`
`See
`ELSEVIER
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`Available online at www.sciencedirect.com
`SCIENCE
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`pirnecT®@
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`JOURNAL OF
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`ALTH
`ECONOMICS
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`Journal of Health Economics 22 (2003) 151-185
`
`www.cisevier.com/locate/econbase
`
`The price of innovation: new estimates
`of drug development costs
`
`Joseph A. DiMasi**, Ronald W. Hansen>, Henry G. Grabowski°®
`* Tufis Centerfor the Study ofDrug Development, Tufts University, 192 South Street,
`Suite 550, Boston, MA 02111, USA
`» William E. Simon Graduate School ofBusiness Administration, lJniversity ofRochester, Rochester,NY, USA
`° Department ofEconomics, Duke University, Durham, NC, USA
`
`Received 17 January 2002; received in revised form 24 May2002; accepted 28 October 2002
`
`Abstract
`
`The research and developmentcosts of68 randomlyselected newdrugs were obtained from a sur-
`vey of 10 pharmaceutical finns. These data were used to estimate the average pre-tax cost ofnewdrug
`development. The costs of compounds abandoned during testing were linked to the costs of com-
`poundsthat obtained marketing approval. ‘The estimated average out-of-pocket cost per newdrugis
`US$ 403 million (2000 dollars). Capitalizing out-of-pocketcosts to the point of marketing approval
`at areal discountrate of 11% yieldsa total pre-approvalcost estimate ofUS$ 802 million (2000 dol-
`lars). When compared to the results ofan earlier studywith a similar methodology,total capitalized
`costs were shown to have increased at an annual rate of 7.4% above general price inflation.
`©2003 Elsevier Science B.V. All rights reserved.
`
`JEL classification: L65, O31
`
`Keywords: Innovation: R&D cost; Pharmaceutical industry: Discountrate: Technical success rates
`
`
`1. Introduction
`
`Innovations in the health sciences have resulted in dramatic changes in the ability to treat
`disease and improve the quality of life. Expenditures on pharmaceuticals have grownfaster
`than other major components of the health care system since the late 1990s. Consequently,
`the debates on rising health care costs and the development of new medical technologies
`have focused increasingly on the pharmaceutical industry, which is botha majorparticipant
`in the health care industry and a major source of advancesin health care technologies.
`
`* Corresponding author. ‘lel.: +1-617-636-2116.
`E-mail address: joseph.dimasi@tufls.edu (J.-A. DiMasi).
`
`0167-6296/03/S—see front matter © 2003 Elsevier Science B.V. All rights reserved.
`doi: 10.1016'S0167-6296(02)00 126-1
`
`1
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`Exhibit 2067
`Slayback v. Sumitomo
`IPR2020-01053
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`152
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`JA. DiMasiet ai./Journal ofHealth Economics 22 (2003) 151-185
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`Oneof the key components of the discussionis the role of private sector pharmaceutical
`industry investments in R&D and an understanding of the factors that affect this process.
`Althoughthe industry engages in many forms of innovation, in general the most significant
`is the discovery and development of new chemical and biopharmaceutical entities that
`become newtherapies. Our prior research (DiMasiet al., 1991) found that the discovery
`and development of newdrugsis a very lengthy and costly process. In the research-based
`drug industry, R&D decisions have very long-term ramifications, and the impact of market
`or public policy changes maynot be fully realized for many years. From both a policy
`perspective, as well as an industrial perspective, it is therefore important to continue to
`analyze the components of and trends in the costs of pharmaccutical innovation.
`In this paper we will build on research conducted bythe current authors (DiMasi etal.,
`1991) and others on the economics of pharmaceutical R&D. As we described in our prior
`study, “Empirical analyses of the cost to discover and develop NCEsare interesting on
`several counts. First, knowledge of R&D costs is important for analyzing issues such as
`the returns on R&D investment. Second, the cost of a new drug has direct bearing on
`the organizational structure of innovation in pharmaceuticals. In this regard, higher real
`R&D costs have been cited as one of the main factors underlying the recent trend toward
`more mergers and industry consolidation. Third, R&D costs also influence the pattern
`of international resource allocation. Finally, the cost of R&D has become an important
`issue in its own right in the recent policy deliberations involving regulatory requirements
`and the economic performance of the pharmaceutical industry”. In the decade that has
`followed the publication of our earlier study, these issues remain paramount. In addition,
`the congressional debates on Medicare prescription drug coverage and various newstate
`initiatives to fill gaps in coverage for the elderly and the uninsured have intensified the
`interest in the performance of the pharmaceutical industry.
