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1、RewiR&DMaking more medicines that matterJanuary 2025RewiR&D:Making more medicines that matter is published by McKinseys Life Sciences Practice.McKinsey&Company1200 19th Street NWFl.10-11,Suite 1100Washington,DC 20036Editors:Jermey Matthews,Mark Staples,Gwyn HerbeinArt director:LEFFCommunications:Sha

2、nnon Ensor,Emily M.KiernanProject management:Wendy ZhangLead reach and engagement partner:Gregory GravesThis publication is not intended to be used as the basis for trading in the shares of any company or for undertaking any other complex or significant financial transaction without consulting appro

3、priate professional advisers.No part of this publication may be copied or redistributed in any form without the prior written consent of McKinsey&Company.Copyright 2025 McKinsey&Company.All rights reserved.ContentsMaking more medicines that matterProductivity in biopharmaceutical R&D has slumped for

4、 a decade or more.We propose a recipe for sustainable,value-creating innovation,even in the face of strengthening industry headwinds.Charting the path to patientsCareful development of asset strategy across the pharmaceutical R&D pipeline is increasingly important in embracing opportunities for inno

5、vation.How biopharmaceutical leaders optimize their portfolio strategiesLeading biopharmaceutical companies manage their clinical pipelines to optimize for risk and reward.Heres how.Strengthening the R&D operating model for pharmaceutical companiesRevisiting the operating model could help pharmaceut

6、ical companies improve R&D productivity.Accelerating clinical trials to improve biopharma R&D productivityBiopharma sponsors are seeking to accelerate clinical trials and reduce costs through a set of targeted actions aimed at improving patient and site engagement and enrollment productivity.Operati

7、onal excellence in biopharma research and early developmentLeading companies are revamping research and early development to curb lengthy drug development timelines and rising costs.7295317394712354MAKING MORE MEDICINES THAT MATTERCHARTING THE PATH TO PATIENTSPICKING WINNING MEDICINESSTRENGTHENING T

8、HE BACKBONEWORKING SIMPLY AND SMARTLYContents(continued)External innovation:Biopharma dealmaking to boost R&D productivityTop-performing pharma companies over the past decade have relied on a short list of critical dealmaking behaviors that drive high external innovation productivity.How artificial

9、intelligence can power clinical developmentArtificial intelligence is accelerating drug discovery.If clinical development fails to keep pace,the benefits to patients will be delayed.Boosting biopharma R&D performance with a next-generation technology stackA modern,well-designed tech stack can unlock

10、 the potential of AI,automation,and data and their promised benefits to R&D productivity.Unlocking peak operational performance in clinical development with artificial intelligenceThree lighthouse use cases serve as a blueprint for AIs potential to improve the speed,efficiency,and quality of clinica

11、l trials.Putting people at the center of the R&D talent model in life sciencesRapid advancements in science and technology are challenging pharma and biotech companies approaches to talent.What R&D skills do they need today,and how can they sustain this workforce?Building a shared vision for pharma

12、R&Dsupplier partnershipsPharma R&D leaders and their suppliers see transparency as a key to unlocking more effective collaborations and cost efficiencies.5890667583996789INNOVATING WITH THE EXTERNAL ECOSYSTEMBRINGING THE FUTURE FORWARDPUTTING PEOPLE AT THE CENTERPARTNERING FOR JOINT SUCCESSThank you

13、 to the following authors and contributorsIan LyonsJacob KautzkyJan GnthnerJay ParkJeff SmithJeffrey AlgazyJeffrey LewisJennifer HouJoachim BleysJocelyn YipJon BoorsteinJosh AlbrechtJulia QuachJulius SeitterKatarzyna SmietanaKetan KumarKevin WebsterLeigh JansenLeo PottersLieven Van der VekenLing Liu

14、Lionel JinLotte Berghauser PontLucas RobkeLucia DarinoLucy PrezMarina ShirobokovaMarion BossyMatthew WilsonMeredith LangstaffMichael LoeblMichael SteinmannMichelle SuhendraMiho SakumaMoritz WolfNavraj NagraAdam KneppAhsan SaeedAlana HorowitzAlberto LocheAlex DeveresonAlexandra ZempAmelia ChangAmy Si

15、lversteinAnas El TurabiAngelika StankiewiczAnirudh Roy PopliAnna ByziaAnton MihicAshley Van HeterenBart Van de VyverBettina OlsausenBrandon ParryCaroline LoyChaitanya Adabala ViswaChris AnagnostopoulosDaniel von BornstdtDavid ChampagneDominika SwiebodaEmily CapraEmily WingroveEoin LeydonErika Stanzl

16、Eva Lopez VidalFangning ZhangFrancesco PaganiGaurav AgrawalGuang YangGulia FerrettiHann YewHarriet KeaneHeikki TarkkilaPari RanjanPeter PfeifferPiotr PilarskiRachel MossRajesh ParekhRalf RaschkeRoerich BansalRosa PoetesSaurabh GoyalSean RyanSebastian KlugerStephan WurzerSteven AronowitzSvenja Steinb

17、achThomas DevenynsValentina SartoriVanessa LandtwingYevgen KanaloshYi ShaoA note from the authorsInnovation in the biopharmaceutical industry has reached a pivotal moment.Despite remarkable scientific breakthroughs and the unwavering commitment of so many in the industry to patients across the globe

18、,R&D productivity has remained stubbornly flat for more than two decades.The numbers tell a sobering story:development timelines average ten years from Phase I to launch,success rates hover at just 13 percent,and costs per successful new molecular entity have climbed to$4 billionup significantly fro

