feature
Financing
drug
discovery
via
dynamic
leverage
VahidMontazerhodjat1,2,JohnJ.Frishkopf3andAndrewW.Lo1,2,4,5,[email protected]
We
extend
the
megafund
concept
for
funding
drug
discovery
to
enable
dynamic
leverage
in
which
the
portfolio
of
candidate
therapeutic
assets
is
predominantly
financed
initially
by
equity,
and
debt
is
introduced
gradually
as
assets
mature
and
begin
generating
cash
flows.
Leverage
is
adjusted
so
as
to
maintain
an
approximately
constant
level
of
default
risk
throughout
the
life
of
the
fund.
Numerical
simulations
show
that
applying
dynamic
leverage
to
a
small
portfolio
of
orphan
drug
candidates
can
boost
the
return
on
equity
almost
twofold
compared
with
securitization
with
a
static
capital
structure.
Dynamic
leverage
can
also
add
significant
value
to
comparable
all-equity-financed
portfolios,
enhancing
the
return
on
equity
without
jeopardizing
debt
performance
or
increasing
risk
to
equity
investors.
Introduction
Newadvancesinbiologyandbreakthroughsin geneticresearchhavepresentedthe biotech-nologyandpharmaceuticalindustrywithahost ofpromisingnewtargetsandcompoundsto treatarangeofdiseases.However,thedrug developmentprocessremainsunderfunded, withinvestorsshiftingcapitaltoothersectors becauseofmediocrereturnsonperceived high-investmentrisk.Acomparisonoffive-year per-iodsbeforeandaftertherecentfinancialcrisis (2004–2008versus2009–2013)showsthattotal fundingofdrugR&Ddropped21%,from US$21.5billiontoUS$16.7billion[1].Between 2004and2012,fundingfortheNational Insti-tutesofHealth(NIH)declinedby1.8%peryearin realterms[2].Althoughfundingseemstobe improvingoverthepastyearinresponsetoa numberofprominentbiotechinitialpublic offerings,thecapitalinflowsarehighly
concentratedamongafewlargedeals,andthe numberofnewstartupsisnotincreasing[3].In fact,thelackoffundingisparticularlyseverein early-stagedevelopment,beforePhaseIIclinical trials.Forexample,between2004and2011, fundingforprehumanpreclinicalR&Dinthe pharmaindustrydeclinedby2.3%peryear[2]; 2013sawonly63first-timeSeriesAfinancingsin biotechnology,almost30%lowerthanthepeak of89in2006andthelowestlevelinadecade[1]; andthenumberofactiveUSbiotechventure capitalfirmsdeclinedfrom201in2008to138in 2014[4].
Fernandezetal.[5]proposeda‘megafund’ financingapproach,applyingportfoliotheory andsecuritizationtechniquestoreducethe riskandenhancetheexpectedreturnsofa groupofinvestmentsindrugdevelopment projects.Unlikeatraditionalventurecapital fund,themegafundissuesequityanddebt
(‘research-backedobligations’orRBOs),and theportfolioofprojects–candidatedrugs, licensingagreementsandotherintellectual property–serveascollateralfortheRBOs.This approachdiversifiesthetypicallybinarydrug investmentresultsacrossaportfolioof thera-peutics,smoothingtheportfolio’spayoutand reducingthevolatilityofitsreturns. Securitiza-tionalsochangesthewaythatcashflows aredistributedfromapoolofbiomedical projects,allowingabroaderarrayofinvestors toparticipateintheriskandexpectedreturn ofdrugdevelopmentaccordingtotheirrisk appetite.
However,issuingsecuritizeddebtgenerally requirescollateralthatgeneratesareliableand well-understoodstreamofcashflowssuchasan approveddrug.Investmentsinearly-stage bio-medicalprojectsusuallyyieldnocashflowuntil theyreachPhaseIIband,eventhen,theyprovide
Features
PERSPECTI
VE
410
cashonlysporadically(e.g.whentheyare out-licensedorsold).Theunpredictabilityofthe amountandtimingofthesecashflowssuggests thatthemegafundisimpracticalforportfolios exclusivelyfocusedonearly-stagedrug discov-eryanddevelopment.