`In the current study we are not attempting to directly answer the policy debates men-
`tioned above. Rather, our focus is on providing newestimates of economic parameters
`associated with the drug development process. In particular, we concentrate on estimates
`of the costs of pharmaceutical innovation. Ourprior estimates have been used by the Office
`of Technology assessment (OTA), the Congressional Budget Office (CBO), and various
`researchers to analyze policy questions such as the effects on R&D activities of health care
`financing reform or changesin intellectual property legislation related to the pharmaceutical
`industry.
`The approach used in this paper follows our previous study (DiMasiet al., 1991) and
`the earlier work by Hansen (1979). Given the similarity in methodologies, we are able
`to compare our results in the current study with the estimates in the earlier studies to
`illustrate trends in development costs. All three studies used micro-level data on the cost
`and timing of development obtained through confidential surveys of pharmaceutical firms
`fora random sample of newdrugsfirst investigated in humansbythese firms. In the current
`study, the newdrugs were first tested in humans anywherein the world between 1983 and
`1994. The reported development costs ran through 2000.Ultimately, we are interested in
`the expected cost of developmentper approved newdrug. The uncertainties in the research
`and development processresult in expenditures on many developmentprojects that are not
`successful in producing a marketed product. However, to produce an estimate of expected
`cost for a marketed product, we mustallocate the costs of the unsuccessful projects to those
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`153
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`that result ina marketed newproduct. The R&D processis lengthy, and as such it is important
`to knowat what stage of development expenses occur. Viewed as an invesimentproject,it
`is necessary to knowboth the amount of expenditures and the timing of these expenditures,
`since funds committed to R&D in advance of any returns from sales have both a direct
`and an opportunity cost. We used a unique database to estimate various cost parameters
`in the developmentprocess. Of particular concern is the estimation of the average pre-tax
`cost of new drug development. since we are interested in the resource costs of new drug
`development and howthey have changed overtime.
`
`1.1. Previous studies ofthe cost ofpharmaceutical innovation
`
`A summary ofearlystudies of the cost of drug developmentcan be foundin the authors’
`previous study (DiMasi et al., 1991) and in OTA (1993). In brief, the carly studies were
`either based ona case study of a specific drug (usually ignoring the cost of failed projects)
`or relied on aggregate data. Since the R&D process often extends for a decade or more
`and the new drug development process often changes,it is difficult to estimate the cost
`of development from aggregated annual data. In contrast, the study by Hansen (1979)
`and the current authors’ previous study (DiMasi et al., 1991) estimated development cost
`based on data supplied by firms for a representative sample of drug development
`efforts.
`DiMasiet al. (1991) used data on self-originated newdrugs to estimate the average cost
`of developing a new drug. Theyobtained data from 12 pharmaceuticalfirms on the research
`and development costs of 93 randomlyselected new drugs that entered clinical trials be-
`tween 1970 and 1982. From these data they estimated the average pre-tax out-of-pocket
`cost per approved drug to be US$ 114 million (1987 dollars). Since these expenditures
`were spread out over nearly a dozen years, they capitalized these expenditures to the date
`of marketing approval using a 9% discount rate. This yielded an estimate of US$ 231
`million (1987 dollars). Measured in constant dollars, this value is more than double that
`obtained by Hansenfor an earlier sample. DiMasi et al. (1991) also found that the average
`cost of the first two phases of clinical trials doubled betweenthe first and second half of
`their sample. This led to the expectation that development costs would be higherin future
`samples.