19、m$2.5 billion in 2016.The opportunityand the obligationto change the current trajectory is perhaps greater than ever.We are witnessing an incredible expansion of the therapeutic frontier,with bold investments(more than 30 percent annual growth)in innovative modalities allowing R&D organizations to a

20、ddress diseases in new ways.Emerging technologies,particularly artificial intelligence,promise to reshape drug discovery and development in ways we are only beginning to understand.And alongside government and public health organizations,the industry continues to commit enormous capital to funding b

21、reakthrough innovations.Making measurable change is difficult but achievable.Companies face increasing pressure to deliver diverse programs and support R&D teams working on novel platforms while also striving to differentiate themselves.To make progress and improve outcomes,pharma leaders need to em

22、brace three shifts:1.Disruptive innovation.Companies must adopt a mindset that prioritizes disruptive change over incremental evolution.2.Urgent action.If R&D leaders treat every day as critical,we have seen that companies can effectively cut the ten-year drug development cycle in half.3.Systematic

23、execution.Companies need a comprehensive strategy that leaves no stone unturned.A piecemeal approach often creates new bottlenecks,especially when applied to a system as complex as pharma R&D.Indeed,a fundamental rewiring of R&D is required for the industry to reach its full potential to deliver eve

24、n more lifesaving therapies for a wide range of medical needs while ensuring sustainable returns on significant investments.To that end,this compendium offers a blueprint for success.RewiR&D:Making more medicines that matter builds on McKinseys extensive research,including our practices contribution

25、s to more than 200 R&D transformations,many of them technology-driven.It features a comprehensive approachan R&D productivity recipethat captures many of the critical targets companies need to hit,including enriching the volume and quality of the asset pipeline,increasing success rates,and shrinking

26、 development costs and timelines for new drugs.We hope this compendium proves both inspiring and practical.Indeed,many have already embraced similar approaches to successfully navigate their own R&D transformations.The challenge is real,but the time for radical change is now.The future of the indust

27、ryand its ability to truly transform patients livesdepends on it.Sincerely,Brandon ParryWashington,DCErika StanzlZurichJeffrey AlgazyNewarkLieven Van der VekenLyon6Making more medicines that matter Productivity in biopharmaceutical R&D has slumped for a decade or more.We propose a recipe for sustain

28、able,value-creating innovation,even in the face of strengthening industry headwinds.1Making more medicines that matter77Making more medicines that matterMaking more medicines that matterProductivity in biopharmaceutical R&D has slumped for a decade or more.We propose a recipe for sustainable,value-c

29、reating innovation,even in the face of strengthening industry headwinds.by Brandon Parry and Rachel Mosswith Katarzyna Smietana and Michelle SuhendraThe global biopharmaceutical industry is coming to grips with an uncomfortable reality:after adjusting for the one-off returns generated by COVID-19 va

30、ccines and therapeutics,R&D productivity has been anemic over the past decade,barely recouping the full value of capital invested.This has been the case whether its pipeline attrition rates,development timelines,or the costs of clinical trials.And productivity is well below what it was during the gl

31、ory days of the late 1990s.Of course,there have been bright spots,but the industry has largely failed to make systemic gains(Exhibit 1).Indeed,a more granular look at the underlying factors of R&D performance reveals the main culprits of this trend:slumping probabilities of success in clinical trial

32、s and rising costs of bringing new molecular entities(NMEs)to market(see sidebar,“The R&D productivity equation:Underlying factors of R&D performance”).Moreover,in our analysis of the top 15 companies in the industry,there does not seem to be a strong correlation between R&D spend and NME value crea

33、tion(Exhibit 2).Instead,we see that their R&D performance has largely been propelled by“blockbuster”medicines(NMEs that achieve over$1 billion in peak-year sales);these assets have buttressed overall productivity in the past decade(Exhibit 3).Stagnant productivity is not a new problem,but it increas

34、ingly feels entrenched.The outlook for reimbursement erodes in major markets(especially in the United States as the Inflation Reduction Act takes effect),the impact of patent expirations for major franchises is expected to be significant(propelled by increasing biosimilar penetration),and pipeline c

35、ompetition intensifies(with increasing herding in high-potential disease areas and targets1).To be sure,R&D productivity is only one way to measure biopharma success,and other measures are much more encouraging.From a shareholder perspective,biopharma has achieved admirable returns(roughly 9 percent

36、 on an annualized basis over the past decade).From a scientific perspective,the frontier of possibilities opened by novel modalities(today,22 percent of the industrys clinical pipeline is novel therapeutics)and the vast powers of AI are nothing short of breathtaking.And whats most important,from a p

37、atients perspective,is the industry has provided numerous life-altering therapies across a wide range of diseases.1 Christian Fougner et al.,“Herding in the drug development pipeline,”Nature Reviews Drug Discovery,April 2023,Volume 22,Number 8.8Making more medicines that matterA recipe for boosting

38、R&D performanceBut productivity still matters.Over the past year,we have spoken with hundreds of R&D leaders who are determined to build on this innovation potential,crack the R&D productivity conundrum,and provide still more medicines that matter to patients.Based on those dialogues and our experie

39、nce,we propose in this article a“recipe”of eight essential ingredients for sustained R&D success(Exhibit 4):1.charting the path to patients:effective asset and program strategies2.picking winning medicines:investor-like portfolio strategy optimized for risk and reward3.working simply and smartly:sim

40、plified,automated,and digitized core processes4.strengthening the backbone:enabling the R&D system(decision making,footprint,and organization)5.innovating with the external ecosystem:skills to identify and secure external assets6.bringing the future forward:next-generation data,analytics,and technol

