGPT) was used to generate Fig. 2 on the basis of the study results. The authors reviewed and ensured its accuracy. Fig. 2 Fair prices of 10 medicines (12 indications) in relation to the median list prices of the 6 participating countries. The red horizontal line represents the median gross price of each medicine for Belgium, Estonia, Germany, the Netherlands, Slovenia, and Switzerland. The orange bars represent the modeled fair price (FP) for each medicine or indication calculated with the €800 million research and development (R&D) lump sum. The difference between the FP and the median gross price is indicated by the hatched area (if the FP is lower than the actual median gross price) or by the dark orange area (if the FP is higher than the actual median gross price).

Results

Selection of Medicines

For this study, we selected ten medicinal products, among others, on the basis of volume, budget impact, and relevance for all participating countries. Three medicines were indicated for cancer: daratumumab (Darzalex®) for multiple myeloma, trifluridine with tipiracil (Lonsurf®) for metastatic colorectal or stomach cancer, and palbociclib (Ibrance®) for locally advanced or metastatic breast cancer. Three medicines were for the treatment of a (ultra) rare disease: emicizumab (Hemlibra®) for preventing bleeding in patients with hemophilia A with factor VIII inhibitors (first indication) or without factor VIII inhibitors (second indication), selexipag (Uptravi®) for pulmonary hypertension, and mepolizumab (Nucala®) as an add-on treatment for severe refractory eosinophilic asthma in adults. Additionally, four medicines for chronic diseases were included: ocrelizumab (Ocrevus®) for relapsing forms of multiple sclerosis (RMS) and early primary progressive multiple sclerosis (PPMS), glecaprevir with pibrentasvir (Maviret®) for hepatitis C, dolutegravir with abacavir and lamivudine (Triumeq®) for human immunodeficiency virus (HIV), and semaglutide (Ozempic®) for type 2 diabetes. Two out of the ten medicines had an orphan designation (Darzalex ® and Nucala®) at the time of registration. The indication(s) included in the study were those at the time of initial market approval (two initial indications for Ocrevus), except for Hemlibra®, for which a second indication approved within the first year was also included, as the ultra-rare first indication might not properly reflect the market for this medicine.