`Based on an analysis by Myers and Shyam-Sunder performed for the OTA, the OTA
`(1993) report noted that the cost-of-capital for the industry was roughly 10% in the early
`1980s. This is moderately higher than the 9% used by DiMasiet al. (1991). The OTAalso
`recalculated the DiMasi et al. (1991) numbers using an interest rate that varied overthelife
`of the R&D cycle therebyraising the cost estimate by US$ 100 million in 1990 dollars.!
`The OTApresented both pre- and post-tax cost estimates.
`
`' The OTA applied a range of discountrates that varied with the time to marketing approval. Theychose 14%
`for the earliest stage R&D and 10%for developmentjust prior to approval, with rates in between that declined
`linearly with time in development. This approach was meant to capture the essence ofthe risk-return staircase
`perspective expressed by Myers and others, and discussed below. The methodology described in Myers and Howe
`(1997) is actually quite different, but the OTA technique yielded results that would not be muchdifferent(for the
`same distribution of costs) than what one would have obtained with the correct methodology (Myers and Howe,
`1997, p. 33).
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`NCEs
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`JA. DiMasi et ai./ Journal ofHealth Economics 22 (2003) 151-185
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`28
`
`24
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`12($000249SuOIiIG)APY
`
`20
`
`16
`
`1963 1967 1971 1975 1979 1983 1987 1991 1995 1999
`
`- NCEs + Real R&D (2000$) —-NCE Trend
`
`Fig. 1. Inflation-adjusted industry R&D expenditures (2000 dollars) and US newchemicalentity (NCE) approvals
`from 1963 to 2000. Source ofdata: PhRMA(2001) and Tufts CSDD Approved NCE Database.
`
`1.2. Aggregate data analyses
`
`There have been no recent comprehensive studies of the cost of developing newpharma-
`ceuticals from synthesis to marketing approval based onactual project-level data. However,
`aggregate data and data on parameters of the drug development process suggest that R&D
`costs have increased substantially since our earlier study. For example, the Pharmaceutical
`Research and Manufacturers of America (PhRMA,2000) publishes an annualreport on the
`R&D expenditures of its memberfirms that shows a continuous increase in outlays well in
`excessof inflation. Reports on specific components of the R&D process, such as the number
`of subjects in clinical trials (OTA, 1993; The Boston Consulting Group [BCG], 1993), also
`suggest an increase in the real cost of pharmaccutical innovation.
`|
`Published aggregate industry data suggest that R&D costs have been increasing. Fig.
`showsreported aggregate annual domestic prescription drug R&D expenditures for mem-
`bers of the US pharmaccutical industry since 1963. The chart also shows the number of
`US newdrug approvals by year. Given the muchfaster rate of growth of R&D expendi-
`tures, data suchas these suggest that R&D costs have increased over time. However, they
`cannot be conclusive or precise. For one matter, the drug development process is known
`to be very lengthy. Thus, new drug approvals today are associated with R&D expenditures
`that were incurred manyyears prior. Ignoring the inherent lag structure underlying these
`data and simplydividing current R&D expenditures by the number of newdrug approvals
`will in general yield inaccurate estimates.* Given a substantial increasing trend in R&D
`
`2 The estimates would also vary widelyfrom year-to-year. For example, if we divided each year’s real R&D
`expenditures bythat year’s number of NCE approvals, we would obtain US$ | billion for 2000, US$ 743 million
`for 1999, US$ 839 million for 1998, USS 568 million for 1997, US$ 400 million for 1996, US$ 635 million for
`1995. and US$ 878 million for 1994. While there is a general upward trend in such calculations, the year-to-year
`variability is not credible.
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`155
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`expenditures. such calculations will result in greatly exaggerated estimates of out-of-pocket
`cost per approval.
`Secondly, even properly lagged time series would tend to be imprecise if aggregate in-
`dustry data were used as reported. The industrydata include expenditures on improvements
`to existing products. Thus, they would overestimate pre-approval development costs. On
`the other hand, they also do not incorporate all of the R&D on licensed-in drugs since
`firms or other organizations that are not members of the UStrade association would have
`conducted some of the work. Onthat account the data would tend to underestimate costs.
`Therefore, R&D cost estimates based on project-level data are needed to assure a reasonable
`level of confidence in the accuracyof the results. We present results based on suchdata in
`this study.