Inthisarticle,weextendtheconceptofthe megafundtoallowfortime-varyingamountsof debtor‘dynamicleverage’,whichcan accom-modatethestartupphaseofafundfocused purelyonpreclinicalR&Dandearly-stage translationalmedicine.Dynamicleverage adjuststheamountofdebtthatasecuritization vehiclecansustain,basedonparametersrelated toitsdefaultprobability(thelikelihoodofthe entitybeingunabletomeetitspayment obli-gationsonatimelybasis).Itisdirectlytiedtoa secondconcept,‘dynamicriskmeasurement’,in whichthedefaultriskofabondisperiodically measuredviacertaincreditmetricsand perfor-manceindicators.Together,dynamicrisk mea-surementanddynamicleverageenableusto constructatime-varyingsecuritizationstructure thatreflectstheevolvingnatureoftheportfolio’s assetsandoptimizesthefund’scapitalstructure accordingly.
Dynamicleverage
Dynamicleverageismotivatedbyasimple ob-servation:asaportfolioofbiomedicalprojects progressesitsriskshoulddecrease.Therefore, theamountofdebtofagivendefaultprobability thatcanbesupportedbythisportfolio,asa percentageofthetotalinvestedcapitalrequired, shouldincrease,effectivelydecreasingthe amountofequityrequired.Becausecostofdebt (assumedtobe5–8%here)islowerthancostof equity(usuallyinthe15–30%range),the sub-stitutionofequitybydebtyieldsanincreasein returnonequity.Thisdefaultprobability corre-spondstoaratingbyaNationallyRecognized StatisticalOrganization(NRSO)suchasMoody’s InvestorsServiceorStandard&Poor’s.The de-faultprobabilityisalsoreferredtoasasolvency standard,whereasthedebtasapercentof capitalisreferredtoasanattachmentpoint.
Atanypointduringthelifeofthefundthereis solvencyrisk,theriskthatthevehiclehas in-sufficientcashtomakescheduledinterestand/ orprincipalpayments.Foreachratingcategory thereisanassociatedsolvencystandardthat specifiesthemaximumacceptableriskof in-solvencyforthatratingclassuntilthenotesare repaid–seeTableS1,providedbyMoody’s InvestorsService[6](SupplementaryMaterial online).Theriskiscalculatedbyexaminingallof thepotentialoutcomes,anddeterminingwhat percentageoftheseoutcomesresultsinan
insolvencyevent.Therefore,theriskisrelatedto ameasureofthevolatilityoffuturecashflows. Foranygivenratingtranchethevolatilityof thecorrespondingcashflowscanchangeover time,andthereforetheinsolvencyriskcan change.Twofactorsdeterminethepotentialfor changeininsolvencyrisk.Theprimaryfactoris whetherthedrugdevelopmentprocessis pro-ceedinginaccordancetoanexpectedplan(orto themeanofallpossibleoutcomes)ateachtime instant.Iftheperformanceisaheadoftheplan, thentheprobabilityofinsolvencyshouldbe lowerthantheassumedvalue.Infact,ifthe performanceisonplan,theprobabilityshould beloweraswellbecausethedispersionoffuture pathshasnarrowed,loweringtheeffective vol-atility.Thesecondfactoristhepossibilitythat volatilityhasincreasedbecauseofchangesin externalfactors,e.g.,theenvironmentor im-proveddataandforecasts.However,thisclassof exogenouseventsisoutsidethescopeofthis paper.Formoredetailsandanillustrative ex-ampleondynamicleverageseeSupplementary Materialonline.
Dynamicmeasurementcanbemademore precisebyemployingadaptivetrials,during whichtheposteriorprobabilityofsuccessis continuouslyupdated;hence,theamountof debtcanbeadjustedaccordingly.However,for simplicitywedonotuseadaptiveclinicaltrialsin ourmodel.Dynamicriskmeasurementisnot onlyusefulindeterminingdynamicleveragebut inanyapplicationinwhichchangesinriskhavea materialimpact.Forexample,inafinancing structurethatemploysguarantees,the guaran-teefeecanbeadjusteddynamicallybasedon theriskprofileoftheportfolioovertime.
