Deloitte Centre for Health Solutions. 2019. “Ten Years on Measuring the Return from Pharmaceutical Innovation 2019.” https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-ten-years-on-measuring-return-on-pharma-innovation-report-2019.pdf.

Abstract: Not available.

Link: https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-ten-years-on-measuring-return-on-pharma-innovation-report-2019.pdf.

DiMasi, Joseph A, Ronald W Hansen, Henry G Grabowski, and Louis Lasagna. 1991. “Cost of Innovation in the Pharmaceutical Industry.” Journal of Health Economics 10 (2): 107–42. https://doi.org/10.1016/0167-6296(91)90001-4.

Abstract: The research and development costs of 93 randomly selected new chemical entities (NCEs) were obtained from a survey of 12 U.S.-owned pharmaceutical firms. These data were used to estimate the pre-tax average cost of new drug development. The costs of abandoned NCEs were linked to the costs of NCEs that obtained marketing approval. For base case parameter values, the estimated out-of-pocket cost per approved NCE is $114 million (1987 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a 9% discount rate yielded an average cost estimate of $231 million (1987 dollars).

Link: https://doi.org/10.1016/0167-6296(91)90001-4.

DiMasi, Joseph A., Ronald W. Hansen, Henry G. Grabowski, and Louis Lasagna. 1995a. “Research and Development Costs for New Drugs by Therapeutic Category: A Study of the US Pharmaceutical Industry.” PharmacoEconomics 7 (2): 152–69. https://doi.org/10.2165/00019053-199507020-00007.

Abstract: The clinical period (i.e. clinical trial and long term animal testing) development costs of a random sample of new chemical entities (NCEs) were examined for differences in average cost. All of the NCEs studied were first tested in humans between 1970 and 1982, and were classified for the purposes of the study by therapeutic class. The costs of unsuccessful projects were included with those of projects that resulted in US marketing approval. Including income forgone from expending funds before returns are earned ('time costs'), the capitalised (i.e. out-of-pocket plus time) clinical period costs per approved NCE were $US70, $US98, $US103 and $US163 million (1993 dollars) for anti-infective, cardiovascular, neuropharmacological and nonsteroidal anti-inflammatory drugs, respectively. Combining the data for all therapeutic categories, the mean clinical period cost per approved NCE was $US93 million. Omitting costs associated with unsuccessful projects, the mean capitalised clinical period costs for approved NCEs ranged from $US7.1 million (for topical steroids) to $US66.7 million (for cardiovascular agents) [1993 dollars]. The estimates of total clinical period costs per approved NCE depend on average out-of-pocket clinical phase costs, attrition rates across phases (i.e. the rates at which compounds drop out of active testing), the probability of marketing approval, and development and regulatory review times. Phase attrition and approval rates are the most important sources of variability in total clinical period costs between therapeutic categories. Development cost estimates by therapeutic category did not correlate strongly with US sales in the fifth year of marketing. Cardiovascular NCEs had much higher than average sales revenues, but clinical development costs for these drugs were only slightly above average. Conversely, nonsteroidal anti-inflammatory drugs attained average sales revenues, but had much higher than average development costs.

Link: https://doi.org/10.2165/00019053-199507020-00007.

Dimasi, Joseph A., Henry G. Grabowski, and John Vernon. 1995b. “R&D Costs, Innovative Output and Firm Size in the Pharmaceutical Industry.” International Journal of the Economics of Business 2 (2): 201–19. https://doi.org/10.1080/758519309.

Abstract: This study examines the relationships between firm size, R&D costs and output in the pharmaceutical industry. Project–level data from a survey of 12 US–owned pharmaceutical firms on drug development costs, development phase lengths and failure rates are used to determine estimates of the R&D cost of new drug development by firm size. Firms in the sample are grouped into three size categories, according to their pharmaceutical sales at the beginning of the study period. The R&D cost per new drug approved in the US is shown to decrease with firm size, while sales per new drug approved are shown to increase markedly with firm size. Sales distributions are highly skewed and suggest that firms need to search for blockbuster drugs with above average returns. The results are consistent with substantial economies of scale in pharmaceutical R&D, particularly at the discovery and preclinical development phases.

Link: https://doi.org/10.1080/758519309.

DiMasi, Joseph A, Ronald W Hansen, and Henry G Grabowski. 2003. “The Price of Innovation: New Estimates of Drug Development Costs.” Journal of Health Economics 22 (2): 151–85. https://doi.org/10.1016/S0167-6296(02)00126-1.

Abstract: The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per new drug is US$ 403 million (2000 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 11% yields a total pre-approval cost estimate of US$ 802 million (2000 dollars). When compared to the results of an earlier study with a similar methodology, total capitalized costs were shown to have increased at an annual rate of 7.4% above general price inflation.

Link: https://doi.org/10.1016/S0167-6296(02)00126-1.

DiMasi, Joseph A., Henry G. Grabowski, and John Vernon. 2004. “R&D Costs and Returns by Therapeutic Category.” Drug Information Journal 38 (3): 211–23. https://doi.org/10.1177/009286150403800301.

Abstract: Objectives: This study examines the degree to which therapeutic class accounts for variability in drug development costs. It also scrutinizes how sales levels vary across the associated therapeutic classes for those drugs that have reached the marketplace.

