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There is a growing consensus that Drug Repurposing,
Repositioning andRescue (DRPx) impacts all stakeholders involved in
the therapeutic drugsector. In part, this is due to the fact that
the pharmaceutical industry accrues~25% of its annual revenue from
DRPx products. However, a number ofmisperceptions are associated
with this sector, and that has led to limitedgrowth and
development. Historically, many of the smaller,
DRPx-focusedcompanies have relied on large pharmaceutical entities
as their primary sourceof revenue. This has usually been in the
form of a fee-for-service, or technologyplatform/product licensing
model. The problem with such business models isthat large
pharmaceutical companies have been, and continue to be,
ambivalenttowards externally-sourced DRPx endeavours. In order for
individual DRPxcompanies to be successful, they must rely less on
large pharmaceuticalcompanies and focus more on building their own
unique product pipeline inthe form of repurposed, repositioned and
rescued drugs. They must provide acompelling narrative about the
enhanced value proposition of DRPx productscompared to de
novo-derived therapeutic drugs. This is necessary to raise
thesignificant start-up and growth capital required to carry out
such activities. Inthis final paper we discuss the issues of risk,
time, cost and value enhancementassociated with bringing a DRPx
derived drug to market. In addition wepresent a comparative
financial analysis of a de novo-derived drug versus aDRPx-derived
drug on reaching the market, using Net Present Value (NPV)
andInternal Rate of Return (IRR) considerations.
Therapeutic Drug Repurposing,Repositioning and Rescue
Part IV: Financial model and analysis
By David M. Kauppiand Dr Stephen
Naylor
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I n the past year we have published a series ofarticles on Drug
Repurposing, Repositioningand Rescue (DRPx)1-3. We noted that
DRPxemerged in the early 1990s, and that all these inter-changeable
descriptors of DRPx usually refer to theprocess of identifying new
indications for existingdrugs, abandoned or shelved compounds and
candi-dates under development1. It has also been pro-posed that
Drug Repurposing should be used as aubiquitous term that includes
‘all the redevelopmentstrategies based on the same chemical
structure ofthe therapeutically active ingredient as in the
origi-nal product’4. Mucke has suggested that “repurpos-ing
describes the general concept of branching thedevelopment of an
active pharmaceutical ingredient,at any stage of the life cycle and
regardless of thesuccess or misfortune it has encountered so far,
toserve a therapeutic purpose that is significantly dif-ferent from
the originally intended one”5. DrugRepositioning is defined more
specifically, as theprocess of finding a new indication for an
approveddrug5. Finally, Drug Rescue refers to the develop-ment of
new uses for chemical and biological entitiesthat previously were
investigated in clinical studiesbut not further developed nor
submitted for regula-tory approval, or had to be removed from the
mar-ket for safety reasons5.
Much of the impetus for DRPx development hascome ostensibly from
specific non-profit and smallbiotechnology companies. In the past
20-25 years~70 non-profit organisations and companies havebeen
created that are dedicated to DRPx efforts2.During that same
timeframe, 11 companies havebeen acquired for a total of $2.38
billion, 10 com-panies have failed and three companies have
refo-cused their efforts away from DRPx. It is interest-ing to note
that the failure rate of DRPx companiesover a 10-year period is
only ~30%2. This is incontrast to the significantly higher failure
rate of40-50% in the general biotechnology sector6.Overall the DRPx
sector is vibrant and growing;with an average ~15 new companies
being formedevery five years. Furthermore, at least 25 of
thecurrent ~40 DRPx active companies are focused ondeveloping drug
candidate pipelines and producingmarketable drug products2.
The advantages that accrue from DRPx effortsare compelling when
the market potential of arepurposed/repositioned/rescued drug
(RRRDx) isconsidered. Such RRRDx price points are deter-mined by
the same market forces as for a de novo-derived Drug Discovery and
Development (DDD)product, and include drug safety and efficacy
dif-ferentiation, market need, patient acceptance, mar-keting
strategy and IP position. Thus a RRRDx has
the same possibility to achieve blockbuster statusas a de
novo-derived drug. We have highlightedthis phenomenon by listing a
‘top 10’ of currentmini-blockbuster (~$0.5 billion/year in sales)
andblockbuster (>$1 billion/year in sales) RRRDxs2.This
compendium of drugs includes Evista,Gemzar, Proscar, Propecia,
Revlimid, Revatio,Rituxan, Tecfidera, Thalomid and Viagra. It
isnoteworthy that all the drugs listed were developedand are sold
by large pharma or large biotechnol-ogy companies. The top 10
mini-blockbusters andblockbusters have produced a total of ~$12.89
bil-lion in peak annual sales alone. Based on suchcompelling
revenues, it is not surprising to learnthat DRPx constitutes
anywhere from 10-50% ofcurrent pharma R&D spending2. DRPx
efforts area determining factor in the lifecycle management
ofpharmaceutical products, and Persidis has estimat-ed that RRRDx
products generate ~25% of totalannual revenue for the
pharmaceutical sector7.