`The remainder of this paper is organized as follows. Section 2 describes the standard
`drug development paradigm, whichserves as the structure through which the results are
`reported. Section 3 contains a description ofthe survey sample data and the population from
`which it was drawn. Section 4 describes the methodology used to derive R&D costesti-
`mates. We present our base case pre-marketing approval R&D cost estimatesin Section5,
`as well as a comparison of ourresults with those ofearlier studies to examine R&D cost
`trends. Section 6 provides sensitivity analyses for key parameters. Section 7 focuses on
`some extensions of the base case analyses: estimates of clinical development costs for ap-
`proved drugs bytherapeutic significance, estimates of post-approval R&Dcosts, and a tax
`analysis. Section 8 contains data and analysesthat corroborate ourresults. Finally, we offer
`some conclusions in Section 9,
`
`2. The new drug development process
`
`Newdmg development can proceed along varied pathwaysfor different compounds, but
`a development paradigm has beenarticulated that has long served well as a general model.
`The paradigmis explained in some detail elsewhere (DiMasi etal., 1991; US Food and Drug
`Administration [FDA], 1999). In outline form, the paradigm portrays newdrug discovery
`and development as proceeding ina sequence of (possibly overlapping) phases. Discovery
`programs result in the synthesis ofcompoundsthat are tested in assays and animal models.
`It was not possible to disaggregate our data into discovery and preclinical development
`testing costs.> so for the purposesofthis study discoveryand preclinical developmentcosts
`are grouped and referred to as preclinical costs.
`Clinical (human)testing typically proceeds through three successive phases. In phase I,
`a small numberof usually healthy volunteers* are tested to establish safe dosages and to
`gather information on the absorption, distribution, metabolic effects, excretion, and toxicity
`of the compound. To conductclinical testing in the United States, a manufacturer mustfirst
`
`> The reported basic research expenditures byfirm were highlyvariable, and suggest that different firms may
`categorize their pre-humantesting expenditures somewhatdifferently. Thus, we report pre-humantesting costs in
`onefigure.
`4 In sometherapeutic areas, testing is initially done on patients who have the disease or condition for whichthe
`compoundis intended to be a treatment. This is ordinarilytrue in the cancer and AIDS areas.
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`file an investigational new drug application (IND) with the FDA. However,initiation of
`human testing can, and often does, occurfirst outside the United States.
`Phase II trials are conducted with subjects who have the targeted disease or condition
`and are designed to obtain evidence on safety and preliminarydata onefficacy. The number
`of subjects tested in this phase is larger than in phase I and may numberin the hundreds.
`The final pre-approval clinical testing phase, phaseIII, typically consists of a number of
`large-scale (often multi-center) trials that are designed to firmlyestablishefficacy and to
`uncoverside-effects that occur infrequently. The numberof subjects in phase III trials for
`a compoundcan total in the thousands.
`Once drug developers believe that they have enough evidence of safety and efficacy,
`they will compile the results of their testing in an application to regulatory authorities
`for marketing approval. In the United States, manufacturers submit a new drug appli-
`cation (NDA)or a biological
`license application (BLA) to the FDA for review and
`approval.
`
`3. Data
`
`Ten multinational pharmaceutical firms, including both foreign and US-owned firms,
`provided data through a confidential survey of their new drug R&D costs.’ Data were
`collected on clinical phase costs for a randomlyselected sample ofthe investigational drugs
`of the firms participating in the survey.° The sample was taken fromaTufis Center for the
`Study of Drug Development (CSDD)database of investigational compounds. Cost and time
`data were also collected for expenditures on the kind of animaltesting that often occurs
`concurrently with clinical trials.? The compounds chosen were all self-originated: thatis,
`their development up to initial regulatory marketing approval was conducted under the
`auspicesofthe surveyed firm.® Licensed-in compounds were excluded because non-survey
`firms would have conducted portions of the R&D?
`Wealso collected data from the cost survey participants on their aggregate annual phar-
`maceutical R&D expenditures for the period 1980-1999. The firms reported on total an-
`nual R&D expenditures broken down by expenditures on self-originated newdrugs. on
`licensed-in or otherwise acquired newdrugs, and on already-approved drugs. Annual ex-
`penditures on self-originated newdrugs were further decomposedinto expenditures during
`the pre-humanandclinical periods.
