`
`Koios Pharmaceuticals v. Medac
`
`Medac Exhibit 2052
`
`IPR2016-01370
`
`Page 00001
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`Medac Exhibit 2052
`Koios Pharmaceuticals v. Medac
`IPR2016-01370
`Page 00001
`
`

`

`THE OXFORD HANDBOOK OF
`
`THE ECONOMICS
`
`OF THE
`
`BIOPHARMACEUTICAL
`
`INDUSTRY
`
`Page 00002
`
`Page 00002
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`

`

`
`
`CONS ULTING EDITORS
`
`MICHAEL SZENBERG
`
`LUBIN SCHOOL OF BUSINESS, PACE UNIVERSITY
`
`LALL RAMRATTAN
`
`UNIVERSITY OF CALIFORNIA, BERKELEY EXTENSION
`
`Page 00003
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`

`
`
`THE OXFORD HANDBOOK OF
`
`THE ECONOMICS
`
`OF THE
`
`BIOPHARMACEUTICAL
`
`INDUSTRY
`
`Edited by
`
`PATRICIA M. DANZON
`
`AND
`
`SEAN NICHOLSON
`
`UNIVERSITY PRESS
`
`Page 00004
`
`Page 00004
`
`

`

`OXFORD
`UNIVERSITY PRESS
`
`Oxford University Press. Inc, publishes works that further
`Oxford University’s objective of excellence
`in research. scholarship, and education.
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`
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`
`All rights reserved. No part of this publication may be reproduced.
`stored in a retrieval system. or transmitted, in any form or by any means,
`electronic. mechanical, photocopying, recording. or otherwise,
`without the prior permission ofOxford University Press.
`
`Library of Congress Cataloging—in-Publication Data
`The Oxford handbook of the economics of the biopharmaceutical industry i'
`edited by Patricia M. Damon and Sean Nicholson.
`p. cm.
`Includes bibliographical references and indexes.
`ISBN ops-o—ig-gnzgg—S (cloth :aik. paper)
`1. Pharmaceutical industry.
`2. Biopharmaceutics—-—Econornic aspects.
`1. Danzon. Patricia Muncli.1946—
`Il. Nicholson, Scan.
`111. Title: Economics of the biopharmaceutical industry.
`HD9665.5.094 2cm.
`338-4’r615r—dc23
`2011040315
`
`135 7 9 8 6 4 2
`Printed in the United States of America
`on acid-free paper
`
`Page 00005
`
`Page 00005
`
`

`

`CONTENTS
`
`Contributors
`
`.
`
`Introduction
`PATRICIA M. DANZON AND SEAN NICHOLSON
`
`PART I PHARMACEUTICAL INNOVATION
`
`. R&D Costs and Returns to New Drug Development:
`A Review of the Evidence
`
`JOSEPH Al DIMASI AND HENRY G. GRABOWSKI
`
`. Financing Research and Development
`SEAN NICHOLSON
`
`. Cost of Capital for Pharmaceutical, Biotechnology,
`and Medical Device Firms
`SCOTT E. HARRINGTON
`
`. The Regulation of Medical Products
`ANUP MALANI AND TOMAS PHILIPSON
`
`.
`
`Incentives to Innovate
`DARIUS LAKDAWALLA AND NEERA] Soon
`
`. Patents and Regulatory Exclusivity
`REBECCA S. EISENBERG
`
`vii
`
`1
`
`21
`
`47
`
`75
`
`100
`
`143
`
`167
`
`PART II THE MARKET FOR PHARMACEUTICALS
`
`. Pricing and Reimbursement in US Pharmaceutical Markets
`ERNST R. BERNDT AND JOSEPH P. NEWHOUSE
`
`. Regulation of Price and Reimbursement for Pharmaceuticals
`PATRICIA M. DANZON
`
`201
`
`266
`
`Page 00006
`
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`
`