Data and Methods: A stratified random sample of 68 investigational drugs that first entered clinical testing anywhere in the world from 1983 to 1994 was selected from the pipelines of 10 pharmaceutical firms. Clinical period cost data were obtained for these compounds by phase. The sample consisted both of drugs that failed in testing and drugs that obtained marketing approval. We grouped the drugs by therapeutic category. Clinical period costs per approved new drug (inclusive of failures) were obtained for the analgesic/anesthetic, antiinfective, cardiovascular, and central nervous system (CNS) therapeutic classes. Worldwide sales profiles for new drugs approved in the United States from 1990 to 1994 over a 20-year product life cycle were computed based on IMS Health sales data. All costs and sales were expressed in year 2000 dollars.

Results: Out-of-pocket clinical period cost per approved drug (inclusive of failures) for cardiovascular ($277 million) and CNS ($273 million) drugs was close to the overall average ($282 million). However, antiinfective drug costs were considerably above average ($362 million) and analgesic/anesthetic drug costs were modestly below average ($252 million). The results were qualitatively similar when the development timelines were used to determine capitalized (out-of-pocket plus time) costs. In comparison to the overall average of $466 million, the capitalized cost per approved drug was slightly lower for CNS ($464 million) and for cardiovascular ($460 million) drugs. The capitalized costs were $375 million for analgesic/anesthetic drugs and $492 million for antiinfective drugs. The mean net present values of life cycle sales for new drugs approved in the first half of the 1990s were $2434 million, $ 1080 million, $2199 million, $3668 million, and $4177 million for all drugs, analgesic/anesthetic drugs, antiinfective drugs, cardiovascular drugs, and CNS drugs, respectively.

Conclusions: Development costs vary substantially from drug to drug. A drug's therapeutic class can explain some of that variability. The sales of new drugs by broad therapeutic category did not correlate well with average development costs. However, given the dynamic nature of pharmaceutical markets and changes over time in research and development (R&D) expenditure shares, the results are still consistent with a model of firm behavior that posits that R&D efforts will generally shift toward high net return, and away from low net return, therapeutic areas.

Link: https://doi.org/10.1177/009286150403800301.

Adams, Christopher P., and Van V. Brantner. 2006. “Estimating The Cost Of New Drug Development: Is It Really $802 Million?” Health Affairs 25 (2): 420–28. https://doi.org/10.1377/hlthaff.25.2.420.

Abstract: This paper replicates the drug development cost estimates of Joseph DiMasi and colleagues ("The Price of Innovation"), using their published cost estimates along with information on success rates and durations from a publicly available data set For drugs entering human clinical trials for the first time between 1989 and 2002, the paper estimated the cost per new drug to be 868 million dollars. However, our estimates vary from around 500 million dollars to more than 2,000 million dollars, depending on the therapy or the developing firm.

Link: https://doi.org/10.1377/hlthaff.25.2.420.

Adams, Christopher Paul, and Van Vu Brantner. 2010. “Spending on New Drug Development.” Health Economics 19 (2): 130–41. https://doi.org/10.1002/hec.1454.

Abstract: This paper replicates DiMasi et al. (J. Health Econ. 2003; 22: 151-185; Drug Inf. J. 2004; 38: 211-223) estimates of expenditure on new drug development using publicly available data. The paper estimates that average expenditure on drugs in human clinical trials is around $27m per year, with $17m per year on drugs in Phase I, $34m on drugs in Phase II and $27m per year on drugs in Phase III of the human clinical trials. The paper's estimated expenditure on new drug development is somewhat greater than suggested by the survey results presented in DiMasi et al. (J. Health Econ. 2003; 22: 151-185; Drug Inf. J. 2004; 38: 211-223). The paper combines a 12-year panel of research and development expenditure for 183 publicly traded firms in the pharmaceutical industry with panel of drugs in human clinical trials for each firm over the same period. The paper estimates drug expenditure by estimating the relationship between research and development expenditure and the number of drugs in development for 1682 company/years (183 firms multiplied by the number of years for which we have financial and drug development information). The paper also estimates expenditure on drugs in various therapeutic categories.

Link: https://doi.org/10.1002/hec.1454.

DiMasi, Joseph A., and Henry G. Grabowski. 2007. “The Cost of Biopharmaceutical R&D: Is Biotech Different?” Managerial and Decision Economics 28 (4–5): 469–79. https://doi.org/10.1002/mde.1360.

Abstract: The costs of developing the types of new drugs that have been pursued by traditional pharmaceutical firms have been estimated in a number of studies. However, similar analyses have not been published on the costs of developing the types of molecules on which biotech firms have focused. This study represents a first attempt to get a sense for the magnitude of the R&D costs associated with the discovery and development of new therapeutic biopharmaceuticals (specifically, recombinant proteins and monoclonal antibodies [mAbs]). We utilize drug-specific data on cash outlays, development times, and success in obtaining regulatory marketing approval to estimate the average pre-tax R&D resource cost for biopharmaceuticals up to the point of initial US marketing approval (in year 2005 dollars). We found average out-of-pocket (cash outlay) cost estimates per approved biopharmaceutical of $198 million, $361 million, and $559 million for the preclinical period, the clinical period, and in total, respectively. Including the time costs associated with biopharmaceutical R&D, we found average capitalized cost estimates per approved biopharmaceutical of $615 million, $626 million, and $1241 million for the preclinical period, the clinical period, and in total, respectively. Adjusting previously published estimates of R&D costs for traditional pharmaceutical firms by using past growth rates for pharmaceutical company costs to correspond to the more recent period to which our biopharmaceutical data apply, we found that total out-of-pocket cost per approved biopharmaceutical was somewhat lower than for the pharmaceutical company data ($559 million vs $672 million). However, estimated total capitalized cost per approved new molecule was nearly the same for biopharmaceuticals as for the adjusted pharmaceutical company data ($1241 million versus $1318 million). The results should be viewed with some caution for now given a limited number of biopharmaceutical molecules with data on cash outlays, different therapeutic class distributions for biopharmaceuticals and for pharmaceutical company drugs, and uncertainty about whether recent growth rates in pharmaceutical company costs are different from immediate past growth rates.