Many of the larger pharmaceutical companiescontinue to embrace
in-house DRPx efforts via aformal or ad hoc mechanism. One notable
excep-tion appears to be Merck, which remains cautiousbecause of
its experience with the NSAID,Rofecoxib (brand name Vioxx)1. In
contrast com-panies such as Roche, Celgene and Allergen evalu-ate
drug candidate compounds from a polyphar-macological perspective
and therefore considereach one as a potential treatment for
multiple dis-ease indications2. Other large pharma companiesthat
have dedicated in-house resources to DRPxinclude Novartis (New
Indications DiscoveryUnit), Bayer Healthcare Pharmaceuticals(Common
Mechanism Research group) and TEVA,which announced in 2013 the
creation of its ‘NewTherapeutic Entity’ initiative. Pfizer, on the
otherhand recently closed its DRPx IndicationsDiscovery Unit based
in St Louis, but joined theNational Center for Advanced
TranslationalSciences (NCATS) Therapeutic DiscoveryProgram. In this
latter programme, eight pharma-ceutical companies (AbbieVie,
AstraZeneca,Bristol Myers Squibb, Lilly,
GlaxoSmithKline,Sanofi-Aventis, Janssen and Pfizer) have
collective-ly made 58 of their shelved or abandoned com-pounds
available for DRPx. A similar initiativewas announced by the
Medical Research Council(MRC) in a partnership arrangement
withAstraZeneca in the UK. This programme wasexpanded to include
Cancer Research UK late lastyear, and allows unprecedented access
toAstraZeneca’s compound library2,3.
Substantial growth in the DRPx sector has result-ed in a myriad
of capabilities provided by specific
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non-profit and small biotech companies. Theseofferings range
from consulting and fee-for-servicetechnology platforms to
‘in-house’ discovery anddevelopment of RRRDx products2. The problem
isthat many of the DRPx companies have struggledto convince the
pharmaceutical sector of the valueof their service and product
offerings. More successhas been demonstrated by DRPx companies
thathave pursued their own drug candidate and drugproduct
pipelines. This latter approach has resultedin a number of
lucrative acquisitions by larger,more resource-rich companies, and
has been per-ceived as a primary source of rapid value creationand
accretion. However, such RRRDx product-focused companies usually
lack significant start-upand growth capital resources. In order for
new,emerging DRPx companies to attract capital theymust create and
execute on a viable business modelthat is not reliant on revenues
derived from servicesprovided to the pharmaceutical industry. They
needto create a compelling narrative as well as a docu-mented
business case that clearly differentiatesDRPx from de novo-derived
DDD drug products.In this paper we discuss and present a
comparativefinancial analysis for a de novo-derived drug versusa
DRPx-derived drug, using Net Present Value(NPV) and Internal Rate
of Return (IRR) calcula-tions. We consider also the implications of
our find-ings for DRPx companies focused on developingRRRDx
products.
Comparison of DDD versus DRPxmetrics and modelsA litany of woes
has beset the DDD processemployed by the pharmaceutical sector8.
Theprocess was conceived in the early 1960s and hasremained
unchanged over the past 50-plus years.Almost all other industries
that utilise an R&Dstrategy have made frequent and
sweepingchanges; whereas the DDD protocols practisedtoday continue
to be risk-ladened, slow, costly andinefficient, as well as
delivering products of ques-tionable value1. For example,
stratospheric risk isassociated with any effort to bring a drug to
mar-ket. The initial screening of compound libraries(104-106),
leads to a single compound that onlyhas an ~8% chance of
successfully traversing theclinical trials gauntlet9. In addition,
the failure rateof a drug candidate at each stage of DDD
clinicaltrials, namely Phase I, II and III is 46%, 66% and30%
respectively10. The average time requiredfrom drug discovery to
product launch remains atan eye-watering 12-15 years11. Finally,
the totalcapitalised cost of bringing a new drug to marketwas
recently calculated at a staggering $2.558 bil-
lion12. Some have argued that this is a gross
over-estimation13,14, and a more realistic value is$1.778
billion10.
The metrics associated with the DDD process areclearly
problematic, but there is also a growing con-cern about the value
proposition of the therapeuticdrug products on offer. A number of
factors haveconspired to highlight this issue and they include:
i. Drug safety: Not all approved drugs stand thetest of market
pressures due to the scrutiny ofpharmacovigiliance and post-market
surveillance.In some cases approved drugs can be removedfrom the
market because they manifest safety,effectiveness or economic
problems. For example,from 1994-2015 the USA Food and
DrugAdministration (FDA) issued 215 ‘Withdrawal ofApplication’
notices15. During that same time-peri-od the FDA actually recalled
26 drugs from the USmarket predicated primarily on safety
concerns16.This list includes well-known and widely-useddrugs such
as Baycol (Bayer AG, withdrawn 2001),Bextra (GD Searle, withdrawn
2005), Redux(Wyeth, withdrawn 1997) and Vioxx (Merck,withdrawn
2004). In the case of Vioxx alone, thelitigation settlements which
included patient law-suits as well as criminal plea charges cost
Merckmore than $5.8 billion17.ii. Drug effectiveness: There is now
a significantbody of evidence that indicates individual
patientsdiagnosed with the same disease indicationrespond
differently to the same therapeutic drug18.For example, Spears and
co-workers analysed theeffectiveness of a number of different drug
classesagainst major disease indications19. They foundthat most
drugs ranged in effectiveness from 50-75% as determined by patient
responses. The low-est patient responders occurred with
conventionalcancer chemotherapy (25%) whereas the highestpercentage
of patient responders was treated withCox-22-inhibitors (80%).