`

`
`
`vi CONTENTS
`
`10. Drugs and Vaccines for Developing Countries
`ADRIAN Towse, ERIC KEUFFEL, HANNAH E. KETTLER,
`AND DAVID B. RIDLEY
`
`11. Insurance and Drug Spending
`MARK V. PAULY
`
`19.. Consumer Demand and Health Effects of Cost—Sharing
`DANA P. GOLDMAN AND GEOFFREY F. IOYCE
`
`13. Measuring Value: PharmacoeconOmics Theory and Practice
`ADRIAN Towsn, MICHAEL DRUMMOND,
`AND CORINNA SORENSON
`
`14. Price Indexes for Prescription Drugs: A Review of the Issues
`ANA AIZCORBE AND NICOLE NESTORIAK
`
`15. Empirical Evidencc on the Value of Pharmaceuticals
`CRAIG GARTHWAITE AND MARK DUGGAN
`
`16. Promotion to Physicians and Consumers
`DON KENKEL AND ALAN MATHIOS
`
`17. The Economics of Vaccines
`FRANK A. SLOAN
`
`18. Mergers, Acquisitions. and Alliances
`HENRY G. GRABOWSKI AND MARGARET KYLE
`
`Index
`
`302
`
`336
`
`365
`
`394
`
`438
`
`463
`
`493
`
`524
`
`552
`
`579
`
`Page 00007
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`
`

`

`
`
`CHAPTER 2
`
`R&D COSTS AND
`
`RETURNS TO NEW
`
`DRUG DEVELOPMENT:
`
`A REVIEW OF THE
`
`EVIDENCE
`
`JOSEPH A. DIMASI AND
`
`HENRY G. GRABOWSKI
`
`ECONOMIC analyses of research and development (R&D) costs and returns in
`pharmaceuticals have received prominent attention by scholars and policy
`makers. Investment cycles in pharmaceuticals span several decades. Trends in
`future RScD costs and returns shape the incentives for companies to pursue R8(D
`opportunities for new medicines. Economic studies provide a basis for evaluat-
`ing all the factOrs affecting R&D costs and returns and can be useful in assessing
`productivity changes in the pharmaceutical and biopharmaceutical industries
`(Munos 2009). They also can be used to consider how various policy actions
`(e.g., price regulation) affect innovation incentives (Giaccotto et al. 2005; Vernon
`2005).
`
`This chapter reviews the extensive literature on R&D costs and returns. The
`first section focuses on R&D costs and the various factors that have affected the
`trends in real R8<D costs Over time. The second section considers economic stud-
`ies on the distribution of returns in pharmaceuticals for different cohorts of new
`drug introductions. It also reviews the use of these studies to analyze the impact
`
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`
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`
`

`

`fl
`
`PHARMACEUTICAL ENNOVATION
`
`W &
`
`D costs and returns. The final section concludes and dis.
`for further research.
`
`of olicy actions on R
`p
`cusses open questions
`
`
`
`PHARMACEUTICAL INDUSTRY R&D COSTS
`
`Estimates of the cost of developing new drugs have varied methodologically and
`in terms of coverage, but taken together, they paint a picture of substantially rising
`costs for more than half a century. The resource cost increases are dramatic, even
`after adjusting for inflation. This section briefly review the literature on pharma-
`ceutical R8rD costs and then describes some of the more recent results.
`
`Approaches to Estimating Pharmaceutical
`Industry R8rD Costs
`Early attempts to examine at least some of the costs of new drug development were
`quite limited in that they did not account for important aspects of the drug devel-
`opment process, such as non—drug-specitic R&D, expenditures on drug failures.
`and the length of the development process and its relationship to opportunity
`costs. DiMasi et al. (1991) referenced and discussed the early economic iiterature
`on the R&D costs of new drug development. One of the earliest of these studies
`(Schnee 1972] examined data on 17 new chemical entities (NCEs) from the 19505
`and 19605 for a single firm. However, only out-ofpocket (cash outlay) costs were
`considered (i.e., the time costs of R&D investments were not evaluated), and nei-
`ther fixed discovery costs nor the costs ofdrug failures were counted. This was fol-
`lowed by several studies that also focused on individual drug out-of-pocket costs;
`taken together With the Schnee estimate of an average cost of $0.5 million per NCE.
`these Studies Susgested that R&D costs increased substantially from the 19505 to
`the late 19605 (Mund 1970; Baily 1972; Sarett 1974; Clymer 1970}.
`The early literature also included two attempts to develop RSzD cost estimates
`from publiShed aggregate industry data on R&D expenditures and lists ofappffived
`NCES (Mund 197°? Bail? 1972l- These studies assumed fixed lag times between
`industry R&D expenditures and new drug approvals. Although these approaches
`:nlpllcrtly accounted for the costs of drug failures, neither of them included cap"
`a;;::::: of costs or accounted for varying lag times between expenditures and
`to
`of
`gatIOnal drug failures as Well as successes, fixed discovefi'
`
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`