Discrepancies Between Fair and Net Prices

Using average monthly posology and 2020 list or net prices provided by AIM members, we calculated full treatment durations and gross and net costs (if available) for 1 month’s treatment per medicine in each participating country. Table 1 presents the specific parameters used for the calculation of the fair price for each medicine. Fair prices were calculated on the basis of the varying assumptions (€250 million, €800 million, and €2.5 billion) of R&D expenses (Table 2 ). For subsequent analyses and further calculations, the €800 million estimate is used as the base-case scenario. Table 1 Parameters used to calculate the fair price Brand name Active substance Type of disease Prevalence (P)/incidence (I) Competitors Production cost (€) Rare disease Duration of treatment Innovation bonus Darzalex® Daratumumab Cancer 3.14/100,000 (I) 1 Biological (150) No 5 months 5% (life-threatening) Ocrevus® PPMS Ocrelizumab Rare PPMS = 2.19/10,000 (P) 0 Biological (750) Yes 120 months 15% (debilitating, minor impact, no alternative) Ocrevus® RMS Chronic 0.22% (P) 2 Biological (150) No 120 months 10% (debilitating, minor impact) Lonsurf® Trifluridine/tipiracil Cancer 9.43 /100,000 (I) 1 Chemical (50) No 2 months 5% (life-threatening) Maviret® Glecaprevir/pibrentasvir Chronic 0.14% (P) 2 Chemical (50) No 2 months 35% (life-threatening, curative) Uptravi® Selexipag Ultra-rare 0.79/100,000 (P) 2 Chemical orphan (250) Yes 120 months 10% (debilitating, minor impact) Hemlibra® First indication Emicizumab Ultra-rare 0.14/100,000 (P) 0 Biological orphan (750) Yes 120 months 15% (debilitating, no alternative, minor impact) Hemlibra® Second indication Rare 0.27/10,000 (P) 2 Biological orphan (750) Yes 120 months 15% (debilitating, no alternative, minor impact) Ibrance® Palbociclib Cancer 24.72/100,000 (I) 2 Chemical (50) No 9 months 10% (life-threatening disease 5% and pfs gain of at least 6 months) Triumeq® Dolutegravir/abacavir/lamivudine Chronic Number in Europe = 866,899 2 Chemical (50) No 120 months 5% (life-threatening) Ozempic® Semaglutide Chronic 2.88% (P) 2 Biological/5 (high prevalence) = 30 No 120 months 5% (life-threatening) Nucala® Mepolizumab Rare 2.19/10,000 (P) 2 Biological orphan (750) Yes 120 months 10% (life-threatening, minor effect) The table presents the different parameters used to calculate the fair price of various pharmaceutical drugs. Each row corresponds to a specific drug, listing key factors relevant for pricing such as the brand name and active substance, the type of disease the drug treats (for example, cancer, chronic, rare, or ultra-rare), and the prevalence or incidence rates, which indicate how common the disease is. It also includes the number of competitors for the drug, the category of production cost (such as chemical, biological, or orphan drug, with associated cost figures), and whether the disease is classified as rare or ultra-rare. Additionally, the table specifies the duration of treatment in months and a percentage value representing the drug’s innovation or therapeutic impact PPMS primary progressive multiple sclerosis, RMS relapsing forms of multiple sclerosis Table 2 Fair prices (FP) per month of treatment (€) for three different lumpsums for R&D, actual costs (AC) per country (gross and net costs when applicable), and difference between fair price (R&D of € 800 million) and actual cost (%) Brand name Fair price (R&D €250M) Fair price (R&D €800M) Fair price (R&D €2.5B) Germany (gross/net costs) Germany FP-AC (%) Belgium (gross/net costs) Belgium FP-AC (%) The Netherlands (gross/net costs) The Netherlands FP-AC (%) Estonia (gross/net costs) Estonia FP-AC (%) Slovenia (gross costs) Slovenia FP-AC (%) Switzerland (gross costs) Switzerland FP-AC (%) Median (gross) Darzalex® 861 2,384 7,089 14,114 − 83% 16,319 − 85% 14,247 − 83% Hospital drug, no data NA 13,846 − 83% 15,576 − 85% 14,247 12,703 − 81% 9,726 − 75% Ocrevus® 1,708 − 89% (RMS) 1,625 − 88% (RMS) 1,846 − 90% (RMS) Hospital drug, no data NA 1,718 − 89% (RMS) 1,668 − 89% 1,708 PPMS 935 962 1,046 RMS 181 188 212 1,538 − 88% (RMS) 969 − 81% (RMS) Lonsurf® 632 1,900 5,816 2,492 − 24% 2,300 − 17% 2,400 − 21% 2,740 1,397 − 31% 2,003 − 5% 2,878 − 34% 2,446 2,243 − 15% 2,036 − 7% + 36% Maviret® 808 2,428 7,436 12,187 − 80% 12,000 − 80% 13,080 − 81% 18,876 − 87% 12,028 − 80% 13,850 − 82% 12,633 10,986 − 78% 7,248 − 67% 9,627 − 75% Uptravi® 2,090 6,039 18,244 2,548 + 137% 3,307 83% 3,419 + 77% 3,340 + 81% No data NA 4,180 44% 3340 2,293 163% 1,703 + 255% Hemlibra® 29,099 − 96% (second) 31,282 − 96% (second) 34,071 − 97% (second) 34,546 − 97% (second) 34,083 − 97% (second) 29,110 − 96% (second) 30,196 First indication 4,442 12,184 36,114 Second indication 977 1,098 1,470 26,189 − 96% (second) 18,644 − 94% (second) 13,629 − 92% (second) 17,618 − 94% (second) Ibrance® 135 304 824 1,962 − 85% 3,247 − 91% 2,002 − 85% 2,742 − 89% 1,984 − 85% 2,926 − 90% 2,372 1,765 − 83% 1,961 − 84% 1,398 − 78% Triumeq® 64 79 127 780 − 90% 797 − 90% 858 − 91% Tender, no data NA 679 − 88% 1,004 − 92% 797 702 − 89% Ozempic® 34 35 39 74 − 53% 85 − 59% 95 − 63% 96 49 − 64% 82 − 57% 98 − 64% 90 66 − 47% − 29% Nucala® 950 1,092 1,532 999 9% 1,004 9% 1,029 6% Hospital drug, no data NA 925 18% 1,155 − 5% 1004 899 21% This table presents a comparison of fair prices and current market prices for 1 month of treatment with various pharmaceutical drugs, calculated using three different lump sum amounts allocated for research and development (R&D): 250 million, 800 million, and 2.5 billion euros. For each drug, the table presents the estimated fair price per month on the basis of these R&D costs and the gross and estimated net price when the medicine is under contract. For Ocrevus ® , fair prices were calculated for the two indications that were both registered concurrently, using half the lump sum for each. For Hemlibra ® , the second indication was approved in a later stage. Consequently, the first indication was assigned the full R&D cost, while the second indication was allocated 10% of the total R&D expenses. Slovenia and Switzerland could not provide net prices. For Germany, Belgium, the Netherlands, and Estonia, estimated net prices are displayed when a managed agreement is applicable or a discount is given. Products with only one price in the column “Country (Gross/Net Cost)” are not subject to MEAs; for these products, gross and net prices are equal. Slovenia and Switzerland reported confidential agreements for all products but could only disclose the listed gross prices. The difference between the fair price and the real costs is given in %. For Ocrevus ® and Hemlibra ® the fair price was taken into account for the second indications (RMS for Ocrevus ® and preventing bleeding in patients with hemophilia A without factor VIII inhibitors for Hemlibra ® ) to calculate the difference between fair price and real costs FP fair prices, AC actual costs, R&D research and development