Dynamicleverageforanorphandrugfund
Forconcreteness,weusethestatisticalmodel describedin[7]toillustratedynamicrisk mea-surementanddynamicleverage.Thefocusof Fagnanetal.[7]onorphandrugstargetingrare diseasesisparticularlywell-suitedfordynamic leveragebecausethesetherapiesarerelatively newandnotlikelytobeabletogeneratemuch cashflowatfundinception.Tohighlighttherole ofdynamicleverageweemploytheidentical orphandrugparametersasinFagnanetal.[7]. Following[5,7],adiscrete-timefinite-state Mar-kovchainisemployedtomodeltheevolutionof eachcompoundthroughthedevelopment cy-cle.Theassumptionsregardingtheaveragecost, successrate,durationandvaluationofeach phasearelistedinTable1.Underthese assumptions,consideranRBOstructureto fi-nanceaportfolioofinvestigationaltherapeutics throughtheirdevelopmentcycle.Inexchange
forapledgeofthefutureroyaltycashflows, equityanddebtinvestorspurchasenotesand receiveaportionofthesecashflowstreams.
OursimulatedRBOportfoliocomprisesnine compoundsinthepreclinicalstageandten compoundsintheclinicalPhaseIstage.The employedcapitalstructureiscomposedofone equitytrancheandtwodebttranches,namely mezzanineandseniortranches.Theinitial amountsofcapitalfortheequity,mezzanineand seniortranchesareUS$373.75million,US$30 millionandUS$25million,respectively,andthe annualcouponratesforthemezzanineand seniordebttranchesare8%and5%, respec-tively.Thematuritydatesfortheseniorandthe mezzaninetranchesarefourandsixyears, re-spectively,andtheoutstandingbalanceofeach trancheispaidinfourequalinstallmentsover thetwoyears(foursemesters)precedingthe maturitydates.After13semesters(6.5years),the portfoliooftheremainingcompoundsis liqui-dated.Assumingthatthedrugsaletakesayear tosettle,thecashproceedsfromthesalegoto theequityinvestorsinthefifteenthsemester. Furthermore,anycompound,uponreachinga pre-specifiedtargetphase(PhaseIIIinthe simulations),getssoldregardlessofhowfarinto thelifeofthefunditis.
Astheportfolioofcompoundsprogressesand itsriskdecreasesovertime,thesizeofthedebt tranches–andthereforetheleverage–canbe adjustedtomaintainadesiredprobabilityof defaultforeachtranche.Forsimplicity,the tranchesizeadjustmentinthesimulationsis performedonlyforthemezzaninetranche,and upuntilthejuniorbondsstartprincipal repay-ment(i.e.untilthefourthyear).Figure1 illus-tratestheexpectedsizeofeachtrancheaswell asthetotalcapitaldeployedintheportfolio, fromtheequityandbondinvestors,overtime.
SeveraltrendsinFig.1areworthnoting.As seeninTable1,thecompoundsneed progres-sivelylargeramountsoffundingastheyproceed intheirdevelopmentcycle.Ifthetotalrequired capitalisraisedinitsentiretyatthebeginningof thefund’slife,inanticipationthatthe com-poundswillfollowtheirexpectedpathof de-velopment,itwillimposeadragonthefund’s returns.Shouldthiscapitalberaisedbycalling moreequity,thereturnontheequitytranche wouldbediluted.Alternatively,ifthefinancing structurekeepstheleveloftheinvestedequity constant,issuingmoredebtatthebeginningto meettheexpectedneedsoffuturedrug devel-opment,theprobabilityofdefaultforthedebt trancheswouldinevitablyincrease.Inthis ap-proach,usedin[7],theprobabilityofdefault increasesbecausethedeteriorationinportfolio
Feat
ures
PERSPE
valueleadstomoredebt,whereastheequityis thesameasbefore.Therefore,theprobabilityof defaultandthemagnitudeoflosswillincreaseif moredebtisissuedatfundinception.
Dynamicleveragecanmitigatethisissue. Specifically,themezzaninetrancheshould in-creaseinsizeovertimetoprovidethecapital requiredtofundthedevelopmentofthe com-poundsmovingforwardintheirdevelopment cycle.Thisisdoneonlyifraisingmoredebtdoes nothurttheprobabilityofdefaultforthejunior notes(i.e.ifitdoesnotincreasethesolvency risk).Hence,theincreaseinthemezzanine trancheisslowinearlierperiods,whentheriskof theportfolioisrelativelyhigh,andthedebt utilizationacceleratesastheportfoliomoves forwardintimeandriskisreduced.