`
`
`
`
`RSID COSTS AND RETURNS TO NEW DRUG DEVELOPMENT 23
`
`and preclinical development costs. and time costs) was that of Hansen (1979). The
`study used Tufts Center for the Study of Drug Development (Tufts CSDD) survey
`data from a dozen pharmaceutical firms to obtain a random sample oftheir inves-
`tigational drugs and aggregate annual data on their RStD expenditures broken
`down by development phase and compound source (self-originated or licensed—in).
`Hansen found an average capitalized cost of$54 million in 1976 dollars for develop-
`ment that occurred in the 19605 and up to the mid—19705. As with most subsequent
`studies, Hansen estimated the R&D cost per approved drug, taking into consider-
`ation costs incurred on failed drugs and adjusting historical costs to take account
`ofthe opportunity costs oftime.
`Following the Hansen (1979) study, Wiggins (198?) applied a regression analysis
`using industry—reported aggregate annual R&D expenditure data combined with
`the development time profile used by Hansen. Wiggins found a capitalized cost per
`approved new drug of $125 million in 1986 dollars for drugs approved from 1970
`to 1985. However, implicit in the analysis was the assumption ofa fixed lag rela-
`tionship for the time between R&D expenditures and ultimate new drug approval.
`This was not a shortcoming with the Hansen approach.
`Since Hansen's (1979) study, the survey approach has been dominant, with
`similar studies from DiMasi and associates that found increasingly higher R&D
`cost estimates for later periods. Specifically, DiMasi et al. (1991) reported an aver-
`age R&D cost of $2.31 million in year 1987 dollars ($318 million in year 2000 dol-
`lars), and DiMasi et al. (2003) reported an average RSKD cost of $802 million in
`year 2000 dollars. Companion studies to these two survey-based articles exam-
`ined how R&D costs varied by therapeutic category (DiMasi et al. 1995; DiMasi
`et al. 2004). Gilbert et al. (2003), using an internal Bain Consulting develop-
`ment model, found an estimate of $1.1 billion for 1995 to 2000 approvals, but
`the methodology was not deSCribed in any great detail and the results included
`launch costs. In two recent papers, Adams and Brantner (2006, 2010) attempted
`to validate the results reported by DiMasi et al. in 2003 using public data and
`found general support for them. Earlier, the Congressional Office of Technology
`Assessment concluded that the results in the 1991 DiMasi et al. study were rea-
`sonable (US. Congress, OTA 1993).
`The highest estimate to date in the literature of the expected, fully capital—
`ized cost of developing a single approved drug was $1.8 billion in year 2008 doi-
`lars (Paul et al. 2010). The authors obtained this resuit by using a mathematical
`model, some recent industry benchmark data on part of the process, and some
`internal data from a single firm. The most recent full capitalized R&D cost esti-
`mates based on industry survey data were reported by DiMasi and Grabowski
`(2007), although they focused on “biotech” drug development. The DiMasi et
`ai. (2003} and DiMasi and Grabowski (2007) findings are discussed in some
`detail later in this chapter, along with some comparisons to the earlier findings
`to illustrate the extent to which pharmaceutical RSrD costs have changed over
`time.
`
`
`
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`
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`