Therapeutic drugs werereported to be ineffective for 70% of
Alzheimer,50% of arthritis, 43% of diabetes and 40% ofasthma
patients19. iii. Pricing: As noted above, approved drug pricepoints
are determined by market forces thatinclude drug safety and
efficacy differentiation,market need, patient acceptance, sales and
market-ing strategy and IP position as well as individualR&D
costs20. In many cases rampant R&D costshave been used by
pharmaceutical companies tomaximise prices charged to the
patient/consumer.Unfortunately, even in such a favourable
economicclimate, only three in 10 approved drugs generaterevenues
that are at least equal to or greater than
References1 Naylor, S and Schonfeld, JM.Therapeutic
DrugRepurposing, Repositioningand Rescue: Part I-Overview.Drug
Discov. World WinterEdition. 54-62 (2015).2 Naylor, S, Kauppi, D
andSchonfeld, JM. TherapeuticDrug Repurposing,Repositioning, and
Rescue: PartII- Business Review. DrugDiscov. World Spring
Edition.57-72 (2015).3 Naylor, S, Kauppi, D andSchonfeld, JM.
TherapeuticDrug Repurposing,Repositioning, and Rescue: PartIII-
Market Exclusivity UsingIntellectual Property andRegulatory
Pathways. DrugDiscov. World Summer Edition.62-69 (2015).4 Murteira,
S, Ghezaiel, Z,Karray, S and Lamure, M. DrugReformulations
andRepositioning in thePharmaceutical Industry andits Impact on
Market Access:Reassessment ofNomenclature. Journal ofMarket Access
& Health Policy1: 21131 –
http://dx.doi.org/10.3402/jmahp.v1i0.21131(2013).5 Mucke, HAM. A
New Journalfor the Drug RepurposingCommunity. DrugRepurposing,
Rescue &Repositioning 1, 3-4 (2014).6 Novac, N. Challenges
andOpportunities of DrugRepositioning. TrendsPharmacol. Sci. 34,
267-272(2013).7 Persidis, A. Myths andRealities of Repositioning.
a.Systematic DRPx-2015Conference, Hanson Wade,Boston MA, USA
October 21-23, (2015). http://systematic-drpx.com b. 4th Annual
DrugRepurposing, Repositioningand Rescue Conference,Arrowhead,
Chicago IL USAMay 27-28
(2015).http://www.drugrepositioningconference.com/index.
Continued on page 57
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average R&D costs21. In addition, pricing strate-gies are
not as straightforward as in other indus-tries. For example, RRRDx
products should besubject to the same market forces as
DDD-derivedproducts, but the outcome is often nuanced andcomplex.
One such case study is Tecfidera(Dimethyl Fumarate) marketed by
Biogen. It wasapproved as a new indication to treat multiple
scle-rosis (MS) in 2013 and achieved stunning revenuesales of $2.91
billion worldwide in 20142.Tecfidera is one of three
recently-approved oraldrugs for the treatment of MS. The other two
denovo-derived drugs are Gilenya (Fingolamide)developed by Novartis
and FDA approved in 2010,and Aubagio (Teriflunomide) from
Sanofi-Aventisand approved by the FDA in 2012. The DRPx
drugTecfidera was priced at ~$55,000/year, whereasGilenya is more
expensive at ~$60,000/year, andAubagio is cheaper at ~$48,000/year.
It is notewor-thy that Tecfidera is outperforming the other
twodrugs predicated on its safety and efficacy profiles,and
aggressive pricing by Biogen does not appearto have hindered
sales2.
DDD productivity modelAll of the issues noted above raise the
beguilingquestion of how to improve on such a quandary ofproblems?
For more than 30 years the Center forthe Study of Drug Development
(CSDD) at TuftsUniversity has pondered this matter and evaluatedthe
R&D metrics of risk, time, cost and value asso-ciated with the
DDD process21. The CSDD esti-mated late last year the cost of
bringing a new drugto market at $2.558 billion12. This total
dollaramount included $1.395 billion in out-of-pocketexpenses, as
well as $1.163 billion in capitalisedcosts. This latter item is the
cost associated with an‘expected investment return’ that investors
foregowhile the drug is being developed. The estimate didnot
include an additional $312 million associatedwith lifecycle
management costs after the drug isapproved. The analysis was based
on 106 random-ly selected drugs from 10 major
pharmaceuticalcompanies that were developed during the
period1995-2007, and a 10.5 % cost of capital (CoC)was
applied22.
There was an immediate repudiation of theCSDD estimate,
accompanied by suggestions thatthe cost was inaccurate and
inflated13,14. Boothargued that the model was distorted since it
was“biased towards Big Pharma programs”14. A moreintense attack was
propagated by the medical char-ity Medicins Sans Frontieres (MSF),
which issued astatement stating that “if you believe that [cost
of$2.558 billion] you probably believe the earth is
flat!”13. In addition GlaxoSmithKline’s CEOAndrew Witty was
quoted as saying that “the fig-ure of a billion dollars to develop
a drug is amyth… and is used by the industry to justify exor-bitant
prices”13. MSF also exhorted that a morerealistic cost estimate
ranged from as little as $50million up to $186 million if the cost
of failed pro-grammes was also taken into account. The lattercost
was based on estimations obtained from theDrugs for Neglected
Disease Initiative (DNDi)23.
In 2010 Paul and co-workers proposed a com-prehensive R&D
model that estimated a capi-talised cost per new drug launch10.