Two medicines followed specific calculation rules in AIM’s model, implying that a 10% surcharge is associated with the second (and subsequent) indication to account for additional research costs. For Ocrevus®, as two indications were authorized concurrently by the EMA, the R&D costs (including the 10% surcharge) were equally distributed between them, resulting in R&D costs of €440 million for each indication (€880 million divided by 2). For Hemlibra®, the first indication was assigned the full R&D lump sum, while the second indication was allocated 10% of the total R&D lump sum, resulting in fair prices per treatment month of €12,184 for the initial indication and €1098 for the second, on the basis of R&D costs of €800 million and €80 million, respectively.

Table 2 also presents the estimated gross and net monthly treatment costs. When a MEA was applicable, the net price was confidential. Therefore, we applied an average reduction on the basis of the average rebate in 2020, as disclosed by AIM members: 30%, 39.6%, and 49% for the Netherlands, Belgium, and Estonia, respectively. Switzerland and Slovenia could not disclose estimated average and therefore only public list prices were used. For Germany, a rebate of 10% is applied for all selected medicines, reflecting the average confidential rebates of insurance companies.

The base-case scenario, using a R&D lump sum of €800 million in the Fair Price Calculator, reveals substantial discrepancies between fair and real (median) prices for eight out of the ten selected medicines (Table 2 and Fig. 2 ). Although the real cost is lower than the list prices due to confidential price negotiations, large differences remain even when net prices are considered. For Ocrevus ® and Hemlibra ® , fair prices were calculated for two indications. The median is calculated on the basis of the gross prices of six countries presented in Table 2 .

Chronic and anticancer medicines show a wider difference between fair and net prices, with the fair price of Triumeq® representing only 10% of the net price and Ibrance® 13%. In contrast, for (ultra-)rare indications such as Uptravi® and Nucala®, fair prices were higher. However, both for Ocrevus® and Hemlibra®, when considering the second indications, fair prices are significantly lower than real prices. To better reflect company expenditures and healthcare system costs, the lowest fair prices of Ocrevus® and Hemlibra® were included in further calculations.

In Belgium, the difference between fair prices and actual gross costs per month ranged from − 96 to + 137%, calculated as (fair price − real gross cost)/real gross cost × 100 with an average deviation of − 45% (Table 2 ). For Germany, the Netherlands, Estonia, Switzerland, and Slovenia, fair prices were on average 45%, 53%, 48%, 59%, and 59% lower than real prices, respectively (− 53% on average). When the same analysis is applied to net prices, fair prices are, on average, 33% lower than net prices across Europe.

For half of the medicines, the negative delta, representing the potential savings between fair and gross price, was above 80% in all countries for at least one indication.