`

`
`
`PHARMACEUTICAL INNOVATION
`
`W R
`
`isks, Times, and Costs for Traditional
`Pharmaceutical Industry R&D
`Figure 2.1 indicates how inflation—adjusted aggregate industry pharmaceutical
`RSrD expenditures have changed over a long period, measured against changes over
`the same period in the number of US new drug approvals (new chemical entities,
`or NCEs). Given that drug development phases are lengthy, spreading over many
`years (DiMasi et al. 1991), there is a substantial lag betWeen when R&D expendi_
`tures are made and when new drugs get approved. Nonetheless, the data in Figure
`2.1 strongly suggest that average REID costs have risen at a rapid rate over time. A
`more rigorous analysis is needed to assess just how high pharmaceutical R8<D costs
`have been during any period and how rapidly they have risen over time. It is also
`instructive to look beneath an overall estimate of drug deVelopment cost to impor.
`tant aspects of the drug development process that contribute to that cost.
`
`Technical Risks
`
`One of the most important contributors to cost of drug development is the amount
`of resources that are devoted to drugs that fail in testing at some point in the devel—
`opment process. The series of studies begun with Hansen {1979) involved esti—
`mates of the likelihood that a drug that enters the clinical testing pipeline l[i.e.,
`phase 1) will eventually be approved for marketing by the US Food and Drug
`Administration (FDA) and estimates of attrition rates for drugs during the three
`clinical phases ofdevelopment. Hansen used a clinical approval success rate ofone
`in eight (12.5 percent). The second study in the series, DiMasi et al. (1991), found
`that the clinical approval success rate between the two study periods had increased
`substantially, to between one in five and one in four (13 percent). If nothing else
`had changed from one study period to the next, the estimated cost per apprOVEd
`
`60
`
`.3;U1
`
`HD
`
`G
`
`
`
`NMEApprovals
`
`R&D Expenditures
`
`60
`
`30
`
`15
`
`(ssuoztoworms)
`
`
`
`sam‘upuadxg(1:93
`
`I
`II
`
` 1963
`196?
`19?}
`mg [m 1933
`193?
`1991
`1995
`1999
`zoos
`zoo?
`nFigure 2.1. New drug approvals and R&D spending.
`Source: C
`Phar
`ml: est)’ of Tufts Center for the Study of Drug Development {CSDD} and
`ccullcal Research and Manufacturers of America (PhRMA), 2009.
`
` ________________H__
`
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`
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`
`

`

`
`
`
`
`RScD COSTS AND RETURNS TO NEW DRUG DEVELOPMENT 25
`
`new drug, inclusive of the cost of failures, would have declined significantly. This
`did not happen because, as described later, out-of-pocket preclinical and clinical
`costs also increased substantially, as did average development times and the cost of
`capital. The result was a much higher full average cost estimate.
`The most recent study in the series, DiMasi et al. (2003), found that the success
`rate had worsened for drugs tested in humans between 1983 and 1994 relative to
`drugs tested on humans between 1970 and 1982, but only modestly. The estimate of
`the clinical approval success rate was 21.5 percent. The effect offailures on costs was
`modified somewhat by estimates showing that firms had terminated their clinical
`failures earlier. However, as discussed later, other factors contributed to produce a
`much higher full cost per approved drug for the most recent period.
`
`Development Times
`
`When the R&D process for pharmaceuticals is lengthy, development cycles will
`be an important indirect determinant of costs if cash flows are capitalized to the
`point at which revenues from the investment could be earned. As development
`times increase, so do capitalized cost estimates, other things equal. The time from
`synthesis ofa new compound to first testing in humans increased by 6.6 months,
`on average, between the Hansen (1979) study and the DiMasi et al. (1991) study.
`The time from first human testing to regulatory approval increased by almost 21
`months, on average, between the study periods. The extra 2.3 years in average total
`time from discovery to approval for the second study period accounted for approx—
`imately 24 percent ofthe increase in average costs between the studies.
`In contrast, changes in development times had little impact on the increase in
`average cost between the DiMasi et al. (1991) study and the most recent study in
`the series, DiMasi et al. (2003). Although the time from first testing in humans to
`regulatory approval declined by an average of 8.6 months between the two study
`periods, the total time from discovery to approval remained, on average, virtually
`identical at 11.8 years. The increase in the cost of capital had a much greater impact
`on total capitalized costs than did changes in development times.
`
`Opportunity Costs
`
`Industrial R&D expenditures are investments, and there are potentially IOng lags
`between when the expenditures are made and when any potential returns can be
`earned. The three survey-based studies we focus on here attempted to capture
`these time costs, which, together with the out~of-pocket costs ofdevelopment, yield
`a measure ofthe opportunity costs ofbringing drugs from discovery to marketing
`approval. The approach is to capitalize costs to the point of first US approval using
`an appropriate discount rate. The discount rates used were estimates of the cost of
`capital for the pharmaceutical industry over the respective study periods. Average
`out—of-pocket costs by development phase were spread over average development
`times for each phase and capitalized to the point of marketing approval at the dis—
`count rate used for the study.
`
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`
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`
`