Link: https://doi.org/10.1002/mde.1360.

DiMasi, Joseph A., Henry G. Grabowski, and Ronald W. Hansen. 2016. “Innovation in the Pharmaceutical Industry: New Estimates of R&D Costs.” Journal of Health Economics 47 (May): 20–33. https://doi.org/10.1016/j.jhealeco.2016.01.012.

Abstract: The research and development costs of 106 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug and biologics development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per approved new compound is $1395 million (2013 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 10.5% yields a total pre-approval cost estimate of $2558 million (2013 dollars). When compared to the results of the previous study in this series, total capitalized costs were shown to have increased at an annual rate of 8.5% above general price inflation. Adding an estimate of post-approval R&D costs increases the cost estimate to $2870 million (2013 dollars). Link: https://doi.org/10.1016/j.jhealeco.2016.01.012.

DNDi. 2014. “An Innovative Approach to R&D for Neglected Patients: Ten Years of Experience and Lessons Learned by DNDi.” Drugs for Neglected Diseases Initiative. http://www.dndi.org/wp-content/uploads/2009/03/DNDi_Modelpaper_2013.pdf

Abstract: Not available.

Link: http://www.dndi.org/wp-content/uploads/2009/03/DNDi_Modelpaper_2013.pdf.

DNDi. 2019. “15 Years of Needs-Driven Innovation for Access: Key Lessons, Challenges, and Opportunities for the Future.” Drugs for Neglected Diseases Initiative. https://www.dndi.org/wp-content/uploads/2019/10/DNDi_ModelPaper_2019.pdf

Abstract: Not available. Link: https://www.dndi.org/wp-content/uploads/2019/10/DNDi_ModelPaper_2019.pdf.

Global Alliance for TB Drug Development. 2001. “Executive Summary for the Economics of TB Drug Development.” http://www.tballiance.org/downloads/publications/TBA_Economics_Report_Exec.pdf.

Abstract: Not available.

Link: http://www.tballiance.org/downloads/publications/TBA_Economics_Report_Exec.pdf.

Gunn, Alexander, Shashika Bandara, Gavin Yamey, Flavia D´Alessio, Hilde Depraetere, Sophie Houard, Nicola Viebig, and Stefan Jungbluth. 2019. “Pipeline Analysis of a Vaccine Candidate Portfolio for Diseases of Poverty Using the Portfolio-To-Impact Modelling Tool.” F1000Research 8 (July): 1066. https://doi.org/10.12688/f1000research.19810.1.

Abstract: Background: The Portfolio-To-Impact (P2I) P2I model is a recently developed product portfolio tool that enables users to estimate the funding needs to move a portfolio of candidate health products, such as vaccines and drugs, along the product development path from late stage preclinical to phase III clinical trials, as well as potential product launches over time. In this study we describe the use of this tool for analysing the vaccine portfolio of the European Vaccine Initiative (EVI). This portfolio includes vaccine candidates for various diseases of poverty and emerging infectious diseases at different stages of development.

Methods: Portfolio analyses were conducted using the existing assumptions integrated in the P2I tool, as well as modified assumptions for costs, cycle times, and probabilities of success based on EVI’s own internal data related to vaccine development.

Results: According to the P2I tool, the total estimated cost to move the 18 candidates currently in the EVI portfolio along the pipeline to launch would be about US $470 million, and there would be 0.69 cumulative expected launches during the period 2019-2031. Running of the model using EVI-internal parameters resulted in a significant increase in the expected product launches.

Conclusions: The P2I tool's underlying assumptions could not be tested in our study due to lack of data available. Nevertheless, we expect that the accelerated clinical testing of vaccines (and drugs) based on the use of controlled human infection models that are increasingly available, as well as the accelerated approval by regulatory authorities that exists for example for serious conditions, will speed up product development and result in significant cost reduction. Project findings as well as potential future modifications of the P2I tool are discussed with the aim to improve the underlying methodology of the P2I model.

Link: https://doi.org/10.12688/f1000research.19810.1.

Horvath, Christopher. 2010. “Comparison of Preclinical Development Programs for Small Molecules (Drugs/Pharmaceuticals) and Large Molecules (Biologics/Biopharmaceuticals): Studies, Timing, Materials, and Costs.” In Pharmaceutical Sciences Encyclopedia, by Shayne Cox Gad, pse166. Hoboken, NJ, USA: John Wiley & Sons, Inc. https://doi.org/10.1002/9780470571224.pse166.

Abstract: Successful and efficient development of a new pharmaceutical requires the planning of an integrated development program that coordinates the trilogy of product manufacture—chemistry, manufacturing, and controls (CMC), preclinical studies (distribution, metabolism, and pharmacokinetic [DMPK], pharmacology and toxicology), and clinical trials—within the framework of the regulatory development strategy. Preclinical safety studies must support each successive phase of clinical development, as well as any significant changes to the method(s) of manufacturing, formulating, or administering the pharmaceutical. This article aims to compare the studies, materials, and costs associated with hypothetical preclinical development programs intended to support the clinical development of a small molecule (drug) and a large molecule (biologic).