41、ogy7.putting people at the center:a distinctive talent model8.partnering for joint success:streamlined vendor partnershipsNone of these ingredients are surprising on their own;however,weve observed that meaningful productivity and performance gains can be achieved Exhibit 1ROI vintage index for“new

42、molecular entity”launches1New molecular entitygrade products,excluding generics,biosimilars,and NDA products(ie,new derivatives,reformulations,etc);launch year based on the global market entry and frst reported/expected revenues;3-year rolling average(2-year rolling average used for 2022).Inflation

43、adjusted to 2022 US$for 19862020 long-term average value(2.6%);for 202122 actual values;and for 202328 average based on last 5 years(3.2%).“COVID-19 contribution”visible in 2019 is a result of using 3-year rolling average(which smoothens the chart and thus enables best long-term trend visibility).Th

44、e 7-year frame is used as a proxy for overall drug potential because most prelaunch,asset-specifc R&D spend can be captured within that time frame,and revenues within the frst 7 years are typically a good proxy for an assets overall potential.(However,this only accounts for initial indication expans

45、ion;hence,for some assets,the potential might be underestimated.)COVID-19 assets show very diferent revenue distribution(almost all revenue realized within 2 years);we consider the observed productivity uptick an artifact and have excluded those assets to give a more realistic view of the long-term

46、trend.Source:EvaluatePharma,Dec 2022;PhRMA;US Bureau of Labor Statistics,2023;McKinsey analysis Apart from COVID-19 therapies,the recent uptick in the pace and volume of drug development has led to only modest gains in R&D productivity.McKinsey&Company 020001993201020200.51.01.52.02.53.03.5R&D produ

47、ctivityAdditionalCOVID-19contributionThe ROI vintage index measures the return on investment for drugs launched in a specifc year.It calculates 7 years of postlaunch revenue(using a 3-year rolling average)divided by the R&D spending from the preceding 7 yearsattributed to that“vintage”of launches.9M

48、aking more medicines that matterwhen they are tackled together,at scale,and at pace.Detailing this recipe and how to apply it to outperform is the focus of our ongoing research on biopharma R&D.In upcoming publications,we will explore each of these ingredients in detail and describe the practices th

49、at distinguish industry leaders from laggards.For now,we offer this article as a high-level concept note that sets out what we believe are the eight essentials of successful,value-creating R&D,based on our research and discussions.Effective asset and program strategiesCompanies are gradually shaping

50、 a value-maximizing asset strategy(often starting as early as candidate selection)that fully explores line extensions and indication expansions to generate a future blockbuster drug.This requires actors to take on significant investment risk earlier,as they pursue parallel,pivotal,and enabling clini

51、cal programs to explore the full potential of an asset.This,in turn,is inducing companies to include insights powered by AI and machine learning(AI/ML)(for example,those informed by in silico disease and safety models)in decision making to derisk such investments.Investor-like portfolio strategy opt

52、imized for risk and rewardPractically speaking,a“blockbuster seeking”portfolio strategy directs 80 percent or more of R&D investment to a subset of assets that have the potential to yield at least$3 billion in peak-year sales(it costs as much to develop a single successful Exhibit 2Performance of bl

53、ockbuster assets in top 15 companies,proportion of assets with$1 billion in peak sales value in total portfolio,%Note:R&D spend calculation does not include BD&L(business development and licensing)expenditures;hence,prolifc dealmakers may appear as more productive.1Sum of peak sales for new molecula

54、r entities(NMEs)launched 201822 with minimum annual revenues of$100 million(any year in visible forecast data).NMEs include novel biologics.Partnered launches can be assigned to multiple companies if their revenues attributable to a company exceed$100 million,excluding COVID-19 vaccines and therapeu

55、tics.Total annual pharmaceutical R&D spend from 2018 to 2022(device and generics R&D spend excluded whenever reported separately).Pre-acquisition R&D spend for mega-merged entities(M&A of$10 billion)is included to account for NME pipeline continuity.Source:EvaluatePharma(analysis as of Feb 2024);PhR

56、MA,2020 In recent years,newly launched blockbuster drugs have propelled value creation more than total R&D spending alone.McKinsey&Company0605040302010Total R&D spending,201822,$billionTotal value,201822,$billion03020105352515Blockbusters in portfolio,number90%5090%50%6 3 1AveragevalueAverageR&D spe

57、nd10Making more medicines that matterNME2)and uses the companys distinctive R&D capabilities(for example,in disease biology understanding,relevant modalities,development expertise,or market knowledge and relationships).Shaping such a portfolio requires leadership teams to make investor-like trade-of

58、fs on a“live”basis(versus the classic annual review),informed by internal and external data(real-world evidence and randomized clinical trial data sets)readouts,regulatory guidance,and competitive developments and enabled by scenario-based simulations (such as efficient frontier modeling).Simplified

59、,automated,and digitized core processesProcess simplification,and automation,along the critical path has gradually come into focus in recent years as the industry races to get medicines to patients faster.Examples of value chain steps where we have observed material accelerations include preclinical

60、 candidate nomination to the first subject in(in which we have seen accelerations from 21 to 26 months to 12 to 15 months following optimization),enrollment(20 percent acceleration observed),and submissions(in which actors are increasingly delivering less than eight weeks from database lock to submi

61、ssion).Achieving these accelerations requires both embedding novel automation and technological solutions and absolute operational clarity on the critical pathand the accountabilities for each process step(often across functional silos)to sustainably boost performance.Enabling the R&D system(decisio