`

`W T
` 6
`
`PHARMACEUTICAL INNOVATION
`
`he real (i.e., inflation-adjusted) costs of capital used for the first tWo Studies
`Were 8 percent and 9 percent, respectively. The increase of one percentage point
`accounted for 13 percent ofthe increase in costs between the first two studies. The
`combination of longer development times and a higher discount rate for the sec.
`ond study accounted for 37 percent of the increase in average costs. As mentioned
`earlier, although there were some differences in development times between the
`second and third studies, the total development time was constant. Nonetheless,
`the estimated discount rate applied to the cash flows over the representative time
`profile was 2 percentage points higher for the third study (11 percent versus 9 per.
`cent). However, out-of—pocket costs increased enough that the time cost share of
`total capitalized cost remained virtually the same (50 percent for the third study,
`compared with 51 percent for the second).
`Figure 2.2 shows the primary results for the DiMasi et al. (2003) study. In year
`2000 dollars, the estimated preapproval capitalized cost per approved new drug
`was $802 million, with $403 million of that total accounted for by out-of—pocket
`cash outlays. Pharmaceutical R&D does not end with the approval of an NCE.
`Development often continues on new indications, new dosage strengths, and new
`formulations. The DiMasi et a1. (2003) study provided an estimate of postapproval
`RSrD costs. It found that approximately one-quarter of the total R8<D life—cycle
`cash outlays per approved new drug were incurred after a drug product contain-
`ing the active ingredient was first approved. Given that the analysis is focused on
`the point of first marketing approval, the postapproval costs must be discounted
`back in time to the date of marketing approval. Therefore, on a capitalized basis,
`postapproval R&D costs account for only 11 percent of the total life—cycle RSrD cost
`per approved drug, $897 million.
`
`Cost Trends
`
`The three survey—based studies, taken together, demonstrate that pharmaceutical
`industry R&D costs increased dramatically over the first four decades of the mod-
`ern era of drug development—that is, since enactment of the 1962 Amendments to
`
`(2000S)
`Millions
`
`Out-of—Pocket
`
`Capitalized
`
`l
`fl Pre-approval I Tatal
`ll] Post-approval
`figure 2.2 Pharmaceutical life—cycle Rle costs-
`Source: From DiMasi et al. 2003.
`
`i
`
`i
`
`A
`
`Page 00013
`
`I
`
`5
`
`I
`;
`
`
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`