Link: https://doi.org/10.1002/9780470571224.pse166.

Jayasundara, Kavisha, Aidan Hollis, Murray Krahn, Muhammad Mamdani, Jeffrey S. Hoch, and Paul Grootendorst. 2019. “Estimating the Clinical Cost of Drug Development for Orphan versus Non-Orphan Drugs.” Orphanet Journal of Rare Diseases 14 (1): 12. https://doi.org/10.1186/s13023-018-0990-4.

Abstract: Background: High orphan drug prices have gained the attention of payers and policy makers. These prices may reflect the need to recoup the cost of drug development from a small patient pool. However, estimates of the cost of orphan drug development are sparse.

Methods: Using publicly available data, we estimated the differences in trial characteristics and clinical development costs with 100 orphan and 100 non-orphan drugs.

Results: We found that the out-of-pocket clinical costs per approved orphan drug to be $166 million and $291 million (2013 USD) per non-orphan drug. The capitalized clinical costs per approved orphan drug and non-orphan drug were estimated to be $291 million and $412 million respectively. When focusing on new molecular entities only, we found that the capitalized clinical cost per approved orphan drug was half that of a non-orphan drug. Conclusions: More discussion is needed to better align on which cost components should be included in research and development costs for pharmaceuticals.

Link: https://doi.org/10.1186/s13023-018-0990-4.

Light, Donald W, and Rebecca Warburton. 2011. “Demythologizing the High Costs of Pharmaceutical Research.” BioSocieties 6 (1): 34–50. https://doi.org/10.1057/biosoc.2010.40.

Abstract: It is widely claimed that research to discover and develop new pharmaceuticals entails high costs and high risks. High research and development (R&D) costs influence many decisions and policy discussions about how to reduce global health disparities, how much companies can afford to discount prices for lower- and middle-income countries, and how to design innovative incentives to advance research on diseases of the poor. High estimated costs also affect strategies for getting new medicines to the world's poor, such as the advanced market commitment, which built high estimates into its inflated size and prices. This article takes apart the most detailed and authoritative study of R&D costs in order to show how high estimates have been constructed by industry-supported economists, and to show how much lower actual costs may be. Besides serving as an object lesson in the construction of ‘facts’, this analysis provides reason to believe that R&D costs need not be such an insuperable obstacle to the development of better medicines. The deeper problem is that current incentives reward companies to develop mainly new medicines of little advantage and compete for market share at high prices, rather than to develop clinically superior medicines with public funding so that prices could be much lower and risks to companies lower as well.

Link: https://doi.org/10.1057/biosoc.2010.40.

Mestre-Ferrandiz, Jorge, Jon Sussex, A Towse. “The R&D Cost of a New Medicine”. Office of Health Economics, London. 2012. https://www.ohe.org/publications/rd-cost-new-medicine.

Summary: The cost of R&D for a successful new medicine has been an important policy issue at least since the 1960s. Cost estimates matter not just because of intellectual curiosity or for industry understanding of its performance, but because they are a key aspect of the international debate about the reasonableness of pharmaceutical prices and the magnitude of the long-term investments involved. This publication reviews research published over the last three decades, which shows an increase in costs from £125 million ($199 million) per new medicine in the 1970s to £1.2 billion ($1.9 billion) in the 2000s (both in 2011 prices). An OHE costs analysis based on new data for 1998-2002 agrees with comparable analyses for the same time period. The study explores four major factors that are producing higher R&D costs: out-of-pocket expenses, success/failure rates, R&D times and the cost of capital. It also discusses measures companies are taking now to improve efficiency and offers a glimpse into the promise and challenges presented by the new, gene-based sciences.

Link: https://www.ohe.org/publications/rd-cost-new-medicine.

Morgan, Steve, Paul Grootendorst, Joel Lexchin, Colleen Cunningham, and Devon Greyson. 2011. “The Cost of Drug Development: A Systematic Review.” Health Policy 100 (1): 4–17. https://doi.org/10.1016/j.healthpol.2010.12.002.

Abstract: OBJECTIVES: We aimed to systematically review and assess published estimates of the cost of developing new drugs.

METHODS: We sought English language research articles containing original estimates of the cost of drug development that were published from 1980 to 2009, inclusive. We searched seven databases and used citation tracing and expert referral to identify studies. We abstracted qualifying studies for information about methods, data sources, study samples, and key results.

RESULTS: Thirteen articles were found to meet our inclusion criteria. Estimates of the cost of drug development ranged more than 9-fold, from USD$92 million cash (USD$161 million capitalized) to USD$883.6 million cash (USD$1.8 billion capitalized). Differences in methods, data sources, and time periods explain some of the variation in estimates. Lack of transparency limits many studies. Confidential information provided by unnamed companies about unspecified products forms all or part of the data underlying 10 of the 13 studies. CONCLUSIONS: Despite three decades of research in this area, no published estimate of the cost of developing a drug can be considered a gold standard. Studies on this topic should be subjected to reasonable audit and disclosure of - at the very least - the drugs which authors purport to provide development cost estimates for.

Link: https://doi.org/10.1016/j.healthpol.2010.12.002.

Odevall, Lina, Deborah Hong, Laura Digilio, Sushant Sahastrabuddhe, Vittal Mogasale, Yeongok Baik, Seukkeun Choi, Jerome H. Kim, and Julia Lynch. 2018. “The Euvichol Story – Development and Licensure of a Safe, Effective and Affordable Oral Cholera Vaccine through Global Public Private Partnerships.” Vaccine 36 (45): 6606–14. https://doi.org/10.1016/j.vaccine.2018.09.026.