AsecondtrendseeninFig.1relatestothesize oftheequitytranche,whichdecreasesovertime. Thisisduetodistributionsmadetotheequity investorswhentheportfolioisonorabovethe expectedpath.Thesedistributionscomefrom thesaleofthosecompoundsthathavereached theirtargetphaseofdevelopment,andfroma portionofthedebtraised.MATLABcodewith
anopen-sourcelicenseisprovidedin Supple-mentaryMaterialonlinetoallowreaders to examinethespecificsofhowthetranchesizesare determinedateachtime,and/ortousedifferent valuesforparametersusedinthemodel.
Astheriskoftheportfoliodecreases,wecan replaceanever-increasingamountofequitywith debttoyieldahigherrateofreturntotheequity investors.Thiscanbeachievedwithout jeopar-dizingthesolvencyoftheportfolio,ascanbe observedinTable2,wherethesimulated expectedannualizedinternalrateofreturn(IRR) ismorethan25%,andtheprobabilitiesof de-faultfortheseniorandmezzaninetranchesare lessthan0.1bpsand36.2bps,respectively. Theseprobabilitiesofdefaultandtheexpected losses,reportedinTable2,overthelifehorizon oftheseniorandjuniornotesarecomparableto thatofAAA/AaaandA+/A1ratednotes, re-spectively(TableS1inSupplementaryMaterial online).
Comparisontoall-equityfinancing
ThethirdcolumnofTable2,‘All-EQ1’,compares theRBOstructurewithanequitystructurein
whichaportfolioofsevencompoundsinthe preclinicalstageandsixcompoundsinPhaseIis fundedusingthesamelevelofequityasusedin theRBOstructure(i.e.US$373.75million).As observedinTable2,fewercompoundscanbe financedduringthelifeofthefundunderthe equitystructurecomparedwiththeRBO port-foliobecausethereisnoadditionalinjectionof capitalintotheequityportfolioaftertheinitial equitydraw.Thescientificimpactoftheequity structureis,consequently,smallerthanthatof theRBOportfolioasmeasuredbythenumberof thecompoundsthataresoldinPhasesIIandIII. Notonlyisthescientificimpactsmallerinthe equitystructure,butalsothereturn character-isticsoftheequitytranchearenotaspromising asthoseoftheRBOstructure.Owingtothedebt issuanceovertime,intheRBOcase,moreequity isreturnedtotheinvestorsearlier.Incontrast, intheequitystructurethereturnofcapitalto theequityinvestorsisconstrainedbythe speedwithwhichthecompoundsreachthe targetphaseandaresold.
ThefourthcolumninTable2,‘All-EQ2’, comparestheperformanceoftheRBOfundand theperformanceofthesameportfolioof com-poundsfinancedbyequityalone.Theamountof equityusedtofinancethisportfolioismatched tothepeakvalueofthetotalcapitaldeployedin theRBOstructure(i.e.US$510.70million)as observedinFig.1.Thislevelisalmost37%more thantheRBO’sinitialequitylevelofUS$373.75 million.AsisseeninTable2,thescientificimpact ofthisnewequitystructureisthesameasthatof theRBOstructure.However,thefinancial per-formanceoftheequitystructureisstillless promisingthantheperformanceoftheRBO becausemoreequityisdeployedintheequity structurethanintheRBOstructure.Theonlyarea inwhichtheequityportfoliooutperformsthe RBOportfolioistheprobabilityofnegative returnsontheequity.Intheequitystructure, thereisa10.3%chanceofdeliveringanegative returntotheequityinvestors,whereasthis chanceis10.6%fortheRBOportfoliobecause theequitytrancheintheRBOstructureisthefirst TABLE1
Simulationparametersfororphandrugdiscoveryanddevelopment
Phase Cost(US$millions) Successrate(%) Duration(years) Valuation(US$millions)
Preclinical 5 69 1.00 7.1 PhaseI 5 84 1.66 27.6 PhaseII 8 53 2.09 75.6 PhaseIII 43 74 2.15 321.5 NDA – 96 0.80 701.9 APP – – – 817.6 600 400 200 0 –200 –400 –600 –800 –1000 –1200 Senior Mezzanine Equity Total liabilities 1 3 5 7 9 11 13 15 Time (periods) Millions of US dollars
Drug Discovery Today
FIGURE1
Capitalstructureandtotaldeployedcapitalinthefundforeachsix-monthperiod.