This model hasfound fairly widespread acceptance due to its
thor-oughness and completeness. They argued that oneof the critical
issues facing the pharmaceuticalindustry was the problem of
productivity, and con-cluded that without an increase in R&D
productiv-ity, the pharmaceutical industry cannot sustain
suf-ficient innovation to replace lost revenues due topatent
expirations. Based on the critical impor-tance of this concept,
they attempted an unambigu-ous definition of R&D productivity
and presenteda compelling model consisting of “the essential
ele-ments of contemporary drug discovery and devel-opment that
account for the current cost of a newmedicine, and discuss[ed] the
rate-limiting steps ofthe R&D process that are contributing to
reducedR&D productivity”10. They went on to define
pro-ductivity as a relationship between the value of aNew Molecular
Entity (NME) or New BiologicalEntity (NBE) and the investment
required to actu-ally generate such an approved NME/NBE.
Finally,they proposed a ‘productivity relationship or
phar-maceutical value equation’ which was defined as:
P � WIP x p(TS) x V CT x C
where P is R&D Productivity WIP is work in progress
necessary
for a single new drug launch P(TS) is the probability of
technical
success V is value CT is cycle time (in years) C is cost (in US
dollars)
The model was developed using R&D perform-ance productivity
data from 13 pharmaceuticalcompanies, provided by the
PharmaceuticalBenchmarking Forum as well as internal
LillyPharmaceuticals project data. According to Pauleach of these
parameters can be considered on aper project or portfolio basis.
Clearly, increasing
Continued from page 56
8 PriceWaterhouseCoopers-Pharma 2020. i) The Vision; ii)Virtual
R&D; iii) Marketing theFuture; iv) ChallengingBusiness Models;
v) TaxingTimes Ahead; vi) Supplying theFuture vii) Introducing
thePharma 2020
Series.http://www.pwc.com/gx/en/pharma-life-sciences/pharma2020/index.jhtml.9
Cook, D et al. LessonsLearned from the Fate ofAstra-Zeneca’s Drug
Pipeline:A Five Dimensional Network.Nature Reviews: DrugDiscovery.
13, 419-431 (2014).10 Paul, SM et al. How toImprove R&D
Productivity: thePharmaceutical Industry’sGrand Challenge.
NatureReviews: Drug Discovery, 9,203-214 (2010).11 Deloitte Centre
for Healthsolutions. Measuring theReturn from
PharmaceuticalInnovation 2014. Turning aCorner?
http://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/measuring-the-return-from-pharmaceutical-innovation-2014.pdf.12
Tufts Center for the Studyof Drug Development. Cost toDevelop and
win MarketingApproval for a New Drug is$2.6 Billion. Press
ReleaseNovember 18th,
(2014).http://csdd.tufts.edu/news/complete_story/pr_tufts_csdd_2014_cost_study.13
Malipani, R. R&D CostEstimates: MSF Response toTufts CSDD Study
on Cost toDevelop New Drug. DoctorsWithout Borders, November18th,
(2014).http://www.doctorswithoutborders.org/article/rd-cost-estimates-msf-response-tufts-csdd-study-cost-develop-new-drug.
Continued on page 59
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any of the components of the numerator relative tothe
denominator will increase productivity andvice versa. For instance,
if one could decrease attri-tion, hence increase p(TS), for any
given drug can-didate or portfolio of drug candidates, at anyphase
in the process then P would increase accord-ingly. In a similar
manner any given level of R&D
investment, substantially reducing CT or C wouldalso increase P.
However, all of the components arelinked together and changing any
one element canadversely or beneficially impact other
elements.Based on their comprehensive analyses theydemonstrated
that development (Phase I-III)requires ~63% of total costs whereas
preclinicalefforts account for ~32% of total costs per NewMolecular
Entity (NME) launched. They estimatedthat only 8% of NMEs will
successfully traversecandidate selection to product launch. Finally
themodel required 9-11 molecules must enter clinicaldevelopment
every year in order to ensure a singleNME is launched per year.
Based on theirProductivity Model and a CoC of 11% they esti-mated
that it costs $1.778 billion per NME launchand on average this
takes 13.5 years. All the keycomponents of their findings are
highlighted andsummarised in Figure 1a.
DRPx Productivity Model Paul and co-workers argued that using
theirProductivity Model and starting from a baselinevalue for the
estimated capitalised cost of a singleNME, they could evaluate
which operationalparameters needed to be changed to enhance
pro-ductivity and thus impact the key metrics of risk,time, cost
and value. We took that cue and utilisedtheir basic Productivity
Model to create a DRPxProductivity Model. In the Kauppi-Naylor
DRPxProductivity Model there are some significant dif-ferences and
additional factors that need to be con-sidered. As we have
discussed previously, the con-ventional de novo discovery process
is typicallyreplaced by a computational and pathway/networkbiology
platform in DRPx discovery1. A number ofcompanies such as BioVista,
CureHunter andTherametrics, use algorithmically augmented
datamining to comprehensively query clinical trialdatasets as well
as other literature-derived data andinformation. The output from
this type of analysisis a prioritised list of high probability
RRRDx can-didates that can be potentially used to treat a spe-cific
disease indication.
Each RRRDx candidate is accompanied by an‘Evidence Network’ of
specific information con-tent that contains i) new disease
indication(s); ii)safety/toxicity profile from patient outcome
dataderived from original clinical trials and publishedliterature;
iii) putative target for the new diseaseindication; iv) possible
mechanism-of-action forthe new disease indication; v) panoply of
compan-ion diagnostics specific for the RRRDx candidatedefining
elements such as safety, efficacy andpatient stratification.