Abstract: Cholera, a diarrheal disease primarily affecting vulnerable populations in developing countries, is estimated to cause disease in more than 2.5 million people and kill almost 100,000 annually. An oral cholera vaccine (OCV) has been available globally since 2001; the demand for this vaccine from affected countries has however been very low, due to various factors including vaccine price and mode of administration. The low demand for the vaccine and limited commercial incentives to invest in research and development of vaccines for developing country markets has kept the global supply of OCVs down. Since 1999, the International Vaccine Institute has been committed to make safe, effective and affordable OCVs accessible. Through a variety of partnerships with collaborators in Sweden, Vietnam, India and South Korea, and with public and private funding, IVI facilitated development and production of two affordable and WHO-prequalified OCVs and together with other stakeholders accelerated the introduction of these vaccines for the global public-sector market.

Link: https://doi.org/10.1016/j.vaccine.2018.09.026.

Paul, Steven M., Daniel S. Mytelka, Christopher T. Dunwiddie, Charles C. Persinger, Bernard H. Munos, Stacy R. Lindborg, and Aaron L. Schacht. 2010. “How to Improve R&D Productivity: The Pharmaceutical Industry’s Grand Challenge.” Nature Reviews Drug Discovery 9 (3): 203–14. https://doi.org/10.1038/nrd3078.

Abstract: The pharmaceutical industry is under growing pressure from a range of environmental issues, including major losses of revenue owing to patent expirations, increasingly cost-constrained healthcare systems and more demanding regulatory requirements. In our view, the key to tackling the challenges such issues pose to both the future viability of the pharmaceutical industry and advances in healthcare is to substantially increase the number and quality of innovative, cost-effective new medicines, without incurring unsustainable R&D costs. However, it is widely acknowledged that trends in industry R&D productivity have been moving in the opposite direction for a number of years. Here, we present a detailed analysis based on comprehensive, recent, industry-wide data to identify the relative contributions of each of the steps in the drug discovery and development process to overall R&D productivity. We then propose specific strategies that could have the most substantial impact in improving R&D productivity.

Link: https://doi.org/10.1038/nrd3078.

Prasad, Vinay, and Sham Mailankody. 2017. “Research and Development Spending to Bring a Single Cancer Drug to Market and Revenues After Approval.” JAMA Internal Medicine 177 (11): 1569. https://doi.org/10.1001/jamainternmed.2017.3601.

Abstract: Importance: A common justification for high cancer drug prices is the sizable research and development (R&D) outlay necessary to bring a drug to the US market A recent estimate of R&D spending is $2.7 billion (2017 US dollars). However, this analysis lacks transparency and independent replication. Objective: To provide a contemporary estimate of R&D spending to develop cancer drugs. Design, Setting, and Participants: Analysis of US Securities and Exchange Commission filings for drug companies with no drugs on the US market that received approval by the US Food and Drug Administration for a cancer drug from January 1, 2006, through December 31, 2015. Cumulative R&D spending was estimated from initiation of drug development activity to date of approval. Earnings were also identified from the time of approval to the present. The study was conducted from December 10, 2016, to March 2, 2017. Main Outcomes and Measures: Median R&D spending on cancer drug development. Results: Ten companies and drugs were included in this analysis. The 10 companies had a median time to develop a drug of 7.3 years (range, 5.8-15.2 years). Five drugs (50%) received accelerated approval from the US Food and Drug Administration, and 5 (50%) received regular approval. The median cost of drug development was $648.0 million (range, $157.3 million to $1950.8 million). The median cost was $757.4 million (range, $203.6 million to $2601.7 million) for a 7% per annum cost of capital (or opportunity costs) and $793.6 million (range, $219.1 million to $2827.1 million) for a 9% opportunity costs. With a median of 4.0 years (range, 0.8-8.8 years) since approval, the total revenue from sales of these 10 drugs since approval was $67.0 billion compared with total R&D spending of $7.2 billion ($9.1 billion, including 7% opportunity costs). Conclusions and Relevance: The cost to develop a cancer drug is $648.0 million, a figure significantly lower than prior estimates. The revenue since approval is substantial (median, $1658.4 million; range, $204.1 million to $22 275.0 million). This analysis provides a transparent estimate of R&D spending on cancer drugs and has implications for the current debate on drug pricing. Link: https://doi.org/10.1001/jamainternmed.2017.3601.

Public Citizen. 2001. “Rx R&D Myths: The Case Against the Drug Industry’s R&D ‘Scare Card.’” Washington, DC, Public Citizen’s Congress Watch. https://www.citizen.org/wp-content/uploads/rdmyths.pdf.

Executive summary: This new Public Citizen report reveals how major U.S. drug companies and their Washington, D.C. lobby group, the Pharmaceutical Research and Manufacturers of America (PhRMA), have carried out a misleading campaign to scare policy makers and the public. PhRMA’s central claim is that the industry needs extraordinary profits to fund expensive, risky and innovative research and development (R&D) for new drugs. If anything is done to moderate prices or profits, R&D will suffer, and, as PhRMA’s president recently claimed, “it’s going to harm millions of Americans who have life-threatening conditions.” But this R&D scare card – or canard – is built on myths, falsehoods and misunderstandings, all of which are made possible by the drug industry’s staunch refusal to open its R&D records to congressional investigators or other independent auditors. Using government studies, company filings with the U.S. Securities and Exchange Commission and documents obtained via the Freedom of Information Act, Public Citizen’s report exposes the industry’s R&D claims.