Features
PERSPECTI
toabsorbanycapitallosses.Forthesamereason, theprobabilitythattheequityiswipedout[i.e. Pr(IRR= 100%)]islargerfortheRBOportfolio comparedwiththeequity-financedportfolios. However,theupsideoftheRBOportfolioismuch higherthanthatoftheequityportfolios,as measuredbytheright-tailprobabilitiesoftheir returnsreportedinTable2[i.e.Pr(IRR>10%) andPr(IRR>25%)].
Itisclearthataddingdynamicallyleveraged debttothepicture,whenfeasibleandasneeded tofunddrugdevelopment,canenhancethe scientificandthefinancialimpactofthe port-foliowithlittledownsiderisk.Furthermore,ifthe effectofdynamicleveragewerereplicatedusing anequity-financedportfolio,theamountof re-quiredequityupfrontwouldbesignificantly larger(almost37%moreinitialequitythanthe RBO’sinitialequityasobservedinTable2).
Comparisonwithstaticcapitalstructure
Forcomparison,theperformancestatisticsofthe RBOstructurewithastaticcapitalstructure, whichwasusedin[7],arereportedinthelast columnofTable2,labeled‘StaticRBO’.The dynamicRBOclearlyoutperformstheRBOwith astaticcapitalstructurefromscientificand financialperspectives.Thisperformance supe-riorityisachievedwithoutjeopardizingthe debtperformance.Notonlydoesdynamic leverageincreasethereturnonequitybutit alsohelpsreducetheprobabilityofdefault forthebondholdersincomparisontoastatic TABLE2
PerformanceresultsfortheRBOportfolio,twoequity-financedportfoliosandthestatic RBOportfolio
RBOa All-EQ1a,b All-EQ2a,b StaticRBOc Numberofcompoundsacquired
Preclinical 10 7 10 8
PhaseI 9 6 9 8
Researchimpact
CompoundssoldinPhaseII 2.6 1.8 2.6 2.2
CompoundssoldinPhaseIII 5.5 3.8 5.5 4.7
Liabilities(US$millions)
Capital 428.75 373.75 510.70 575.00
Seniortranche 25.00 – – 86.25
Initialmezzaninetranche 30.00 – – 115.00
Equitytranche 373.75 373.75 510.70 373.75
Equitytrancheperformance
ExpectedannualizedIRR 25.1% 20.7% 22.0% 13.4%
Pr(IRR= 100%) 38.4bps <0.1bps <0.1bps 60bps
Pr(IRR<0%) 10.6% 14.5% 10.3% 13.1%
Pr(IRR>10%) 77.3% 69.8% 74.6% 66.7%
Pr(IRR>25%) 49.8% 39.9% 42.0% 18.4%
Debttranchesperformance Seniortranche Probabilityofdefault <0.1bps – – 0.8bps Expectedloss <0.1bps – – <0.1bps Mezzaninetranche Probabilityofdefault 36.2bps – – 56.0bps Expectedloss 9.1bps – – 15.0bps
Abbreviations:RBO,research-backedobligations;Pr,probability;IRR,internalrateofreturn;bps,basispoints (1bp=0.01%).
a
Allreportednumbersareobtainedusing20,000,000MonteCarlosimulationpathsforeachportfolio.
b
All-EQ1isanequity-financedportfoliowheretheinitialinvestmentissetequaltotheinitialamountofequityintheRBO portfolio,whereasAll-EQ2isanotherequity-financedportfoliowheretheinitialinvestmentissettothemaximumamount ofcapitalintheRBOportfolio(Fig.1).
c
ForstaticRBO,seeFagnanetal.[7].
30 25 20 15 10 5 40 30 20 10
Expected annualized IRR (%)
Correlation, ρ (%) –20
–10 0
10 Change in the value of
approved drug (%) 28 26 24 22 20 18 16 14 12 10 8 30 25 20 15 10 5
Expected annualized IRR (%)
–25 –20 –15 –10 –5 0 5 10 Change in the value of approved drug (%)
ρ = 10% ρ = 15% ρ = 20% ρ = 25% ρ = 30% ρ = 35% ρ = 40% (a) (b)
Drug Discovery Today
FIGURE2
Expectedannualizedinternalrateofreturn(IRR)fortheresearch-backedobligation(RBO)andequitystructures.Thetexturedshadingin(a)andthesolidlinesin (b)correspondtotheRBOstructure.