Finally, each selected RRRDx
Figure 1: De novo DDD versus DRPx Productivity Models. 1a (top):
Paul R&D Productivity Model for a de novo derived drug
traversing a conventionalDDD process that ensures one successful
NME launch (adapted from10).Probability: determined as a %, and is
equivalent to the p(TS), which is the probability oftechnical
success.WIP/Launch: number of ‘Work in Progress’ projects necessary
for a drug product.Launch cost: Capitalised cost at an 11%
capitalised cost.Cycle Time: Time taken for each stage or phase
shown in years.1b (above): Kauppi and Naylor R&D Productivity
Model for a DRPx derived drug. Terms asdefined in Figure 1a
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candidate should be subjected to an in vitro or invivo efficacy
determination using an appropriatecell/tissue/animal model. A
successful RRRDx can-didate can then be filed for IND status via
the505(b)(2) regulatory pathway, entering the clinicaltrials
process at Phase II3. The RRRDx candidatemust then traverse both a
Phase II and a Phase IIIclinical trial before an NDA is filed,
leading even-tually to market launch. This is all captured
andsummarised in Figure 1b.
Perusal of the Kauppi-Naylor DRPxProductivity Model (Figure 1b)
reveals some signif-icant differences compared to the Paul
ProductivityModel. In the DRPx discovery phase, the dataset
ofpotential RRRDx candidates comprises all knowndrugs and
biologically active agents. For example,in the case of CureHunter
this consists of~247,600 compounds interrogated across
~11,600defined disease indications24. Given the densityand quality
of data and information content asso-ciated with each prioritised
RRRDx candidate andbased on a discussion with other DRPx
companies,the probability of technical success for the
DRPx‘discovery’ stage portfolio of candidates is estimat-ed at
100%. In addition we calculated the cost ofDRPx discovery at
$225,000 per RRRDx candi-date. This includes salaries for key
personnel, over-head and efficacy determination studies all at aCoC
of 11%, bringing the total discovery cost to~$1 million (Figure
1b).
In terms of building out our model for the addi-tional Phase II,
Phase III and Approval stages, weutilised the lower rates of
attrition in the DRPxprocess reported by Thayer25. She stated that
25%of DRPx drugs successfully make it from Phase IIto market launch
in contrast to only 10% for con-ventional DDD drugs. The
probability of successfor DRPx drugs advancing from Phase III to
mar-ket increases to 65%, compared with only 50% forDDD drugs. This
is reflected in our model wherethe improvement in the percentage of
compoundsadvanced utilising DRPx versus traditional DDDimpacts on
p(TS), WIP/Launch, cost and cycletime. In terms of WIP/Launch
projects this isreduced from 4.6 to 2.2 for Phase II and 1.6 to
1.1for Phase III. As predicted by Paul, reducing attri-tion rates
in Phase II and Phase III can significantlyreduce costs10. Our
model also reflects that realityand the capitalised costs for Phase
II are reducedfrom $319 million down to $161 million for theDRPx
process, and from $314 million down to$262 million, as seen by
comparing Figure 1a ver-sus Figure 1b. Conservatively, we have
estimatedthat the cycle time remains the same, since we havelimited
data, but there is evidence that the cycle
time for both Phase II and Phase III will be reducedin the DRPx
process (see later for discussion).
Value of DRPx ModelA comparative analysis of the Paul
ProductivityModel (Figure 1a) representing de novo DDD ver-sus the
Kauppi-Naylor DRPx Productivity Model(Figure 1b) reveals that a
well-devised DRPx strat-egy can add significant value to
pharmaceuticalcompany pipelines. In addition such an approachmakes
a compelling narrative for smaller DRPx-focused companies who are
in the process of mak-ing decisions about the future strategic
directionand focus. At a metrics level the specific issues
thatcontribute to the value of DRPx based on themodel are:
i. Productivity/risk: The attrition rate of drug can-didates
subjected to the conventional DDD processis ~95%. Much of this
failure is caused by a com-pound’s lack of safety (~45% failure in
Phase I) andefficacy (~65% failure rate in Phase II)10. Thesepoor
success rates place tremendous pressure on thedrug pipeline and
hence pharmaceutical companyproductivity. Paul has also argued that
reducingattrition rates (increasing p(TS) for Phase II andPhase III
are the key impact changes to increaseproductivity10. Since RRRDx
candidates have beeneither approved or shown to be safe in late
stage tri-als they can enter the pipeline at Phase II, thus
com-pletely removing any attrition rate at discovery andpreclinical
stages. In addition, as discussed abovethe attrition rates for both
Phase II and Phase III aresignificantly reduced in the DRPx
process. In partthis is due to the increased information
contentavailable for the RRRDx, thus enabling better,faster
decisions to be made in terms of safety andefficacy. Optimisation
of this data/information teth-ered to a specific candidate drug
should onlyenhance the probability of success and decrease therisk
associated with the clinical trial process.ii. Time savings: A
commonly-cited assumption isthat DRPx can reduce the conventional
DDDprocess by 3-5 years. We estimate a cycle time of~7.5 years for
a DRPx drug, based on the Kauppi-Naylor Productivity Model (Figure
1b). We suggestthis can be further reduced by innovation at
theclinical trials stages predicated on the adroit use ofcompanion
diagnostics. However, it should benoted that there are examples of
even more rapidDRPx approvals. Crizotinib was investigated as aDRPx
drug based on its ALK-inhibiting properties.It was approved for the
new indication of NSCLCtreatment in a cycle time of just four
years26.iii. Cost savings: Previously, Persidis has suggested
Continued from page 57
14 Booth, B. A Billion Here, ABillion There: The Cost ofMaking a
Drug Revisited.Forbes /Pharma & HealthcareOnline. November
21st(2014).
