therapeutic drug repurposing, repositioning and...

54 Drug Discovery World Winter 2015/16

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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

Therapeutic drug.qxp_Layout 1 13/01/2016 18:03 Page 54

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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.

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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

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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.




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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


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).




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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



Drug Discovery

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


(90.94)8

572.8228


158.2413

1,102.0637


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.



Drug Discovery

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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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]


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).