`
`
`
`
`RSID COSTS AND RETURNS TO NEW DRUG DEVELOPMENT 27
`
`Millions
`
`(2000S}
`
`Figure 2.3 Pharmaceutical RBED costs gave increased substantially over lime.
`Source: From DiMasi et al. 2003.
`
`the Food and Drug Cosmetic Act of 1938, which, for the first time in the United
`States, required proof of efficacy as well as safety. Figure 2.3 shows how preclini-
`cal, clinical, and total preapproval average costs increased across the three studies.
`Preclinical costs are all costs incurred prior to first human testing. This includes
`out—of—pocket discovery costs as well as the costs of preclinical development.
`Clinical costs include all R&D costs incurred from initial human testing to first
`marketing approval.
`In constant dollars, total capitalized preapproval cost per approved new drug
`increased by a factor of 2.3 between the Hansen (1979) study and the DiMasi et al.
`(1991) study, and there was a similar increase of 2.5 between DiMasi et al. (1991)
`and DiMasi et al. (2003). However, at a more disaggregated level. there were sub—
`stantial differences. From the first to the second study, preclinical costs increased
`somewhat more than did clinical period costs. However, between the second and
`third studies, clinical cost per approved drug increased substantially more rapidly
`than preclinical cost [an increase of 349 percent for the former, compared with 57
`percent for the latter).
`The length of time between the study periods was not identical. We can
`get a more precise estimate of the rate of increase in costs across the studies by
`estimating the average endpoint for analysis in each study. The endpoint is the
`date of marketing approval. The first study roughly corresponded to develop—
`ment that yielded approvals during the 1970s, development for the second study
`mostly resulted in approvals during the 19808, and development for the most
`recent study was associated largely with 19905 approvals. DiMasi et al. (2003)
`found an average difference in approval dates of 9.3 years between the first and
`second studies and 13 years between the second and third studies. Using these
`time differences, we can calculate average annual rates ofincrease between the
`studies.
`
`Figure 2.4 indicates that the annual rate of increase in inflationaacljusted total
`out-of-pocket costs was relatively constant across the studies (7.6 percent between
`the first and second studies and 7.0 percent between the second and third studies).
`However, the rates of increase in overall costs mask substantial differences in how
`
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`
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`
`

`

`
`
`PHARMACEUTICAL INNOVATION
`
`
`
`Preclinical
`Clinical
`Total
`E! l9?05 to 1930s approvals
`I 1980510 1990s approvals _|
`Figure 2.4 Annual growth rates for R&D out-of-pocket cost per appmved new drug.
`Source.- From DiMasi et al. aoo3.
`
`
`
`costs changed over time for components ofthe R&D process. Figure 2.4 shows that,
`whereas preclinical costs continued to increase in real terms between the second
`and third studies, the rate of increase was less than one~third that between the first
`and second studies. 0n the other hand, the rate of increase in clinical period costs
`was dramatic for the most recent study—almost twice as fast as that between the
`first and second studies.
`
`Large—Molecule R&D Cost Metrics
`Almost all prior research on pharmaceutical R8rD costs has focused on synthetic.
`so-called small—molecule drugs, as opposed to biologics, or large-molecule drugs.
`Although some of the molecules for the DiMasi et a1. (2003) sample were biolog-
`ics, the overwhelming majority of the drugs in the sample and in the pipelines of
`the survey firms at that time were small-molecule drugs. The study by DiMasi and
`Grabowski (2007) was the first to focus on so-called biotech molecules. Specificallll
`the sample they used consisted ofapproximately equal numbers of recombinant pro-
`teins and monoclonal antibodies [mAbs). Although out—of-pocket clinical costs were
`collected for a relatively small sample of large molecules (17), the other metrics uSECl
`for the Cost analysis (development times and success and attrition rates) were deter-
`mined from large samples. The same methodology used to estimate average 6055
`for the three surveY-llased studies of traditional pharmaceutical firm development
`described earlier, was applied to the biotech sample.
`Figure 2-5 Shows some of the main results from the DiMasi and Grabowskl
`(30W) SludY- The average overall capitalized cost per approved new chemical
`mm)’ was $1.2 billion for large molecules. The study also compared develop-
`ment costs for small and large molecules. First, the results from the DiMasi 81 Bl-
`
`Page 00015
`
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`
`I.
`i:
`.
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`L
`I
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`