http://www.forbes.com/sites/brucebooth/2014/11/21/a-billion-here-a-billion-there-the-cost-of-making-a-drug-revisited/.15
Gaffney, A. How OftenDoes FDA Withdraw DrugsUsing
DiscontinuationPetitions? Very Rarely.Regulatory Affairs
ProfessionalSociety. June 15th,
(2015).http://www.raps.org/Regulatory-Focus/News/2015/06/15/22690/How-Often-Does-FDA-Withdraw-Drugs-Using-Discontinuation-Petitions-Very-Rarely/.16
ProCon,Org Thirty-FiveFDA-approved PrescriptionDrugs Later Pulled
from theMarket.
http://prescriptiondrugs.procon.org/view.resource.php?resourceID=005528.17
Feeley, J. Merck Pays $23Million to End Vioxx Drug-Purchase
Suits.BloombergBusiness. June 15th,(2013).
http://www.bloomberg.com/news/articles/2013-07-18/merck-pays-23-million-to-end-vioxx-drug-purchase-suits.18
Vizirianakis, IS (Ed).Handbook of PersonalizedMedicine: Advances
inNanotechnology, DrugDelivery and Therapy. CRCPress/Taylor Francis
Group.Boca Raton, FL, USA. (2013). 19 Spear, BB, Heath-Chiazzi,
Mand Huff, JJ. ClinicalApplications ofPharmacogenetics. Trends
Mol.Medicine 7, 201-204 (2001).20 Persidis, A. The Benefits ofDrug
Repositioning. DrugDiscov. World Spring Edition:9-12 (2011).21
Kaitin, KI. Deconstructingthe Drug DevelopmentProcess: The New Face
ofInnovation. Clin. Pharmacol.Ther. 87, 356-361 (2010).
Continued on page 63
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that the cost “to relaunch a repositioned drug aver-ages $8.4
million”20. This appears to a rather con-servative estimation and
may be more applicable tosimple, line-extension DRPx cases. Based
on ourmodel we estimate that the out-of-pocket cost iscloser to
~$320 million, with a capitalised cost of$350 million, assuming
that the RRRDx candidatehas to only undergo Phase II and Phase III
clinicaltrials. This represents a 80.3% saving, comparedto the
$1.778 billion cost of a de novo DDD drug.In addition, we believe
that the choice of the DRPxtechnology deployed with its rich
information con-tent, as well as innovative execution in the
clinicaltrials stage can dramatically affect the final cost ofthe
DRPx process and reduce costs even further.
It is also important to recognise that DRPx stillrequires an
element of discovery and development.These undertakings bring
inherent risk and it isimportant that one comprehensively
understandsthe science, disease, patient population,
regulatory,business and IP issues associated with any specificDRPx
initiative. For instance new Phase I clinicaltrials may be required
if the DRPx candidate is an
old drug and the original safety data does not meetcurrent
regulatory standards. Plus, safety issuescan still present problems
for a potential new indi-cation. Another obvious challenge is that
the effi-cacy of a RRRDx must be demonstrated. Clearlythe RRRDx
must have superior, differential prop-erties from existing drugs
already being marketedand sold in the same class. Otherwise it will
be sub-ject to the same regulatory scrutiny as a conven-tional
drug, which could have a significant impacton its forward progress.
Any lack of differentiationor clear efficacy can obviously lead to
the RRRDxtrial being abandoned.
Financial analysis – DDD versus DRPxWe have discussed the Paul
Productivity Modeland the Kauppi-Naylor Productivity Model
byconsidering the metrics of risk, time, cost andvalue. We now
adapt both Models in order to pro-vide financial insights into DDD
versus DRPx.Paul originally identified out-of-pocket costs foreach
stage of the DDD process10. In order to moreaccurately portray the
impact of the 13.5-year gapbetween the first invested dollar and
the start of
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positive cash flow, he also incorporated capitalisedcosts into
the model. This latter analysis builds thetime value of money into
calculating the true costof this process. For example, if a
pharmaceuticalcompany invests $50 million into the discoveryprocess
in year one, then according to the PaulModel it will not receive a
return for 13.5 years,until the approved drug product reaches the
mar-ket and records sales. The simplest way to thinkabout the
capitalised cost is to consider what that$50 million would be worth
‘invested’ in a bankaccount paying 10% interest annually. There is
acalculation called future value which measuresthis, but for
simplicity, think of multiplying the$50 million by 110% compounded
annually 13.5times. The capitalised cost for this $50
millioninvestment is now $181.24 million! The PaulModel develops
this premise and actually deter-mines the level of expenditure at
each stage of thediscovery and development cycle and capitalisesthe
cost of each stage based on how many years itis from the
expenditure until positive cash flow.For example, expenditure at
the early discoveryphase would be outstanding for 13.5 years
whereasthe first year expenditure in Phase III clinical trialswould
be outstanding for only four years, asshown in the Cycle Time row
in Figure 1a.