Impact of Parameter Selection and Variation on Fair Price Calculations

The AIM model allows for selection of various default values for most parameters on the basis of characteristics of each medicine. Table 3 presents the details of the fair price calculations for each medicine and studied indication and allows for examination of how they influence the calculated fair price. Table 3 Detailed fair price calculations per month of treatment (€) with a R&D lumpsum of €800 million (M) Darzalex® Ocrevus® (PPMS) Ocrevus® (RMS) Lonsurf® Maviret® Uptravi® Hemlibra® First indication Hemlibra® Second indication Ibrance® Triumeq® Ozempic® Nucala® Global R&D € 800M € 440M € 440M € 800M € 800M € 800M € 800M € 80M € 800M € 800M € 800M € 800M Prevalence or incidence of the indication(s) 3.14/100,000 2.19/10,000 0.22% 9.43/100,000 0.14% 0.79/100,000 0.14/100,000 0.27/10,000 24.72/100,000 Number in Europe = 866,899 2.88% 2.19/10,000 European target population of this/these indications 140,515 98,002 984,500 421,993 626,500 3,535 627 12,083 1,106,220 866,899 12,888,000 98,002 R&D cost/patient per month of treatment (€) 1,633 27 8 1,359 1,373 4,056 7,630 119 173 17 1 146 Production costs per month (€) 150 750 150 50 50 250 750 750 50 50 30 750 Treatment duration (months) 5 120 120 2 2 120 120 120 9 120 120 120 Total production costs (€) 750 90,000 18,000 100 100 30,000 90,000 90,000 450 6,000 3,600 90,000 Sales and medical info 20% of R&D costs Profit 8% Innovation bonus % of all costs (R&D, production, sales) 5% 15% 10% 5% 35% 10% 15% 15% 10% 5% 5% 10% Fair price (€) 2,384 962 188 1,900 2,428 6,039 12,184 1,098 304 79 35 1,092 Share of R&D in the price 69% 3% 4% 72% 57% 67% 63% 11% 57% 21% 3% 13% Share of production in the price 6% 78% 80% 3% 2% 4% 6% 68% 16% 63% 85% 69% This table provides detailed calculations of the fair price per month of treatment of the ten selected drugs assuming a fixed global R&D lump sum of €800 million. It lists each drug by brand name and includes information on the prevalence or incidence of the disease they treat used to defining the estimated European target patient population affected by the disease for a 10-year period and the treatment duration in months, and calculates the R&D cost per patient per month of treatment for a European patient on this base, considering a 50% treatment rate and the number of competitors. It also details the production cost per month according to the composition of the medicine. Additional factors include sales and medical information costs (set as a percentage of R&D costs), profit margin, and an innovation bonus percentage applied to all costs. The resulting fair price per month for each drug is calculated, along with the share of the fair price attributable to R&D costs and to production costs R&D research and development

R&D Costs

The relatively weak influence of global R&D costs is clear; for five out of the ten studied medicines, R&D costs per patient account for only 3–21% of the monthly fair price. This share can be related to the relative importance of other parameters (such as production cost and the innovation bonus) but it also reflects very low absolute values for R&D. The R&D costs that need to be recouped for 1 month of treatment range from €1 to €17 for chronic diseases with long-term treatment and €27 to €146 for rare diseases. For cancer and orphan medicines, the absolute R&D values are higher, in direct link with the more reduced patient population, but never approach the net prices paid. The fair pricing model is very sensitive to patient populations as shown by the R&D costs to be recouped for 1 month of treatment for ultra-rare indications of Uptravi® and Hemlibra®, which exceed €4000.

Furthermore, Table 2 presents the details of the fair price calculations for each medicine in the studied indication(s) applying different R&D lump sums, highlighting that the variation of this parameter often has a minor impact on the results. For Ozempic® and Ocrevus® (for the indication RMS) for example, the fair price for 1 month of treatment rises from €34 (for €250 million R&D) to €39 (for €2.5 billion R&D) and from €181 to €212, respectively.

Innovation Bonus

Four medicines in this study were granted a 5% bonus. Among these, two were cancer treatments that obtained this minimal bonus solely due to their indication for a life-threatening disease, without demonstrated clinical benefits in terms of progression-free survival (PFS) or overall survival (OS) at the time of marketing authorization.

Among the evaluated cancer therapies, only Ibrance® was granted a 10% bonus, justified by a PFS gain of at least 6 months at the time of market approval [ 26 ]. The highest bonus in the AIM study (35%) was attributed to Maviret®, a treatment for hepatitis C that achieves curative outcomes. However, none of the assessed medicines was considered worthy of the maximum bonus of 40%.