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`
`
`
`RSrD COSTS AND RETURNS TO NEW DRUG DEVELOPMENT 29
`
`Millions
`
`(20055)
`
`Freclinical'
`
`Clinical
`
`Total
`
` El Biotech El Pharma I Pharma (time-ad'usted)"
`Figure 2.5 Preapproval capitalized cost by new molecule type.
`Source: From DiMasi and Grabowski may.
`
`(2003) study were adjusted upward for inflation, because the biotech results were
`expressed in constant 2.005 dollars. This yielded costs for the preclinical and clin-
`ical phases, and overall costs, that were significantly lower for traditional small—
`molecule development. However, the molecules used for the biotech analysis were
`ofa later vintage than the sample used for the 2003 study. The biotech sample was,
`in some sense, five years more recent. Consequently, the results frorn the DiMasi
`et al. (2003) study were not only adjusted for inflation but also extrapolated out
`five years using the growth rates implied by the differences between the second
`and third survey-based studies of traditional pharmaceutical develoPment (see
`Figure 2.4). This produced an overall capitalized cost per approved new chemical
`entity for traditional pharmaceutical firm development similar to that for biotech
`development ($1.3 billion and $1.2. billion, respectively). However, there were sub-
`stantial differences by development phase. Clinical period costs were higher for
`traditional pharmaceutical development, but preclinical phase costs were higher
`for biotech development.
`
`Recent Metrics and Implications for R&D Costs
`
`The studies in the academic literature on the costs of new drug development cover
`the period from the 19505 to part ofthe first decade ofthe 215i: century. However, it
`is interesting to at least consider the trends for R&D costs during more recent years
`and for the near future. Without new data on cash flows, we cannot be conclusive
`
`about such trends, but there are many metrics that have an impact on full costs
`that can be examined for recent years. Taken together, these metrics may strongly
`suggest a direction ofchange.
`
`
`
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`PHARMACEUTICAL iNNovarioN
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`W I
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`mpact ofRisk and Time on Rd‘D Costs
`Before we examine recent industry benchmark data, it is instructive to get a sense
`for the degree to which changes in certain key development parameters affect over-
`all costs. DiMasi (zooz) was the first to construct various thought experiments
`that examined how much the capitalized cost per approved new drug changes in
`response to isolated changes in individual development phase lengths, equal pm-
`portiunate changes for all development phase lengths Simultaneously, individual
`clinical—phase attrition rates, and clinical approval success rates.
`Figure 2.5 is taken from the DiMasi (2002) study. It uses the results from the last
`survey—based study of traditional pharmaceutical industry development (DiMasi
`et al. 2oo3) as the base against which changes are measured. The figure sh0ws,1n
`percentage terms, the extent to which full capitalized cost per approved new drug
`is reduced if the overall clinical approval success rate is increased from its base
`case value of 21.5 percent to 35 percent. The resalts indicate that cost per approved
`new drug can be reduced by approximately 30 percent if the approval success rate
`increases from approximately one in five to one in three.
`A similar improvement in average cost can be obtained instead from faster
`development times. Figure 2.7 shows that a 30 percent improvement in total capi—
`talized cost per approved new drug would occur if all development phases and the
`regulatory approval phase were simultaneously reduced by half, other things equal.
`Since this work, Paul et al. (zoro) has presented similar results for improvements in
`parameters of their mathematical model.
`
`Development Time, Success Rate, and Trial Complexity Trends
`
`Although comprehensive estimates of out—of—pocket cash flows for new drug REID
`for recent years are not available, we can examine trend data for aspects of the
`development process that can be substantial determinants of changes in costs. As
`
`
`
`35%
`
`30%
`25%
`20%
`15%
`will:
`5%
`
`reduction
` Cost
`
`0%
`
`lI—_11_I_L__|_LI_I_LIL_|_I__.IIIIIIIJI
`eéfiei‘nzei‘jot’es‘aatfodorfifidaj
`
`Success Rate
`
`-I-
`.
`
`I:Average Phase cost +Phase cost adjusted for cost offailures 1
`Figure 2.6 Cost reductions from higher clinical success rates.
`Source: From DiMasi 2002.
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`RStD COSTS AND RETURNS TO NEW DRUG DEVELOPMENT 31
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`30%
`
` 259i:
`
` 20%
`
`
`
` 15%
`
`
`
` Costreduction
`
`0%
`