In this discussion we expand the analysis using aNPV and IRR
approach in order to determine therevenue requirement of the
resulting approveddrug necessary to break even financially, given
thefront-end loaded expenditures and the significanttime delay in
receiving revenues due to the verylengthy approval process. We also
compare andcontrast the NPV and IRR values of DDD versusDRPx. In
order to do this we have used the PaulModel, described above and
summarised in Figure1a for DDD, and our newly described
Kauppi-Naylor DRPx Model we have recently developedand summarised
in Figure 1b.
The NPV calculation is one that is typicallyutilised by the
finance departments of corporationsto aid them in allocating
capital to determine opti-mal investment opportunities27. The
NPVapproach accounts for the time value of money, justas Paul did
in presenting the capitalised cost model.The objective in our NPV
analysis is to modelexpenditures as a function of time, as well
revenuesand when they are received and relate all these fac-tors
back to the start of the process at day one, iepresent value. It is
important to bear in mind thatthe nature of drug discovery
front-end loadsexpenses and back-end loads revenues leading
toburdensome expenses and revenues that are rela-tively muted. For
example, $10 million spent on
day one, costs the project in NPV $10 million, but$10 million in
revenue received at the end of year13 (assuming a CoC of 10%) is
worth just$2,606,945. In other words the NPV analysis takesall
cashflows for a project and discounts them backto day one using the
determined cost of capital. Ifthe calculation results in a positive
NPV this indi-cates that the project/investment should move
for-ward, and conversely a negative NPV outcome sug-gests the
project/investment should be abandonedor modified. In a similar
manner an IRR analysismodels all of the project’s cashflows over
time andthen enables the calculation of the rate of return onthe
capital investment27. The initial goal is to deter-mine the value
point of the IRR that makes theproject/investment worthwhile
pursuing. In thesubsequent analysis if the target IRR is met then
theproject/investment should proceed.
We focused our initial analysis on the revenueneeded from an
approved drug in order to recoupR&D costs and financially
break-even. The criteriawe applied to the analysis was a CoC of
10%, aNPV=0 and an IRR of 10%. In our NPV and IRRanalysis of the
DDD process we employed the sameup-front cost metrics and the
timing of thoseexpenditures as described by Paul (Figure 1a).
Weestimated that the revenues produced by the result-ing approved
drug and the timing of those receipts
DRUG REVENUE DE NOVO DDD DRPx DDD
$100 million – NPV$100 million – IRR
(340.12)a
(2)43.5812
$200 million – NPV$200 million – IR
(215.53)4
308.2022
$300 million – NPV$300 million – IRR
(90.94)8
572.8228
$500 million – NPV$500 million – IRR
158.2413
1,102.0637
$750 million – NPV$750 million – IRR
469.7217
1,763.6144
$1 billion – NPV$1 billion – IRR
781.2020
2,425.1650
$2 billion – NPV$2 billion – IRR
2,027.2327
5,071.3561
Table 1: NPV and IRR values as determined for annual drug
revenues ($100 million to $2 billion)
The values were obtained using a cost of capital of 10%. a In
accounting terms ( ) represents a negative value.
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were determined by a period of exclusivity basedon IP/Regulatory
considerations3) to be 10 yearspost market launch. These analyses
were carriedout on an ‘approved drug’ ranging in hypotheticalannual
sales from $100 million up to $2 billion,and these data are
summarised in Table 1. Thistype of sensitivity analysis creates a
decision matrixfor a pharma executive before they even embark ona
new disease target. This is highlighted by the fol-lowing
consideration for a de novo-derived drugusing the Paul Productivity
Model with our backend revenue levels suggesting that in order to
justbreak-even, the approved drug must produceannual cash flows of
$263 million and assuming anet profit margin of 70%, total revenues
of $375million. This very high break-even revenue require-ment
greatly limits the disease targets that thepharmaceutical industry
can profitably pursue.
In the case of the RRRDx-approved product, avery different
outcome scenario is determined. Asdiscussed above, in the DRPx
process the searchuniverse is only populated with candidate
drugsthat have been approved for use in humans, so the
entire 4.5 years and $219 million of out-of-pocketdiscovery
expense have been eliminated.Furthermore both Preclinical and Phase
I clinicaltrials are also not necessary resulting in an addi-tional
saving of time, 2.5 years, and $190 millionin out-of-pocket costs
(compare Figure 1a withFigure 1b). This has all been replaced by
algorith-mically augmented data mining of the universe ofclinical
trials data in order to identify high proba-bility candidates of
known safe drugs for a newindication(s)1. One final advantage to
such anapproach is the enhanced IP/Regulatory exclusivitytime
period afforded to a RRRDx, which we con-servatively estimate at 13
years. Based on all theseconsideration the break-even revenue level
for aDRPx approved drug is $85 million and marginsof $60 million
for our period of exclusivity com-pared to the $375 million in
revenue and $263 mil-lion in margin required to break-even on a de
novoapproved drug.
The IRR and NPV analysis summarised inTable 1 for approved
annual drug revenues rang-ing from $100 million up to $2 billion
clearly
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Therapeutic drug.qxp_Layout 1 13/01/2016 18:03 Page 62
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Drug Discovery World Winter 2015/16 63
Drug Discovery
demonstrates the significant financial advantagesaccrued by
employing a DRPx approach versus aDDD approach. Specific highlights
include:
l Lower or eliminated front end costs based onselection criteria
and mining research data using analgorithmic augmented approach.l
Shorter cycle time from project beginning toapproved drug.l Earlier
receipt of positive cashflows because thedrugs reach the market 5-6
years sooner.lA longer period of exclusivity because time to
prod-uct launch from patent date issuance is compressed.l A greater
percentage of advancement in Phase IIand Phase III trials resulting
in having to makeexpenditures on fewer compounds at these
veryexpensive stages.