`The NationalInstitutes ofHealth (NTH) support throughtheir own labs and through grants
`to researchers in academic and other non-profit institutions a substantial amountof research
`
`
`> Using pharmaceuticalsales to measurefirm size, four of the surveyfirms are top 10 companies, another four
`are among the next 10 largest firms, and the remaining twoare outside the top 20 (PJB. 2000).
`© A copy ofthe survey instrumentis available upon request.
`7 Long-term teratogenicity and carcinogenicitytesting may be conductedafter the initiation ofclinicaltrials.
`5 This does not preclude situations in which the firm sponsors trials that are conducted byor in collaboration
`with a government agency, an individual or group in academia, a non-profit institute, or another firm.
`° Large pharmaceutical firms much more often license-in than license-out new drug candidates. Firmsthat
`license-in compoundsfor further developmentpaya price for that right through up-front fees, milestone payments,
`and royalty arrangements.
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`157
`
`that expands fundamental knowledge about human biology (NIH, 2000: Scherer, 2000).
`This basic research sometimes results in leads that industrial researchers can capitalize
`on to assist them in discovering new therapeutic compounds.!® Some new compounds
`investigated by pharmaccutical firms, however, originated in government or academic labs.
`It is unclear whether the discovery and early development costs for such compounds are
`similar to those for compoundsoriginating in industrial labs. These drugs, though, represent
`a very small portion of the total number developed. For example, NIH (2000) found that
`of 47 FDA-approved drugs that had reachedat least US$ 500 million in USsales in 1999,
`the governmenthad direct or indirect use or ownership patent rights to only four of them.'!
`In addition, we used a Tufts CSDD database supplemented by commercial databases to
`determine that of the 284 newdrugs approvedin the United States from 1990 to 1999,!7
`3.3% originated from industrial sources (cither from the sponsoring firm or from another
`firm from which the compound waslicensed or otherwise acquired). Government sources
`accounted for 3.2%of these approvals and academia and other non-profits accounted for
`the other 3.5%.!*
`The surveyfirms accounted for 42% of pharmaceutical industry R&D expenditures.!4
`The survey compounds were selected at randomfrom data contained in the Tufts CSDD
`database ofinvestigational compoundsfor the firms that agreed to participate in the R&D
`cost survey. Of the 68 compoundschosen, 61 are small molecule chemical entities, four are
`recombinantproteins, two are monoclonalantibodies, and one is a vaccine. Initial human
`testing anywhere in the world for these compounds occurred during the period 1983-1994.
`Developmentcosts were obtained through 2000. !*
`
`!0 The NIHalso supports the developmentofresearch tools that drug developers find useful. In addition,it funds
`training for manyscientists, some of whom eventually are employed in the industrial sector.
`'! The four drugs were developed in part through the use of NIH-funded patented technologies. Three of the
`four products are recombinantproteins, with two being the same drug produced bytwodifferent companies. Each
`of the relevant patented technologies was developed at academic or non-profit institutions with financial support
`from the NIH.
`!2 ‘The definition ofa newdrug usedfor this analysis is a therapeutic new molecular entity approved by the FDA’s
`Center for Drug Evaluation and Research,
`'3 ‘The proportion ofinvestigational drugs that derive from industrial sourcesis likely to be even higher, since
`acquired drugs have higher clinical approval success rates than do self-originated drugs (DiMasi, 2001b). Our
`cost survey firms were less reliant on licensing-in drugs from non-industrial sources than were firms as a whole;
`98.8%oftheir new drug approvals during 1990-1999 were from industrial sources. DiMasi (2000) found markedly
`greater market entry of small niche pharmaceutical firms in the 1990s relative to earlier periods as measured by
`sponsorship of new chemical entity (NCE) approvals. A disproportionate share ofthe approvals obtained bythese
`newentrants was for drugs that originated in academia.