Production Cost

Production costs account for a significant share of the fair price of six analyzed cases, ranging from 63% to 85% of the total price. The monthly production costs are directly related to the scale of the lump sum applied, with default parameters ranging from €50 to €750 for classic medicines. For the treatment of a high prevalence chronic condition, which is the case for semaglutide, the authors considered that the default lump sum did not reflect the actual low production costs associated with major volumes and applied a fivefold reduced lump sum, following AIM recommendations in the accompanying paper of the model [ 14 ].

Potential Savings on the New Medicines’ Expenditures

To calculate potential savings, reduction percentages were determined as outlined in the methodology. Taking Germany as an example, the fair price of Darzalex® was estimated to be 81% lower than its actual market price. Applying this reduction to the 2020 net budget for Darzalex® yields potential savings of €352,284,111. Repeating this simulation across the ten selected medicines, total savings amount to €910,236,632, representing a 74% reduction compared with their combined budget for Germany.

Table 4 presents the estimated savings on both gross, and where available, net pharmaceutical budgets for newly marketed, patent-protected medicines across the countries included in this study. Reduction percentages varied by country, ranging from 48 to 81% for gross budgets, and from 37 to 74% for countries with available net budget data, with average weighted reductions of 77% of the gross expenses and 73% of net expenses on European level. Table 4 Potential savings on gross and net medicine budget across selected European countries (in euros) Germany Belgium Estonia The Netherlands Switzerland Slovenia Total Population covered (2020) 73,200,000 11,500,000 832,075 16,500,000 8,638,000 2,102,000 112,772,075 Total expenditures on medicines (gross) 49,156,000,000 5,586,166,000 222,941,176 5,953,266,589 7,560,188,311 716,929,839 69,195,491,915 Expenditures new, market-protected medicines (gross) 8,656,717,600 1,528,395,724 63,725,490 248,486,522 1,786,590,060 175,474,245 12,459,389,641 Total expenditures new, market-protected medicines (net) 6,934,581,196 1,151,960,682 32,500,000 234,045,354 NA NA 8,353,087,232 Expenditures on ten selected medicines (or less) GROSS 1,360,071,222 340,793,431 20,789,021 268,098,610 216,716,123 24,178,169 2,230,646,577 Expenditures on ten medicines (or less) net 1,224,064,100 230,286,862 12,278,373 229,534,160 NA NA 1,696,163,495 Savings on the gross expenditures of the ten selected medicines when calculated Fair price with €800 million R&D −1,046,225,755 −274,275,681 −12,353,799 −192,481,377 −169,971,684 −11,616,550 −1,706,924,846 Savings on the net expenditures of the ten selected medicines when calculated Fair price with €800 million R&D −910,236,632 −163,795,133 −4,505,247 −159,322,477 NA NA −1,237,859,489 Reduction percentages (gross) a −77% −81% −59% −72% −78% −48% −77% Reduction percentages (net) a −74% −71% −37% −69% NA NA −73% Extrapolation savings (gross) €800 million R&D −6,659,122,522 −1,230,075,876 −37,868,638 −178,400,880 −1,401,232,714 −84,307,680 −9,591,008,310 Extrapolation savings (net) €800 million R&D −5,156,682,425 −819,350,055 −11,925,076 −162,453,753 NA NA −6,150,411,308 This table presents the total expenditures for pharmaceuticals for the participating countries (for information purposes) and all other numbers (population and expenditures) to calculate the potential savings NA not applicable a The reduction percentages were calculated by dividing the savings on the gross/net expenditures of the ten selected medicines by the total gross/net expenditures of the selected medicines

These percentages were subsequently applied to the 2020 budgets for new, market-protected medicines firstly introduced on the market between 2015 and 2018. The estimated total gross savings amounted to €9.6 billion annually for the six participating countries. Even when accounting for confidential price negotiations, the savings remain substantial at €6.2 billion per year for Germany, the Netherlands, Belgium, and Estonia.

When extrapolated to the entire European Union (EU-27), with a population of 447.7 million in 2020, potential annual savings could reach €38 billion on gross budgets and €27 billion on net budgets for new, market-protected medicines.