62、n making,footprint,and organization)Operating models are evolving rapidly to provide fewer high-value assets,which will require higher-risk investment decisions early in the life Exhibit 3Share of R&Dproductivity byproduct class,%Revenue generated by new molecular entities over the frst 7 years.Bloc

63、kbusters defned as products with peak sales between$1 billion and$5 billion;mega blockbusters defned as products with peak sales above$5 billion.Source:EvaluatePharma,2022In recent years,biopharma R&D productivity has become more persistently reliant on blockbuster and mega blockbuster drugs.McKinse

64、y&Company2004200412average201322average201320220102030405060708090100Mega blockbustersBlockbustersNonblockbusters2640665130812 Joseph A.DiMasi et al.,“Innovation in the pharmaceutical industry:New estimates of R&D costs,”Journal of Health Economics,May 2016,Volume 47.11Making more medicines that mat

65、tercycle.Specifically,three important investment decisions are increasingly in focus:(1)early alignment on the“minimum viable”target product profile for an asset,(2)commitment to the end-to-end asset strategy(and“path to patient,”including staging of clinical activities),and(3)prioritization of the

66、portfolio.Each of them requires absolute clarity on decision rights,as well as the insights(which,more and more often,are analytically powered)to inform the decision and the pace at which it should be made(to minimize periods of indecision).These shifts in decision rights are reshaping organizationa

67、l designs,role profiles,and capability investments to ensure that decisions are informed by the right insights to maximize asset value and that the right level of talent is engaging at the right time.Skills to identify and secure external assetsAs the competition for externally sourced future-blockb

68、uster assets intensifies across the industry,with the value of the top ten M&A deals in biopharma in 2023 surpassing those of the previous three years,3 R&D functions are playing an increasingly critical role in these portfolio-shaping transactions.R&D,for example,is closely collaborating with busin

69、ess development to apply AI/ML techniques for identifying promising NME candidates aligned with its disease area and modality priorities.Additionally,these functions are developing comprehensive plans for asset strategy and evidence generation to become the“partner of choice.”And once a transaction

70、has closed,they move quickly to build and scale new capabilities or investigator relationships to maximize the potential of particularly late-stage transactions,which require significant cross-functional agility and investment.Beyond this transaction-focused approach,companies are shaping their exte

71、rnal ecosystems to secure preferential access to the latest early-stage,differentiated,and emerging scientific substrates,as well as a broad range of mechanisms,including incubators,venture capitallike corporate funds,capability sharing,and scientific community networks.Next-generation data,analytic

72、s,and technologyThe disruptive potential for data,analytics,and technology to unlock R&D productivity is clear;however,we have not yet observed actors that fully realize this potential across the end-to-end R&D value chain.There are foundational opportunities for applying automation(including genera

73、tive AI)to core business processes,such as protocol writing,project and site management,data management,and content authoring.Such uses can accelerate activities,limit operational variation,and reduce costs.As these new technologies are embedded,they could be integrated into a unified data platform

74、with access to internal and external data sets to enable predictive analytics that can unlock further productivity gains.Examples include but are 3 Eric Sagonowsky et al.,“The top 10 biopharma deals of 2023,”Fierce Pharma,February 5,2024.Companies are shaping their external ecosystems to secure pref

75、erential access to the latest early-stage,differentiated,and emerging scientific substrates.12Making more medicines that matternot limited to predictive target identification(using knowledge graphs of multiomics,randomized control trials,and real-world evidence data),lead design simulations,in silic

76、o preclinical models,and trial design simulators.Ultimately,the goal of applying such analytics is to create learning loops whereby experimental data is fed back to power improved analytical design;that,in turn,can propel improvements in success rates and cycle time acceleration.We have observed,for

77、 instance,companies creating such learning loops when moving molecules from lead identification to investigational-new-drug submission nine months faster,while also improving probability of successspecifically a fourfold improvement in leading indicators.A distinctive talent modelThe battle for capa

78、bilities and talent is intensifying as actors herd in blockbuster-yielding disease areas and focus on achieving R&D productivity improvements.This is causing a return to strategic workforce planning focused on both reimagined“old skills”(such as those possessed by bench scientists,asset team leaders

79、 for priority assets,clinical scientists,biostatisticians,regulatory strategists,and innovation scouts)and“new skills”(such as those possessed by new platform technology experts,experts in areas like cell and gene therapy,AI/ML-capable data scientists,and performance transformation leads).Talent tra

80、nsformations may involve upgrading the talent base by replacing those who work on deprioritized diseases and technologies and upgrading associated automated activities with best-in-industry models suitable for the current priorities.New hires can be offered attractive career paths beyond their start

81、ing roles.Any remaining talent gaps can be closed through partnerships(particularly for AI/ML capabilities),with a clear path to embed these capabilities internally.Exhibit 4Enablingcharacteristics8 ingredients for sustained R&D outperformingA comprehensive approach to biopharma R&D transformation c

82、ould boost R&D productivity and propel sustained outperforming.McKinsey&Company2 Investor-like portfoliostrategy optimized for risk and reward1 Efectiveasset andprogramstrategies3 Simplifed,automated,and digitized coreprocesses4 Enabling the R&D system(decision making,footprint,and organization)5 Sk

83、illsto identifyand secure external assets6 Next-generation data,analyt-ics,and tech-nology Applying the recipe in practice:infrastructure and organizational“muscle”to continually scale performance improvements7 Adistinctive talentmodel8 Stream-linedvendorpartnershipsClear R&D investment thesisHigh-p