`..|_.t_4_1_|_ _.t._l
`
`_|.
`
`I
`
`0%
`
`5%
`
`10% 15% 20% 25% 30% 35% 40% 45% 50%
`Phase time reduction
`
`1- Clinical cost
`
`—I— Total cost
`
`Figure 2.7 Cost reductions from simultaneous percentage
`decreases in all phase lengths.
`Source: rom DiMasi 1002.
`
`noted earlier, lengthier average development times, other things being equal, result
`in higher full cost estimates, because R3tD cash flows are capitalized at a given dis—
`count rate over a longer period before first marketing approval. Kaitin and DiMasi
`{2011) examined US clinical development and regulatory approval phase trends
`since the early 1980s (Figure 2.8). Although these data do not account for clinical
`testing periods outside the United States prior to testing in the United States nor
`for preclinical development periods, the average total time from the start of clini~
`cal testing in the United States to US regulatory approval has varied little, ranging
`from approximately eight to nine years for each five-year period since the early
`19805.
`
`Although development times have remained relatively stable over the last few
`decades, the data on technical risks in drug development indicate a worsening of
`conditions. The DiMasi et al. (2003) study found an estimated clinical approval
`success rate of a little more than one in five (21.5 percent) for investigational drugs
`that first entered clinical testing between 1983 and 1994. More recently, DiMasi
`et al. (2010) found an estimated clinical success rate of approximately one in six
`(16 percent) for investigationa] drugs that first entered clinical testing from 1994
`through 2004 {Figure 2.9). Others have suggested even lower success rates for drugs
`tested in humans more recently (Paul et al. 2010).
`We can also gain insight into changes in direct resource costs associated with
`individual investigational drugs from data on the complexity ofclinical trials at a
`fairly micro level. Getz et a1. (2008) examined a very large number ofUS-based piv-
`otal clinical trial protocols to determine changes in protocol complexity over time.
`Unique procedures in these protocols were counted, as well as the frequency with
`which those procedures were to be employed in each protocol. In addition, eligibil—
`ity criteria were examined, and a measure of investigator work effort was applied
`to the individual procedures. Data for 1992—2002 and 2003—2006 were compared.
`
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`PHARMACEUTICAL INNOVATION
`
`
`
`Years
`
`
`
`
`1935—89
`
` 193034 1990-94
`
`I3 Approval Phase
`13 Clinical Phase
`Figure 2.8 Mean US clinical development and regulatory approval phase
`times by period of approval.
`Source: From Kaitin and DiMasi 2011.
`
`
`
`Transition
`
`Probability
`
`Phase 1-1!
`
`Phase ll-lli
`
`Phase III-
`NDMBLA Sub
`
`NDAJBLA Sub-
`NDAIBLA App
`
`Phase I —
`NDAFBLA App
`
`[I 19934998 I 1999-2004
`
`Figure 2.9 Phase transilion probabilities and clinical success rates
`by period of first human testing.
`Abbreviations: NBA, new drug application; BLA, biologic license application;
`Sub, submitted; App, application.
`Source.- From DiMasi el al. 201:).
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`R8KD COSTS AND RETURNS TO NEW DRUG DEVELOPMENT
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`33
`
`As shown in Figure 2.10, the number of unique procedures per protocol, the fre-
`quency with which the procedures were applied, the work effort per procedure,
`and an overall measure ofthe burden of executing the protocols all increased. Of
`the measures depicted in Figure 2.10, only investigator fees declined, and those
`only slightly. In addition, the authors found that eligibility criteria for enrollment
`increased, patient enrollment and retention rates declined, and the number ofcase
`report forms per protocol increased.
`
`Implicationsfor Real) Cost Trends
`
`The recent trends in aspects of the drug development process described in the
`previous section have implications for R&D costs in recent years. As was the case
`for differences between the second and the third surveynbased studies, the data
`on approved drugs examined to date make it seem unlikely that changes in devel—
`opment and regulatory approval phase times will have had much impact on R&D
`costs in recent years. However, many in the industry have suggested that develop-
`ment times-have begun to increase in the wake ofhigh-profile safety concerns for
`approved drugs such as Vioxx and Avandia. It may be too soon to observe much
`impact from increased regulatory stringEncy for drugs that have been approved
`to date.
`
`As indicated in Figure 2.6, other things being equal, a significant increase in
`technical risks (i.e., a decline in clinical approval success rates) will be associated
`with a substantially higher cost per approved new drug. The most recent d