`'4 The data used were aggregate firm pharmaceutical R&D expenditures for the cost survey firms, as reported
`on our questionnaire, in comparison to PhaRMA memberfirm R&D expenditures (1994-1997) onethical phanna-
`ceuticals, adjusted to global expenditure levels (PhRMA, 2601).
`'S Surveys were sent to 24 firms (some of whom havesince merged). Twelvefirms responded that they would
`participate in some form. The data that two firmsultimately provided were not useable. The 10 firms from which
`we used data provided information on 76 compounds. However, the data for eight of these compounds were not
`sufficiently comprehensive to use. Thefirms that did not participate in the survey cited a number ofreasons for
`not doing so. The reasons included the extra demandsthat the transition effects ofa relatively recent merger were
`placing on their relevant personnel, the time and expense ofretrieving archival records in the manner required by
`the study, and difficulties in gathering the relevant data in a uniform manner because their accounting systems had
`changedsignificantly over the study period.
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`
`Weselected a stratified random sample ofinvestigational compounds.Stratification was
`based on the time elapsed since the origination of clinical trials and the current status of
`that testing. Reported costs were weighted to reflect the characteristics of the population,
`so that knowledge of the population from which the sample was drawn was needed. The
`population is composedofall investigational compoundsin the Tufts CSDD investigational
`drug database that metstudycriteria: the compounds wereself-originated andfirst tested in
`humans anywhere in the world from 1983 to 1994, and we had the information necessary
`to classify them according ourstrata. We found 538 investigational drugs that met these
`criteria. Of these compounds, 82 (15.2%) have been approved for marketing, 9 (1.7%) had
`NDAsor BLAsthat were submitted and are still active, 5 (0.9%) had NDAs or BLAs
`submitted but abandoned, 227 (42.2%) were terminated in 4 years orless from theinitiation
`of clinical trials, 172 (32.0%) were terminated more than 4 years after the start of clinical
`testing, and 43 (8.0%) were still in active testing as of the most recent check (31 March
`2001).
`Some firms were not able to provide full phase cost data for every new drug sampled.
`For example, phase I cost data were available for 66 of the 68 new drugs. However, we
`had somephase cost data for every drug in the sample. In addition, five compounds were
`still active at the time of the study. For these drugs it is possible that there will be some
`future costs for the drug’s most recent phase. Thus, for this reason our cost estimates may
`be somewhat conservative. However, given the small numberof drugsin this category and
`the fact that the impact would be on onlyone phasefor each of these drugs, our overall cost
`estimates are not likely to be materially affected.
`
`4. Methodologyfor estimating new drug development costs
`
`The approach that we use to estimate development costs is similar to that described in
`our earlier work (DiMasiet al.. 1991). We will outline here the general methodologyfor
`developing an overall cost estimate. In describing the approach, it will be clear that cost
`estimates for important components of the drug development process will also be derived
`along the way.
`The survey sample wasstratified to reduce sampling error. Results from previous anal-
`yses suggested that the variability of drug costs tends to increase with the development
`phase or the amountof time that a drug spends in testing (Hansen. 1979: DiMasiet al.,
`1991). Costs for successful drugs (i.e. those that achieve regulatory approval) also tend to
`be higher and more variable than those for drug failures. Thus. we based our strata on the
`length of time that failed compounds were in clinical testing and whether or nota compound
`had reach the stage in which an application for marketing approval had beenfiled with
`the FDA.
`
`'© Specifically. we used four strata: compoundsthatfailed in 4 years orless ofclinical testing: compoundsthat
`failed after more than 4 years had elapsed frominitial humantesting: compounds for which an NDAora BLA had
`been submitted to the FDA; and compounds that were still in active testing (as of 30 March 2001). Compounds
`for which an application for marketing approval had been submitted or which had been abandoned after lengthy
`testing were deliberately oversampled. The reported sample values were then weighted, where the weights were
`determinedso that the sample perfectly reflects the population in terms ofthe fourstrata.
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`159
`
`4.1. Expectedcosts in the clinicalperiod
`
`Since newdrug developmentis a risky process, with many compoundsfailing for every
`one that succeeds,it is necessary to analyze costs in expected value terms. Thetotal clinical
`period cost for an individual drug can be viewedasthe realization of a random variable, c.