84、erformanceR&D delivery engine13Making more medicines that matterThe R&D productivity equation is a framework developed to assess the key factors that lead to higher,or lower,R&D performance.It features five factors of R&D efficiency and effectiveness(Exhibit A):1.Volume.Assessed based on the number

85、of new molecular entities(NMEs)launched,the number of investigational new drugs(INDs)in the pipeline,and the number of indication expansions.2.Probability of success.Measured by the probability of a drug candidate successfully progressing all the way from Phase I to approval.3.Value.Determined by me

86、trics such as peak sales per NME,the percentage of assets that are first in class,and total pipeline value.4.Speed.Measured by the average time to launch for new drugs and by phase of development.5.Cost.Assessed using metrics such as R&D spend as a percentage of revenue and R&D spend per asset.The R

87、&D productivity equation:Underlying factors of R&D performanceExhibit AR&D productivity trends from 2019 to 2023:5 essential factors of efciency and efectiveness1Extrapolated based on reported change in cost per NME from 2016 to 2022.Total NME development cost divided by average time from developmen

88、t to launch per NME.Source:Pharmaprojects,Nov 2023;EvaluatePharma,2023;McKinsey analysisIncreased clinical development has boosted industry R&D productivity,but low clinical trial rates and rising development costs have dulled this efect.McKinsey&CompanyPositive60%growth inoverall Phase I volume20%m

89、ore indications per new molecular entity(NME)20%decrease insuccess rate during clinical trials from Phase I to approvalStable averageUS peak salesper asset10%shorterclinical development40%increase in annual cost per NME per year=R&DproductivityVolumeProbabilityof successValueSpeedCostNegativeNeutral

90、The battle for capabilities and talent is causing a return to strategic workforce planning focused on both reimagined old skills and new skills.14Making more medicines that matterExhibit BWeb Exhibit of 1New molecular entitygrade products,excluding generics,biosimilars,and NDA products(ie,new deriva

91、tives,reformulations,etc);launch year based on the global market entry and frst reported/expected revenues;3-year rolling average(2-year rolling average used for 2022).Probability of success:inflation adjusted to 2022 US$for 19862020 long-term average value(2.6%);for 202122 actual values;and for 202

92、328 average based on last 5 years(3.2%).Source:EvaluatePharma,Dec 2022;PhRMA;US Bureau of Labor Statistics,2023;McKinsey analysisThe R&D productivity equation can be used to identify a biopharma companys essential factors of underperformance relative to its peers.McKinsey&Company The 5 essential fac

93、tors of R&D productivity performance,201822(top 15 pharma companies)Average peak sales per NME launched,201822,$billionNME launched,201822,numberOverall from Phase I to launch,201022,%Time from Phase I to fling,201822,yearsAverage annual R&D spend per asset/phase,201822,$millionValueSpeedCost12345Vo

94、lumePOS0123456702468101200.040.080.120.160.200.24024681012020406080100Better than averageWorse than averageAverageDetermined by metrics such as peak sales per NME,the percent-age of assets that are frst in class,and total pipeline value.Assessed based on the number of NMEs launched,the number of inv

95、estigational new drugs in the pipe-line,and the number of indica-tion expansions.Measured by the average time to launch for new drugs,by phase of development.Assessed using metrics like R&D spend as a per-centage of revenue and R&D spend per asset.Measured by the probability of a drug candidate succ

96、essfully pro-gressing all the way from Phase I to approval.Benchmarking companies along these five factors provides a more granular comparison of historic R&D productivity and points to the specific ways certain companies have outperformed or can identify specific areas that need improvement.We benc

97、hmarked,for example,the top 15 industry actors to identify areas of performance improvements(Exhibit B).The R&D productivity equation:Underlying factors of R&D performance(continued)15Making more medicines that matterStreamlined vendor partnershipsPharmaceutical companies are increasingly reliant on

98、 vendors(which they share with their peers)to help them achieve their industry performance goals.Hence,its critical that companies redefine their relationships with these partners.Across the industry,as actors race to secure new technical capabilities and enter new disease areas,there is an increase

99、d focus on streamlining access to cost-effective,nondifferentiated capacity while simultaneously identifying“on demand”capabilities needed to scale;defragmenting across this vendor base accordingly;aligning incentives in contracting;developing joint working models;and applying technical solutions th

100、at allow both partners to outperform.Applying the recipe in practiceR&D engines are complex.Achieving a step change in performance while also growing a portfolio of potential blockbuster medicines requires a continuous transformation musclefew companies have it,but those that do are able to reap tan

101、gible,at-scale performance improvements.Like all sustained transformations,effective R&D performance transformations typically involve the following elements:detailed execution plan designed to achieve“full potential”performance improvement(informed by benchmarks or use cases where possible)aligned

102、metrics that indicate near-term impact(versus progress);delivery of initiatives(“quarterly value releases”)dedicated initiative-scaling engine to ensure test cases(for example,at the asset level)are adopted across R&D as soon as value is demonstrated focused change management efforts to enable the r

103、equired behavioral shifts,cascading communications,objective setting and rewards,and leadership role modelingPharma companies across the industry are beginning to make significant investment shifts in response to mounting external pressures.Pipelines are being refocused,material capability investmen

104、ts are being made,and new partnerships are being forgedall to enable a gear change in R&D engine performance.There is excitement across the industry that,against this backdrop,the decades-old problem of R&D productivity may finally be cracked and a growing recognition that those that fail to tackle

105、this head-on may soon be left behind.Copyright 2024 McKinsey&Company.All rights reserved.Brandon Parry is a senior partner in McKinseys Washington,DC,office;Rachel Moss is a partner in the London office;Katarzyna Smietana is an associate partner in the Wroclaw office;and Michelle Suhendra is a consu