Link: https://www.citizen.org/wp-content/uploads/rdmyths.pdf.

PwC. 2012. “From Vision to Decision - Pharma 2020.” PricewaterhouseCoopers. https://www.pwc.com/gx/en/pharma-life-sciences/pharma2020/assets/pwc-pharma-success-strategies.pdf.

Abstract: Not available.

Link: https://www.pwc.com/gx/en/pharma-life-sciences/pharma2020/assets/pwc-pharma-success-strategies.pdf.

Sertkaya, A., A. Birkenbach, A. Berlind, and J. Eyraud. 2014. “Examination of Clinical Trial Costs and Barriers for Drug Development.” https://aspe.hhs.gov/report/examination-clinical-trial-costs-and-barriers-drug-development.

Abstract: Pharmaceutical companies conduct clinical trials for many reasons. The most obvious goal of clinical trials is to demonstrate safety and efficacy to gain Food and Drug Administration (FDA) approval. FDA provides guidance to developers about what constitutes acceptable clinical trials and appropriate outcomes. Improving the drug development process, especially by conducting better (meaning providing more information on safety or efficacy) and faster clinical trials, can foster innovation in medical product development. The primary purposes of this study: 1) to better understand sponsors' strategies in the design and execution of clinical trials, 2) to identify factors that may delay, hinder, or lead to unsuccessfully completed trials, and 3) to develop an operational model of clinical trial decision-making to enable examination of what-if scenarios by end-users. This study models the decision-making process for a drug sponsor as a stylized decision tree that looks at the process for formulating a clinical trial from the point of view of an expected-revenue-maximizing sponsor in the face of uncertainty (or risk). The simplified clinical decision-making model incorporates the following considerations: Therapeutic area; Potential market size/revenues for the drug; Clinical stage; Success probabilities by clinical stage. In addition to identifying the costs of the clinical trials, the following barrier mitigation strategies were analyzed: Use of electronic health records (EHR); Looser trial enrollment restrictions; Simplified clinical trial protocols and reduced amendments; Reduced source data verification (SDV); Wider use of mobile technologies, including electronic data capture (EDC); Use of lower-cost facilities or at-home testing; Priority Review/Priority Review vouchers; Improvements in FDA review process efficiency and more frequent and timely interactions with FDA. Overall, the therapeutic area with the highest clinical research burden across all phases is respiratory system ($115.3 million) followed by pain and anesthesia ($105.4 million) and oncology ($78.6 million) trials. Use of lower-cost facilities/in-home testing and wider use of mobile technologies appear to be most effective in reducing costs across therapeutic areas and trial phases. Use of lower-cost facilities and/or in-home testing can reduce per-trial costs by up to $0.8 million (16 percent) in Phase I, $4.3 million (22 percent) in Phase II, and $9.1 million (17 percent) in Phase III, depending on therapeutic area. Link: https://aspe.hhs.gov/report/examination-clinical-trial-costs-and-barriers-drug-development.

Speich, Benjamin, Belinda von Niederhäusern, Nadine Schur, Lars G. Hemkens, Thomas Fürst, Neera Bhatnagar, Reem Alturki, et al. 2018a. “Systematic Review on Costs and Resource Use of Randomized Clinical Trials Shows a Lack of Transparent and Comprehensive Data.” Journal of Clinical Epidemiology 96 (April): 1–11. https://doi.org/10.1016/j.jclinepi.2017.12.018.

Abstract: Objectives: Randomized clinical trials (RCTs) are costly. We aimed to provide a systematic overview of the available evidence on resource use and costs for RCTs to support budget planning. Study Design and Setting: We systematically searched MEDLINE, EMBASE, and HealthSTAR from inception until November 30, 2016 without language restrictions. We included any publication reporting empirical data on resource use and costs of RCTs and categorized them depending on whether they reported (i) resource and costs of all aspects at all study stages of an RCT (including conception, planning, preparation, conduct, and all tasks after the last patient has completed the RCT); (ii) on several aspects, (iii) on a single aspect (e.g., recruitment); or (iv) on overall costs for RCTs. Median costs of different recruitment strategies were calculated. Other results (e.g., overall costs) were listed descriptively. All cost data were converted into USD 2017. Results: A total of 56 articles that reported on cost or resource use of RCTs were included. None of the articles provided empirical resource use and cost data for all aspects of an entire RCT. Eight articles presented resource use and cost data on several aspects (e.g., aggregated cost data of different drug development phases, site-specific costs, selected cost components). Thirty-five articles assessed costs of one specific aspect of an RCT (i.e., 30 on recruitment; five others). The median costs per recruited patient were USD 409 (range: USD 41–6,990). Overall costs of an RCT, as provided in 16 articles, ranged from USD 43–103,254 per patient, and USD 0.2–611.5 Mio per RCT but the methodology of gathering these overall estimates remained unclear in 12 out of 16 articles (75%). Conclusion: The usefulness of the available empirical evidence on resource use and costs of RCTs is limited. Transparent and comprehensive resource use and cost data are urgently needed to support budget planning for RCTs and help improve sustainability. Link: https://doi.org/10.1016/j.jclinepi.2017.12.018.

Light, Donald W., Jon Kim Andrus, and Rebecca N. Warburton. 2009. “Estimated Research and Development Costs of Rotavirus Vaccines.” Vaccine 27 (47): 6627–33. https://doi.org/10.1016/j.vaccine.2009.07.077.