`Giventhatit is not certainthat developmentofa randomlyselected investigational compound
`will proceedto a given phase, we maydefine expectedclinical costs for a randomlyselected
`investigational drug tobe C = E(c) = piftje + pusetie + PUT IMe + PA/LAle. Where py, prt,
`and py. are the probabilities that a randomly selected investigational compound will enter
`phases I-III, respectively, pthe probability that long-term animal testing will be conducted
`during the clinical trial period, and the j1’s are conditional expectations. Specifically, j1}.,
`{le, tte. ANd /Laje are the population meancosts for drugs that enter phases I-III, and
`clinical period long-term animal testing, respectively,
`Weighted mean phase costs derived from the cost survey data were used to estimate the
`conditional expectations. A description of howthe probabilities were estimated is presented
`in the next section. Assumingthat the estimated mean phase costs and success probabilities
`are stochastically independent, the estimated expected value is an unbiased estimate of the
`population expected value.
`
`4.2. Clinical success and phaseattrition rates
`
`An overall clinical approval successrate is the probability that a compound that enters the
`clinical testing pipeline will eventually be approved for marketing. Attrition rates describe
`the rate at which investigational drugsfall out oftesting in the variousclinical phases. A
`phase success rate is the probability that a drug will attain marketing approvalif it enters the
`given phase. A phasetransition probability is the likelihood that an investigational drug will
`proceed in testing from one phase to the next. All of these probabilities can be estimated
`from data in the Tufts CSDD database of investigational drugs from which our survey
`sample was drawn.
`The clinical approval success rate was estimated using a two-stage statistical estimation
`processthat has been describedin detail elsewhere (DiMasietal., 1991; DiMasi, 200 1b). The
`data used here consist of the investigational drugs in the Tufts CSDD database that werefirst
`tested in humans anywhere in the world from 1983 to 1994, with information ontheir status
`(approval or research abandonment) obtained through early 2001. Given that some of these
`investigational drugs werestill in active testing at the end of the study period, someofthe
`data are right-censored. Survival analysis can be applied in such a situation, where survival
`indicates that a drug has not reachedits ultimate fate (either approval or abandonment).
`The Tufts CSDD database of investigational compounds contains information on the
`latest phase that an abandoned compound wasin whenit was terminated. These data were
`used to determine the distribution of research terminations by phases.!” These results,
`
`'7 4 small proportion of the compounds in the database were eitherstill in clinical development (8.0%) or had
`an NDAor BLAfiled but not yet approved (1.7%). For those drugs in these groups that will eventuallyfail, their
`abandonment will tend to occur in later testing phases. To deal with the potential bias in the estimated distribution
`of researchterminations that would result fromusing just those compounds that had been abandonedbythe end of
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`together with the estimated overall clinical approval success rate were used to provide
`estimates of the probability that an investigational drug will enter a given phase, phase
`attrition rates, and phase transition probabilities. The estimated overall clinical approval
`success rate and the probabilities of entering various phases provide results with which
`estimates can be derived that include the cost of drugs that fail to make it through the
`development process. Specifically, we use the probabilities ofentering a phase to estimate
`the expected out-of-pocketclinical cost per investigational drug. Adding the out-of-pocket
`preclinical cost estimate described belowyields an estimate of total out-of-pocket cost per
`investigational drug. Dividing this estimate by the overall clinical success rate yields our
`estimate of out-of-pocket cost per approved drug.
`
`4.3. Out-of-pocket discoveryandpreclinical developmentcosts
`
`Manycosts incurred priorto clinical testing cannot be attributed to specific compounds.
`Thus, aggregate level data at the firm level were used to impute costs per drug for R&D
`incurred prior to human testing. Specifically. time series data for each surveyed firm on
`spending on pre-human R&D and on humantesting for 1980-1999 were obtained, and a
`ratio of pre-human R&D expenditures to human testing expenditures was determined based
`on an appropriate lag structure (on average. pre-human R&D expenditures should occur
`years prior to the associated human testing costs). This ratio was then multiplied by an
`estimate of out-of-pocket clinical cost per drug. which is based on the project-level data. to
`yield an esti