106、ltant in the Lisbon office.The authors wish to thank Angelika Stankiewicz,Anna Byzia,Caroline Loy,Erika Stanzl,Jeffrey Algazy,Lieven Van der Veken,Marion Bossy,and Roerich Bansal for their contributions to this article.16Charting the path to patients Careful development of asset strategy across the

107、pharmaceutical R&D pipeline is increasingly important in embracing opportunities for innovation.2Charting the path to patients1717Charting the path to patientsCharting the path to patientsCareful development of asset strategy across the pharmaceutical R&D pipeline is increasingly important in embrac

108、ing opportunities for innovation.This article is a collaborative effort by Guang Yang,Jeff Smith,Lucy Prez,and Valentina Sartori,with Amelia Chang and Ling Liu,representing views from McKinseys Life Sciences Practice.Life sciences is on the cusp of a new era of innovation.The convergence of breakthr

109、ough technologies,widespread access to data,and deeper insights into complex biological systems is revolutionizing how the industry approaches R&D.For instance,venture capital funding for machine-learning-enabled drug discovery surged more than sevenfold from 2019 to 2022,according to McKinsey analy

110、sis.Interest in innovative modalities such as antibodydrug conjugates(ADCs)remains strong,with the top three ADCs expected to bring in$17 billion in global revenue by 2028,and eight of the top ten pharmaceutical companies completing at least one ADC-related acquisition or licensing deal in the past

111、two years.Yet in this time of rapid transformation and excitement,pressure on the industry continues to rise.For example,R&D pipelines are increasingly crowded,with intensifying competition shortening asset life cycles and compressing time between launches.Remaining competitive will require industry

112、 leaders to adopt approaches to optimizing R&D asset strategy.Our analysis of 100 top assetsthose with the highest lifetime actual and forecast sales worldwide from 2014 to 2030identified critical areas to address,including indication breadth and parallelization,trial endpoints,and global trial foot

113、print.An increasingly challenging environmentThere is high pressure on biopharmaceutical companies to drive relentless asset development.We see three primary challenges.Crowded R&D pipelinesThe global industry pipeline has grown significantly:across all therapeutic areas,clinical trial volume increa

114、sed by 4 percent annually from 2020 to 2024,with the number of compounds in active development doubling in the past decade,according to McKinsey analysis.This surge in activity is intensifying competition and shortening the interval between launches.For instance,the launch gap for the top three onco

115、logy targets(HER2,CD20,and BCR-ABL)has shrunk from 6.3 years between first and second launches to 2.4 years between second and third launches;this drops to 1.4 years by fifth launch.1These shorter launch intervals are linked to asset herding,in which multiple companies pursue the same targets.2 In t

116、he past 20 years,the number of assets per target has increased by more than 2.5 times,with oncology leading the trend.In 2000,only 16 percent of top ten pharma pipelines were herded targets(defined as more than five assets pursuing 1 McKinsey analysis of data from ClinicalTrials.gov.2 For more detai

117、ls,see Christian Fougner et al.,“Herding in the drug development pipeline,”Nature Reviews Drug Discovery,April 2023,Volume 22.18Charting the path to patientsthe same target);by 2020,this had risen to 68 percent(Exhibit 1).Compressed asset life cyclesRising competitive intensity and accelerated devel

118、opment timelines are steadily shortening asset life cycles,reducing both the time available in which to capture value and the overall value that can be captured from an asset.This life cycle compressionexacerbated by rapidly evolving clinical practice and growing biosimilar adoptionhas shortened the

119、 time to reach 50 percent of lifetime sales by more than two years in the past two decades.3 Value capture is further constrained by pricing reforms,cost-containment measures,and a shift toward value-based pricing and reimbursement.This is exemplified by the Inflation Reduction Act(IRA),which sets a

120、“maximum fair price”for drugs with the highest Medicare spending and gives small-molecule drugs nine years of protection from price negotiation and biologics 13 years.Given that small-molecule drugs capture 51 percent of lifetime revenue after the protected window and biologics 29 percent,the IRAs e

121、ffect on revenue trajectories may reduce follow-on investments and influence portfolio decisions,pressuring companies to capture value within ever-tighter time frames.4 Increasing cost pressuresDrug development is becoming more expensive.R&D spending accounts for an average of 20 percent of biopharm

122、a revenue and has continued to rise,reaching$260 billion in 2023.5 But this increase in spending has not translated to an increase in efficacy.Time to launch remains lengthy,averaging ten years from Phase I to launch,while cost per launch has grown by 8 percent annually,reaching$4 billion in 2022.6

123、Cost drivers include rising trial complexity(due to a shift toward complex modalities and other factors)and decline in enrollment productivity,especially in pivotal Phase III trials.Escalating costs and inefficiencies highlight the need for innovative approaches to improve returns on R&D investment.