Abstract: Diseases like rotavirus afflict both upper- and lower-income countries, but most serious illnesses and deaths occur among the latter. It is a vital public health issue that vaccines for these types of global diseases can recover research and development (R&D) costs from high-priced markets quickly so that manufacturers can offer affordable prices to lower-income nations. Cost recovery depends on how high R&D costs are, and this study attempts to replace high, unverified estimates with lower, more verifiable estimates for two new vaccines, RotaTeq (Merck) and Rotarix (GlaxoSmithKline or GSK), based on detailed searches of public information and follow-up interviews with senior informants. We also offer a new perspective on “cost of capital” as a claim for recovery from public bodies. Our estimates suggest that companies can recover all fixed costs quickly from affluent markets and thus can offer these vaccines to lower-income countries at prices they can afford. Better vaccines are a shared project between companies and public health agencies; greater transparency and consistency in reporting of R&D costs is needed so that fair prices can be established.

Link: https://doi.org/10.1016/j.vaccine.2009.07.077.

Speich, Benjamin, Belinda von Niederhäusern, Claudine Angela Blum, Jennifer Keiser, Nadine Schur, Thomas Fürst, Benjamin Kasenda, et al. 2018b. “Retrospective Assessment of Resource Use and Costs in Two Investigator-Initiated Randomized Trials Exemplified a Comprehensive Cost Item List.” Journal of Clinical Epidemiology 96 (April): 73–83. https://doi.org/10.1016/j.jclinepi.2017.12.022.

Abstract: Objectives: Randomized clinical trials (RCTs) are costly and published information on resource requirements for their conduct is limited. To identify key factors for making RCTs more sustainable, empirical data on resource use and associated costs are needed. We aimed to retrospectively assess resource use and detailed costs of two academic, investigator-initiated RCTs using a comprehensive list of cost items. Study Design and Setting: The resource use of two investigator-initiated RCTs (Prednisone-Trial [NCT00973154] and Oxantel-Trial [ISRCTN54577342]) was empirically assessed in a standardized manner through semistructured interviews and a systematically developed cost item list. Using information about yearly salaries, resource use was translated into costs. In addition, we collected all “other costs” including fixed priced items. Overall costs as well as cost of different study phases were calculated. Results: The personnel time used in the Prednisone-Trial trial was approximately 2,897 working days and the overall costs were calculated to be USD 2.3 million, which was USD 700,000 more than planned. In the Oxantel-Trial 798 working days were spent and the overall costs were as originally planned USD 100,000. Cost drivers were similar between the two RCTs with recruitment delays explaining the additional costs in the Prednisone-Trial. Conclusion: This case study provides an example of how to transparently assess resources and costs of RCTs and presents detailed empirical data on type and magnitude of expenses. In the future, this model approach may serve others to plan, assess, or monitor resource use and costs of RCTs. Link: https://doi.org/10.1016/j.jclinepi.2017.12.022.

Tay-Teo, Kiu, André Ilbawi, and Suzanne R. Hill. 2019. “Comparison of Sales Income and Research and Development Costs for FDA-Approved Cancer Drugs Sold by Originator Drug Companies.” JAMA Network Open 2 (1): e186875. https://doi.org/10.1001/jamanetworkopen.2018.6875.

Abstract: Importance: High costs and risks of research and development (R&D) have been used to justify the high prices of cancer drugs. However, what the return on R&D investment is, and by extension what a justifiable price might be, is unclear.

Objective: To compare incomes from the sales of cancer drugs with the estimated R&D costs.

Design, Setting, and Participants: This observational study used global pharmaceutical industry sales data to quantify the cumulative incomes generated from the sales of cancer drugs for companies that have held patents or marketing rights (originator companies). All cancer drugs approved by the US Food and Drug Administration from 1989 to 2017 were identified from the United States Food and Drug Administration’s website and literature. Itemized product sales data were extracted from the originator companies’ consolidated financial reports. For drugs with data missing in specific years, additional data was sought from other public sources, or where necessary, estimated values from known reported values. Drugs were excluded if there were missing data for half or more of the years since approval. Data analysis was conducted from May 2018 to October 2018.

Main Outcomes and Measures: Sales data were expressed in 2017 US dollars with adjustments for inflation. Cumulative incomes from the sales of these drugs were compared against the R&D costs estimated in the literature, which had been adjusted for the costs of capital and trial failure (risk adjusted). Results: Of the 156 US Food and Drug Administration–approved cancer drugs identified, 99 drugs (63.5%) had data for more than half of the years since approval and were included in the analysis. There was a median of 10 years (range, 1-28 years) of sales data with 1040 data points, 79 (7.6%) of which were estimated. Compared with the total risk-adjusted R&D cost of $794 million (range, $2827-$219 million) per medicine estimated in the literature, by the end of 2017, the median cumulative sales income was $14.50 (range, $3.30-$55.10) per dollar invested for R&D. Median time to fully recover the maximum possible risk-adjusted cost of R&D ($2827 million) was 5 years (range, 2-10 years; n = 56). Cancer drugs continued to generate billion-dollar returns for the originator companies after the end-of-market exclusivity, particularly for biologics. Conclusions and Relevance: Cancer drugs, through high prices, have generated returns for the originator companies far in excess of possible R&D costs. Lowering prices of cancer drugs and facilitating greater competition are essential for improving patient access, health system’s financial sustainability, and future innovation.

Link: https://doi.org/10.1001/jamanetworkopen.2018.6875.