This significant improvement in ROI is necessaryto
cost-effectively build WIP pipelines and start tooffset the revenue
losses caused by the steadystream of patent expirations. The lower
cost struc-ture greatly expands the universe of diseases thatcan
now be profitably targeted for drug develop-ment. This diminished
cost model with a muchimproved risk profile should attract new
investormoney and provide some needed capital, talent andenergy.
Foundations can adopt a new model toback these DRPx projects and
help speed cures totheir constituents. Orphan diseases that have
nothad the investment necessary to support their limit-ed
populations may find a new wave of investmentand support. What is
really exciting is that we areleveraging technology and we are
really in the earlystages as it applies to big data analysis and
algorith-mic discovery to identify new disease targets forknown
safe drugs. One could speculate of the expo-nential improvements
being made in the cost andtime of sequencing the human genome or
Moore’slaw as it applies to computing power and cost.
ConclusionsThe DRPx sector is populated by a small, but grow-ing
number of specialty companies and non-profitorganisations. We have
argued that in order forindividual companies to be funded and
successfullygrow they must be less reliant on the ‘benevolence’of
the pharmaceutical sector. In addition they mustconsider the
development of a credible narrative inorder to raise capital to
develop their own RRRDxproduct pipeline. We would suggest that the
com-parative analyses presented in the work makes acompelling case
for the advantages of the DRPxversus de novo DDD process. A simple
comparisonof bringing a DDD drug candidate to market versus
a DRPx drug candidate is remarkable in terms ofthe reduction of
risk, time and cost for the latter, ashighlighted in the
Kauppi-Naylor ProductivityModel. In addition the difference in
break-even rev-enues required for de novo-derived DDD versusRRRDx
candidate are illuminating. The break-evenrevenue level for a RRRDx
approved product is$85 million with associated margins of $60
million.This opens up tremendous opportunity not just forsmall DRPx
companies, but also DiseaseFoundations, other non-profits as well
as advocacygroups representing Orphan diseases.
The advent of personalised/precision medicinehas fuelled the
transition of patients to con-sumers28.This has led to a more
demanding cus-tomer-base that requires a better, cheaper,
person-alised product. We have suggested that DRPxefforts can
impact significantly on orphan, rareand neglected diseases, as well
as providing thera-peutic efficacy where none existed previously.
Inaddition a RRRDx may show utility for a popula-tion subset that
fails on the default standard treat-ment, has fewer side-effects
for a given individual,or plays a powerful adjuvant role in a
combinationtherapy with the primary agent. Consumer needs,in the
form of cheaper, faster, safer, more effica-cious drugs across the
entire drug spectrum may beconsidered and contemplated with the
more wide-spread adoption and use of DRPx.
As we have surveyed the DRPx landscape overthe past year, we
have been surprised at the per-ceived limited impact on the DDD
process andproduct offerings. Every analysis we have donefrom
business opportunity, to IP/Regulatory issuesand now financial
aspects of DRPx all indicate asector confronted with tremendous
opportunity.The question is how to leverage the opportunitiesand
change the misperceptions? DDW
David M. Kauppi MBA is the Managing Directorand President of
MidMarket Capital AdvisorsLLC. His company provides investment
bankingand revenue enhancement consulting services forhealthcare
technology firms. He was also a busi-ness and financial adviser to
CureHunter Inc, aDRPx company.
Dr Stephen Naylor is Founder, Chairman andCEO of MaiHealth Inc,
a systems/network biologylevel Diagnostics Company in the
health/wellnessand precision medicine sector. He is also a
scienceand business advisor to CureHunter Inc, and theChief
Scientific Advisor to MidMarket Capital.Correspondence should be
addressed to him [email protected]
Continued from page 59
22 DiMasi, JA, Grabowski, HGand Hansen, RW. Cost ofDeveloping a
New Drug.November 18th,
(2014).http://csdd.tufts.edu/files/uploads/Tufts_CSDD_briefing_on_RD_cost_study_-_Nov_18,_2014.pdf.23
Drugs for NeglectedDiseases Initiative (DNDi).Research &
Development forDiseases of the Poor: A 10-Year Analysis of Impact
of theDNDi Model. December 5th,(2013).
http://www.dndi.org/2013/media-centre/press-releases/dndi-rd-model/.24
Schonfeld, J. Computing aNew Cure for Ebola orAlzheimer’s in Four
MinutesFlat! Systematic DRPx-2015Conference, Hanson Wade,Boston MA,
USA October 21-23, (2015). http://systematic-drpx.com.25 Thayer,
AN. DrugRepurposing. Chem. & Eng.News 90, 15-25 (2012).26 Li,
YY and Jones, SJM. DrugRepositioning for PersonalizedMedicine.
Genome Medicine 4,27-41 (2012).27 Schmidt, R. Understandingthe
Difference Between NPVand IRR. Property Metrics June28th,
2013.http://www.propertymetrics.com/blog/2013/06/28/npv-vs-irr/.28
Naylor, S. What’s in aName? The Evolution of “P-Medicine”. J.
Precision Med. 2,15-29 (2015).
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