124、Three winning strategies for market success Across the industry,we have observed a wide range of tactics to optimize asset outcome at both the indication(above-trial)and trial level across study design,conduct,closeout,and post-approval phases(Exhibit 2).Our examination of the top 100 assets in all

125、therapeutic areas identified three areas of strategic focus.Expanding indication breadth and parallelization Strategic indication expansion is emerging as a key differentiator,with a clear trend toward more aggressive pursuit of greater indication breadth and parallelization as an asset strategy by

126、top biopharma companies.For example,for two of the most crowded and successful drug classesanti-VEGF therapies 3 For more details,see Greg Graves,Rajesh Parekh,and Brian Tanner,“Redesigning for speed:Addressing life cycle compression in biopharma,”McKinsey,March 14,2024.4 John Stanford,“The IRA is a

127、lready curtailing small molecule drug development.Heres how to reverse that,”BioSpace,April 9,2024.5 Evaluate Pharma;PharmaProjects.6 McKinsey analysis based on data from PharmaProjects and Evaluate.We have observed a wide range of tactics to optimize asset outcome at both the indication and trial l

128、evel across various phases.19Charting the path to patientsExhibit 12000200220042006200820102012201420162018202020220246810AllOncologyNon-oncology5.4x2.5x1.5xIncrease,200022Average%pipeline for target pursued by 5 assets in top 10 pharma:16.0%20002020Average%pipeline for target pursued by 5 assets in

129、 top 10 pharma:64.5%811868497263342113813319702720445858785481628730647330Company 1Company 2Company 3Company 4Company 5Company 6Company 7Company 8Company 9Company 10All companiesin data set67178501717171438337269506769677361715311231731172722149Web 2024MCK240573 Path to PatientsExhibit 1 of 5Number

130、of assets per target over time,1 increase 200022Percentage of assets pursuing target across top biopharma pipelines,2 degree of asset herding3Note:Figures may not sum,because of rounding.1Methodology:Identifed all targets for which the frst approval for that target occurred after 1995 and for which

131、two or more drugs have been launched.For every year,assessed the number of drugs being actively investigated for those targets(Phase Iregistration)divided by the number of targets being actively investigated in that year.2Methodology:Identifed top 10 pharma companies in 2000 and 2020 based on public

132、ly available revenue data.Using PharmaProjects Trends data,we identifed targets within each companys pipeline and the number of drugs being actively investigated for those targets(Phase Iregistration).3Defned as 5 assets in development for target.Source:PharmaProjects Trends data,19952022Pharmaceuti

133、cal pipelines are increasingly chasing the same targets,pressuring clinical-trial enrollment and shrinking launch intervals.McKinsey&Company125520Charting the path to patientsand PD-1 inhibitors7our analysis showed the top 15 biopharma companies both initiate new trials in other indications more qui

134、ckly(within 12 months following the first pivotal trial)and proactively launch more trials relative to peers(Exhibit 3).Beyond these two asset classes,we broadened our analysis to the top 100 assets between 2014 and 2030 and assessed the number of indications initiated within five years of first-in-

135、human(FIH)clinical trials as a marker for early parallelization.Rapid indication expansion was a clear trend in both oncology and non-oncology assets,according to McKinsey analysis.Among anti-PD-1s,trials for Opdivo(FIH 2006)were initiated in six new indications within five years of FIH,followed by

136、Tecentriq(2011)and Imfinzi(2012)with trials in 14 and 18 new indications,respectively.Trials were initiated for Keytruda(FIH 2011),a standout example,in 38 indications within five years of FIH through successful basket trials.8 Among ADCs,Padcev(2014)initiated two indications,while Enhertu(2015)and

137、Datopotamab deruxtecan(2018)initiated 11 and 13 indications within five years of FIH,respectively.This“front-load and fail fast”strategy enables companies to rapidly identify the most promising indications to pursue and maximize revenue capture before factors such as competitor entry Exhibit 2Breadt

138、h of indication strategyeg,parallel processing,front-loading,targeting niche indication Depth of indication strategyeg,develop multiple lines of therapy in parallel External landscape eg,patent protection,Infation Reduction Act negotiation,industry partnershipsLife cycle management eg,line extension

139、s,patent strategies,new formulations Integrated evidence generationeg,registries to generate real world data,spontaneous reporting databases,record linkage,electronic health record monitoringPopulation eg,biomarker stratifcation,inclusion/exclusion criteriaTreatmenteg,mono vs combo therapy,prerandom

140、ization chemoComparatoreg,number of control arms,standard of care vs placebo,real-world-evidence control armsEndpoints eg,surrogate endpoints,composite endpoints,time of assessment Adaptive design eg,sample size reestimation,basket trials,rollover design Statistical analysis eg,Bayesian methods,Mont

141、e Carlo Site selectioneg,site tiering,global footprint,AI-driven site selectionSite activation eg,virtual clinical trial associate or assistant trainings,white-glove servicePatient recruitmenteg,digital recruitment strategies,patient databases,decentralized trials,community outreach Trial management

142、 eg,visualization dashboards,real-time performance monitoring External partnerships eg,clinical research organization vs in-house,comparator alliances,procurement strategies,clinical trial networks Dossier preparationeg,data-cleaning strategies,supported clinical study report generationChemistry,man

143、ufacturing,and controlseg,digital twin to optimize manufacturing,supply forecasting,formulation Regulatory strategy eg,FDA or European Medicines Agency expedited approval pathways,adaptive licensing,selective safety data collection,model-informed drug developmentMarket access/pricing strategyeg,risk

144、-sharing contract models,smart discount strategy Commercial strategyeg,TV ads,celebrity endorsementsMedical strategy eg,patient portal,patient advocacy group engage-ment,payer formulary Above trialStudy designStudy conductStudy closeoutand reportingOn marketWeb 2024MCK240573 Path to PatientsExhibit

145、2 of 5Three strategic levers stand out among the many available across the asset life cycle.McKinsey&Company7 Anti-VEGF(anti-vascular endothelial growth factor)therapies are used to treat eye conditions that cause abnormal blood vessel growth or retinal swelling(for example,macular degeneration),whi