Terry, Robert F, Gavin Yamey, Ryoko Miyazaki-Krause, Alexander Gunn, and John C. Reeder. 2018. “Funding Global Health Product R&D: The Portfolio-To-Impact Model (P2I), a New Tool for Modelling the Impact of Different Research Portfolios.” Gates Open Research 2 (July): 24. https://doi.org/10.12688/gatesopenres.12816.2.

Abstract: Background: The Portfolio-To-Impact (P2I) Model is a novel tool, developed to estimate minimum funding needs to accelerate health product development from late stage preclinical study to phase III clinical trials, and to visualize potential product launches over time.

Methods: A mixed methods approach was used. Assumptions on development costs at each phase were based on clinical trial costs from Parexel’s R&D cost sourcebook. These were further refined and validated by interviews, with a wide variety of stakeholders from Product Development Partnerships, biopharmaceutical and diagnostic companies, and major funders of global health R&D.

Results: the tool was used to create scenarios describing the impact, in terms of products developed, of different product portfolios with funding ranging from $1 million per annum through to $500 million per annum. These scenarios for a new global financing mechanism have been previously presented in a report setting out the potential for a new fund for research and development which would assist in accelerating product development for the diseases of poverty.

Conclusion: The P2I tool does enable a user to model different scenarios in terms of cost and number of health products launched when applied to a portfolio of health products. The model is published as open access accompanied with a user guide. The design allows it to be adapted and used for other health R&D portfolio analysis as described in an accompanying publication focussing on the pipeline for neglected diseases in 2017. We aim to continually refine and improve the model and we ask users to provide us with their own inputs that can help us update key parameters and assumptions. We hope to catalyse users to adapt the model in ways that can increase its value, accuracy, and applications.

Link: https://doi.org/10.12688/gatesopenres.12816.2.

United States Congress, Office of Technology Assessment. 1993. “Pharmaceutical R&D: Costs, Risks, and Rewards”. Washington, D.C: Office of Technology Assessment, Congress of the U.S. https://ota.fas.org/reports/9336.pdf.

Summary (extracts): In this assessment, the Office of Technology Assessment examined the costs of pharmaceutical research and development (R&D), the economic rewards from that investment, and the impact of public policies on both costs and returns. Below is a brief synopsis of the study’s major conclusions: SUMMARY OF FINDINGS: Pharmaceutical R&D is a costly and risky business, but in recent years the financial rewards from R&D have more than offset its costs and risks. The average aftertax R&D cash outlay for each new drug that reached the market in the 1980s was about $65 million (in 1990 dollars). The R&D process took 12 years on average. The full aftertax cost of these outlays, compounded to their value on the day of market approval, was roughly $194 million (1990 dollars). Each new drug introduced to the U.S. market between 1981 and 1983 returned, net of taxes, at least $36 million more to its investors than was needed to pay off the R&D investment. This surplus return amounts to about 4.3 percent of the price of each drug over its product life. Over a longer span of time, economic returns to the pharmaceutical industry as whole exceeded returns to corporations in other industries by about 2 to 3 percentage points per year from 1976 to 1987, after adjusting for differences in risk among industries. A risk-adjusted difference of this magnitude is sufficient to induce substantial new investment in the pharmaceutical industry. The National Institutes of Health (NIH) and other Public Health Service laboratories have no mechanism to protect the public’s investment in drug discovery, development and evaluation. These agencies lack the expertise and sufficient legal authority to negotiate limits on prices to be charged for drugs discovered or developed with Federal funds. Link: https://ota.fas.org/reports/9336.pdf.

Young, Ruth, Tewodros Bekele, Alexander Gunn, Nick Chapman, Vipul Chowdhary, Kelsey Corrigan, Lindsay Dahora, et al. 2018. “Developing New Health Technologies for Neglected Diseases: A Pipeline Portfolio Review and Cost Model.” Gates Open Research 2 (August): 23. https://doi.org/10.12688/gatesopenres.12817.2.

Abstract: Background: Funding for neglected disease product development fell from 2009-2015, other than a brief injection of Ebola funding. One impediment to mobilizing resources is a lack of information on product candidates, the estimated costs to move them through the pipeline, and the likelihood of specific launches. This study aimed to help fill these information gaps. Methods: We conducted a pipeline portfolio review to identify current candidates for 35 neglected diseases. Using an adapted version of the Portfolio to Impact financial modelling tool, we estimated the costs to move these candidates through the pipeline over the next decade and the likely launches. Since the current pipeline is unlikely to yield several critical products, we estimated the costs to develop a set of priority “missing” products. Results: We found 685 neglected disease product candidates as of August 31, 2017; 538 candidates met inclusion criteria for input into the model. It would cost about $16.3 billion (range $13.4-19.8B) to move these candidates through the pipeline, with three-quarters of the costs incurred in the first 5 years, resulting in about 128 (89-160) expected product launches. Based on the current pipeline, there would be few launches of complex new chemical entities; launches of highly efficacious HIV, tuberculosis, or malaria vaccines would be unlikely. Estimated additional costs to launch one of each of 18 key missing products are $13.6B assuming lowest product complexity or $21.8B assuming highest complexity ($8.1B-36.6B). Over the next 5 years, total estimated costs to move current candidates through the pipeline and develop these 18 missing products would be around $4.5B (low complexity missing products) or $5.8B/year (high complexity missing products). Conclusions: Since current annual global spending on product development is about $3B, this study suggests the annual funding gap over the next 5 years is at least $1.5-2.8B. Link: https://doi.org/10.12688/gatesopenres.12817.2.