Discussion

Our study shows that there is a large discrepancy between the price of a medicine and its calculated fair price. In most cases, applying the fair pricing model led to substantially lower costs. Even when accounting for confidential price negotiations, a fair price was on average 33% lower than the net price. These findings indicate that implementing fair pricing for new medicines could provide substantial budgetary relief for national healthcare systems. Extrapolated to the entire European population, these savings could reach net savings of more than €27 billion yearly. Nevertheless, an analysis that focuses on medicines with the highest expenditure and/or the greatest growth may not be fully extrapolatable to all medicines, and therefore the savings should be interpreted as hypothetical and illustrative.

Our results are in line with previous studies done by two not-for-profit health insurers. The German Techniker Krankenkasse (TK), together with experts from Bremen University, applied the AIM fair pricing model in real-world scenarios involving seven high-priced drugs in Germany. The results revealed significant differentials, with fair prices (with R&D cost of €250 million) estimated to be up to 13 times lower than current net prices in Germany, suggesting a potential average reduction of 63 % for market-protected medicines, translating to more than €13 billion in annual savings for the German healthcare budget [ 27 ]. Similar research was carried out by the Belgian Mutual Fund Solidaris, showing fair prices up to 18 times lower than net prices in Belgium and a potential average reduction of 77% for all innovative medicines since 2015, translating to potential yearly savings of more than €1 billion for the Belgian medicine’s budget [ 28 ]. Particularly striking are the disparities observed in orphan medicines and oncology treatments in both Germany and Belgium, highlighting the urgent need for improvement in these critical areas.

Pharmaceutical companies often justify the high prices of newly marketed treatments, citing the substantial costs associated with R&D and the necessity of recouping major investments made in developing new medicines. This is important to consider when one of the goals is to sustain innovation in the pharmaceutical industry. The AIM model assumes a baseline allocation of €250 million per medicine to account for global R&D expenses, reflecting an estimated average global development cost. However, the model provides flexibility for pharmaceutical companies to recoup higher actual costs, subject to documented accounting evidence, up to a maximum of €2.5 billion. This ceiling was established on the basis of analyses using methodologies most favorable to the industry, ensuring that the upper limit reflects a robust estimation of R&D costs [ 18 ].

For orphan medicines, clinical trials typically involve a limited number of patients, which significantly reduces R&D expenditures, up to 23% of those for non-orphan medicines according to some research, making an estimate of €250 million more realistic [ 29 ]. This is reflected by the model when applying an R&D cost of €2.5 billion for medicines for rare diseases, where the calculated fair price exceeds the market price set by manufacturers, indicating that the R&D costs are likely much lower.

For highly priced medicines, a correspondingly high level of efficacy is generally expected. In the study, only modest innovation bonuses could be attributed on the basis of available scientific evidence for each of the seven medicines. These findings are consistent with the report from the Belgian Health Care Knowledge Centre (KCE), which found minimal added value in new oncology medicines [ 5 ]. The AIM fair pricing model allows minimal efficacy to be reflected in the initial calculated fair price and allows, as better results emerge with longer follow-up, upwards adjustment of the price.

To facilitate the use of the model in practice, an online Fair Pricing Calculator was developed [ 17 ]. This Calculator translates AIM’s fair pricing model into a usable tool and incorporates the model’s various parameter assumptions. It calculates a fair price per treatment, further converted into a fair price per month and per year. The Calculator is designed to assist healthcare stakeholders in determining a fair price for a new active substance or a new indication and allows them to compare it to the price paid or currently being negotiated. It provides a single European fair price and proposes an automatic calculation per country according to purchase power parity of the member state.

Our study has some limitations: the calculations in our study are based on a number of assumptions and limited (publicly) available data derived from different sources. Accurate calculation requires transparency. In addition, part of drug development is often publicly funded, for example through government programs, academic research, or charitable grants. The contribution of such investments is frequently not transparent or fully accounted for [ 30 ]. In addition, partnering with pharmaceutical companies has limited academia’s influence to bring drugs to the market at affordable and sustainable prices, highlighting the need for better models of academic-led drug development paired with commercialization strategies [ 31 ]. Furthermore, some critics argue that opportunity costs should not be included in R&D cost calculations, and that the discount rates (cost of capital) used overestimate the true costs [ 32 ]. In our calculations, several assumptions are made conservatively, and in some cases, in favor of the industry; as a result, actual R&D costs and production costs are expected to be lower [ 2 , 21 , 33 ]. Consequently, the resulting fair prices may represent an upper-bound estimate and should be viewed as hypothetical. Nevertheless, the key insight lies in the substantial difference between official prices and the prices generated under these assumptions. Despite the substantial gap between fair and actual prices, and the absence of any clear relationship between price and clinical value, no systematic efforts by authorities or other key stakeholders have been undertaken to address this issue effectively [ 34 ].