Feat
ures
PERSPE
capitalstructure.Thisisachievedbecauseless debtisborrowedinitiallyandmoredebt issu-ancehappensovertimeonlyiftheriskofthe portfoliopermitstakingsuchaction. Further-more,becausetheprobabilityofdefaultis smallerforthisdynamiccapitalstructure thanthestaticRBOusedin[7],thevolatility ofthereturnonequityisconsequentlysmaller too.
Robustnessanalysis
Wechecktherobustnessofourresultsby varyingtwokeyparameters:thevalueofthe approveddrug(thebottomrightentryinTable 1)andthecorrelation(r)oftheassetvalues. Wheneverapplicable,wealsoconductthesame testsononeoftheall-equity-financedportfolios introducedearlier,All-EQ2,todistinguishthe roleofunder-andover-borrowingfromtherole thatassetmispricingplays.Thedetailsare reportedintheSupplementaryMaterialonline, andtheyyieldtwokeyobservations.First,the dynamicRBOportfoliomaintainsanacceptable performanceoverawiderangeofcorrelations andexpectedapprovalvalues.Second,the dy-namicRBOportfoliooutperformsthe all-equity-financedportfoliooverawiderangeof corre-lationsandassetvaluesunlessthepresumed valuesfortheparametersofthemodelarefar moreoptimisticthantheirrealizedvalues.Inthis case,theincorrectlydeterminedhighleveragein thedynamicRBOfundwouldexacerbatethe fund’spoorperformancecomparedwiththe all-equity-financedportfolio.
ThesefindingsaresummarizedinFig.2,which showsthattheequityperformanceoftheRBO fund–measuredbyitsIRR–issuperiortothatof theall-equity-financedportfoliooverawide rangeofcorrelation(r)andexpected-approval values.Theequity-financedportfolio,however, outperformstheRBOportfolioforlarge corre-lations(e.g.r=40%)andsmallapprovalvalues (e.g.iftherealizedapprovalvalueis25%less thantheassumedvalue).Forfurtherdetailsand acomparisonofotherperformancemeasures seeSupplementaryMaterialonline.
Concludingremarks
Theapplicationofportfoliotheoryand securi-tizationtechniquestofinancingdrug develop-menthasthepotentialtobeadisruptive technology.Inthispaperweproposeamore efficientstructureandhigherreturnstoequity forinvestorsbyaddingdynamicleverage,a novelsecuritizationtechnique,tothemegafund structureproposedin[5,7].Thereare,ofcourse,
anumberofpracticalchallengestolaunching andmanagingamegafund.Acomprehensive discussionofthesechallengesisbeyondthe scopeofthisarticle,butweaddresssomeofthe mostpressingissuesintheSupplementary Materialonlinesuchashowthefundwould bemanaged,whethertheparameterswehave assumedarerealisticandhowexisting bond-holdersmightreacttoincreasesinleverage. Severalotherrecentstudiesoffermore-detailed analysisofthesechallengesandhowtheycanbe addressed[8–13].
Themainfindingofourstudyisthatafund incorporatingdynamicleveragerequiresless upfrontequitytofinancethedevelopmentof thecompoundsintheportfoliothanprevious implementations,andgenerateshigher returns withsimilar risksofdefaultand loss. Furthermore, thevolatilityofequityreturnsis lowercomparedwithamegafundstructure withastaticcapitalstructure.Borrowingmore debtovertime doesnotadverselyaffect the scientificoutcomebecause,inthedynamically leveraged approach,theadditionaldebtis onlyneedediftheportfolioisonitsexpected path.
Dynamicleveragemagnifiespositiveand negativeperformance.Iftheactualperformance oftheportfolioofprojectsisbetterthan indi-catedbypriorassumptions,thenthefundwith dynamicleveragewilloutperforman equity-financedportfolio.Iftheportfolio underper-forms,however,thentheequity-fundedportfolio willperformbetter.Thisresultisexpected,given thenatureofleverage.Thehighervolatility(risk) ofequityreturnsinamegafundwithdynamic leverage,ascomparedwithan all-equity-fi-nancedportfolio,isaccompaniedbyahigher expectedequityreturn.Nevertheless,iffurther securitizationtechnologiesareintroduced intothepharmaceuticalportfoliostructure weexpectcommensurateimprovementsto equityreturns.