The AIM Fair Pricing Model has been presented at both national and European levels and is being explored and gradually exploited by payers and the academic community. The model has been adopted into daily practice in the Netherlands, where Dutch health insurers now routinely use the calculator when negotiating prices with pharmaceutical companies [ 35 ]. There is also potential to apply the model in hospitals for price negotiations in tenders. The Dutch platform Medicine for Society used AIM’s fair pricing model to calculate a cost-based price for the repurposed mexiletine (Namuscla ® ) for adult patients with non-dystrophic myotonia. The objective was to assess the justification of the extreme price increase observed after the repurposing of this medicine [ 36 ]. AIM’s tool demonstrated that prices in Europe should be substantially lower than the requested price for Namuscla ® and that “cost-based pricing models can support fair pricing discussions and reimbursement decisions for repurposed orphan drugs when reliable information about costs can be retrieved” [ 36 ]. Recently, a study comparing four cost-based pricing models, including AIM’s model, reached the same conclusion for medicines for rare diseases. In rare diseases, despite a positive clinical assessment, estimates of cost-effectiveness can be uncertain and may exceed national reimbursement thresholds. In this context, pricing models can help calculate a fair price, providing additional guidance alongside cost-effectiveness data to support better-informed decisions. The feasibility of such calculations depends on the transparency of cost information provided by the manufacturer [ 37 ].

Currently, the AIM model serves as basis for a pricing tool under development by the Horizon Europe funded project ASCERTAIN, a consortium of academics, payers, patients, and healthcare representatives. This consortium aims to improve access to new health technologies, such as medicines and medical devices, by developing a tool to support decision-makers in assessing the cost and value of new health technologies [ 38 ]. Finally, cross‑national collaboration and comprehensive patient-level data collection offer a path to better assess the clinical impact and affordability of innovative therapies [ 39 ].

Conclusions

This study highlights that current prices paid for new medicines are not justified by the underlying costs of research or their therapeutic value, as demonstrated by AIM’s model. The introduction of cost and price transparency has the potential to strengthen buyers’ negotiating positions during pricing and reimbursement discussions, potentially leading to substantial savings on the national health budgets and safeguarding solidarity and sustainability of European health systems. The Fair Pricing Calculator is a useful tool for putting the AIM Fair Pricing Model into practice. Nevertheless, in markets characterized by monopoly power and limited competition, achieving fair pricing requires government intervention, transparency, and mechanisms that align incentives for innovation with healthcare affordability [ 40 ].

In the ATC classification system developed by the WHO, the active substances are classified in a hierarchy with five different levels. See ATCDDD - Structure and principles

Jocelijn Stokx and Anne Hendrickx contributed equally to the study and manuscript.

Change history

7/2/2026

The original online version of this article was revised: to correct the alignment of entries in tables.

Acknowledgements

The authors gratefully acknowledge the contributions of all participating countries and institutions. We would like to extend special thanks to all members of the Pharmaceutical Working Group of the Association Internationale de la Mutualité (AIM) for their insights and support, and to Sibylle Reichert and Mar Moncosí Saballs for their coordination and leadership, which made this study possible.

Funding

The authors did not receive any funding for the work reported in this manuscript.

Declarations

Ethics committee approval

This study does not involve human subjects, and under 45 CFR §46.102(f), was not submitted for institutional review board approval and did not require informed consent.

Conflict of interest statements

Sahar Barjesteh van Waalwijk van Doorn-Khosrovani received research funding from Horizon Europe Cancer Mission, EC grant agreement no. 101104269 (PRIME-ROSE) and Joint Action for Personalised Cancer Medicine (JA-PCM), financed by EU4Health (grant no. 101233450). All authors have no financial conflicts of interest related to this manuscript.

Authors contribution

All authors were involved in the selection of medicines and study design. A representative from each country provided the relevant country-specific data. JS and AH curated the data, conducted the analysis, and wrote the first draft of the manuscript. TKT assisted with the analysis and coordinated the study across countries. All authors reviewed and approved the final version.

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