Acknowledgments
ResearchsupportfromtheMITLaboratoryfor FinancialEngineeringisgratefully
acknowledged.WethankJaynaCummings,Alex Danehy,MichaelEisensteinandAndrew Goldsmithformanyhelpfulcommentsand discussion.Theviewsandopinionsexpressedin thisarticlearethoseoftheauthorsonly,anddo notnecessarilyrepresenttheviewsandopinions ofanyinstitutionoragency,anyoftheiraffiliates oremployeesoranyoftheindividuals acknowledgedabove.
AppendixA. Supplementarydata
Supplementarymaterialrelatedtothisarticle canbefound,intheonlineversion,athttp://dx. doi.org/10.1016/j.drudis.2015.12.004.
References
1 Thomas,D.andWessel,C.(2015)Venturefundingof therapeuticinnovation:acomprehensivelookata decadeofventurefundingofdrugR&D.Biotechnology IndustryOrganization
2 Moses,H.,Matheson,D.,Cairns-Smith,S.,George,B., Palisch,C.andDorsey,E.(2015)Theanatomyofmedical research:USandinternationalcomparisons.JAMA313, 174–189
3 Booth,B.(2015)Theventurefundingboominbiotech:a fewthingsit’snot.Availableat:http://www.forbes.com/ sites/brucebooth/2015/07/23/the-venture-funding-boom-in-biotech-a-few-things-its-not/
4 Huggett,B.(2015)Biotech’swellspring–asurveyofthe healthoftheprivatesectorin2014.Nat.Biotechnol.33, 470–477
5 Fernandez,J.-M.,Stein,R.M.andLo,A.W.(2012) Commercializingbiomedicalresearchthrough securitizationtechniques.Nat.Biotechnol.30,964–975
6 Moody’sInvestorsService(2014)Ratingmethodology: Moody’sglobalapproachtoratingcollateralizedloan obligations.
7 Fagnan,D.E.,Gromatzky,A.A.,Stein,R.M.,Fernandez, J.-M.andLo,A.W.(2014)Financingdrugdiscoveryfor orphandiseases.DrugDiscov.Today19,533–538
8 Fagnan,D.E.,Fernandez,J.-M.,Lo,A.W.andStein,R.M. (2013)Canfinancialengineeringcurecancer?Am.Econ. Rev.103,406–411
9 Fagnan,D.E.,Yang,N.N.,McKew,J.C.andLo,A.W. (2015)Financingtranslation:analysisoftheNCATS rare-diseasesportfolio.Sci.Transl.Med.7,276ps3
10Lo,A.W.andNaraharisetti,S.V.(2014)Newfinancing methodsinthebiopharmaindustry:acasestudyof RoyaltyPharma,Inc..J.Invest.Manag.12,3–19
11 Forman,S.,Lo,A.,Shilling,M.andSweeney,G.(2015) Fundingtranslationalmedicineviapublicmarkets:the businessdevelopmentcompany.J.Invest.Manag.13,1–24
12David,F.,Bobulsky,S.,Schulz,K.andPatel,N.(2015) Creatingvaluewithfinanciallyadaptiveclinicaltrials. Nat.Rev.DrugDiscov.14,523–524
13Schulz,K.,Bobulsky,S.,David,F.,Patel,N.and Antonijevic,Z.(2015)Drugdevelopmentandthecost ofcapital.InOptimizationofPharmaceuticalR&D ProgramsandPortfolios:DesignandInvestmentStrategy (Antonijevic,Z.,ed.),pp.35–48,Springer,NewYork
VahidMontazerhodjat1,2 JohnJ.Frishkopf3 AndrewW.Lo1,2,4,5,* 1
MITLaboratoryforFinancialEngineering,Sloan SchoolofManagement,Cambridge,MA,USA
2
MIT Department of Electrical Engineering and ComputerScience,Cambridge,MA,USA
3NewStarFinancial,Inc.,Boston,MA,USA 4
MITComputerScienceandArtificialIntelligence Laboratory,Cambridge,MA,USA
5AlphaSimplexGroupLLC,Cambridge,MA,USA
*Correspondingauthor.
Features
PERSPECTI