146、le PD-1 inhibitors are used in cancer treatment.8 Basket trials test a drug across different diseases with the same mutations.21Charting the path to patientsand loss of exclusivity become pressing.Significant considerations accompany such parallelization,though,including higher risk,operational comp

147、lexities,and the need for substantial up-front capital and resource investment,factors that lead to differential prevalence of front-loading among biopharma companies.However,should resources permit,this approach can allow companies to establish leadership in competitive markets,especially those in

148、which they may have lost the first-mover advantage.What does the future hold?The industry is poised for even greater indication breadth and parallelization,especially given the challenges facing R&D today.In particular,the IRA has created a strong incentive to accelerate the development of multiple

149、indications before price controls take effect.Expansion of indication breadth and parallelization will be enabled by both strategic and operational advancements.On the strategic front,AI-enabled predictive analytics is revolutionizing the way companies identify and prioritize new indications.These a

150、dvanced tools allow for the early detection of promising therapeutic areas by analyzing vast data sets,including genomic information,real-world evidence,and patient outcomes.(For insight into the opportunity to continue making R&D more inclusive,see sidebar,“Understanding sex-based differences as a

151、catalyst for improved outcomes and growth.”)Exhibit 3012months1224months2436months92031433Top 15(6 assets)Nontop 15(4 assets)012months1224months2436months5710341Top 15(11 assets)Non-top 15(3 assets)Pivotal trial launch(per asset)Pivotal trial launch(per asset)Web 2024MCK240573 Path to PatientsExhibi

152、t 3 of 5Average additional trials launched following frst pivotal trial,number of new trials per yearAnti-VEGF therapies1PD-1 inhibitors2Note:Data excludes therapies in development by Chinese-headquartered biopharma companies;additional trials limited to industry-sponsored trials.1Anti-VEGF(anti-vas

153、cular endothelial growth factor)therapies included in analysis were pazopanib,sunitinib,infiximab,bevacizumab,sorafenib,regorafenib,cabozantinib,lenvatinib,ponatinib,ziv-afibercept,axitinib,tivozanib,ramucirumab,and vandetanib.2PD-1 inhibitors included in analysis were cemiplimab,cetrelimab,dostarli

154、mab,nivolumab,pembrolizumab,psb-205,retifanlimab,sasanlimab,tebotelimab,and zimberelimab.Source:McKinsey analysis of ClinicalTrials.gov dataLeading companies pursue aggressive indication expansion,which may be a source of competitive advantage.McKinsey&Company22Charting the path to patientsOperation

155、ally,improvements in trial design and execution are creating synergies that further enhance parallelization.Adaptive trial designs,for example,increase the likelihood of success across multiple indications by enabling modifications to ongoing trials based on interim results.Decentralized trials opti

156、mize resource allocation by enabling trials to be conducted more efficiently,as demonstrated by the global enrollment of tens of thousands of participants to support rapid COVID-19 vaccine development.Together,strategic and operational advancements are setting the stage for a new era in drug develop

157、ment,in which indication breadth and parallelization become cornerstones of successful asset strategy.Increasing the number of trial endpoints Recent years have seen an increase in the number of endpoints,which are the target outcomes of clinical trials.This approach allows biopharma companies to ma

158、ximize the value of each trial by gathering data on more metrics beyond primary therapeutic outcomes(for example,quality-of-life measures),but comes at the cost of greater site and patient burden.To quantify this trend,we averaged the number of secondary endpoints across Phase III trials for the 100

159、 top assets.9 Trials initiated between 2015 and 2024 had 12.1 secondary endpoints on average,25 percent more than trials initiated from 2005 to 2014(Exhibit 4).In general,oncology trials had the most endpoints,while endocrine and cardiovascular trials showed the broadest spread.A strategy of increas

160、ed data collection,when used judiciously,can provide a richer data set to support regulatory submissions,expand labeling options,facilitate broader market access,and ultimately encourage greater uptake among patients and healthcare providers.As an example,within GLP-1 agonists,10 early mover Trulici

161、ty had a median of 17.0 secondary endpoints across diabetes trials,while later entrant Cagrisema had 28.8 endpoints.The additional endpoints were tied to patient reported outcomes(PROs),which could help demonstrate differentiation over current on-market assets.Notably,one key trade-off with more end

162、points is a corresponding increase in protocol burden,which may have a detrimental impact on patient participation.Careful operational design and statistical planning are required to ensure that the trial remains manageable and the data can be meaningfully interpreted.What does the future hold?Novel

163、 classes of endpoints are emerging,especially as personalized medicine becomes more prevalent and precision therapies target patient subgroups.For instance,technologies enabling continuous patient monitoringsuch as wearable deviceswill support digital biomarkers as secondary endpoints.These will ena

164、ble monitoring of nuanced,continuous real-time changes in disease progression and treatment response that traditional endpoints might miss.The scope of secondary endpoints is also likely to expand because of increasing focus on PROs and real-world evidence.In oncology,for example,PROs feature heavil

165、y in assessing treatment impact on quality of life and daily functioning.These metrics may be critical differentiators in a crowded market and may be used The scope of secondary endpoints is also likely to expand because of increasing focus on patient-reported outcomes and real-world evidence.9 We f

166、ocused on secondary endpoints as companies typically have more flexibility to introduce additional secondary analyses that can affect the label(versus exploratory endpoints)but not jeopardize the registrational package(versus primary endpoints).10 GLP-1s(glucagon-like peptide-1s)are a class of medic

167、ation that help regulate blood sugar and support weight loss by mimicking a natural hormone in the body that controls appetite and insulin levels.23Charting the path to patientsPrecision medicine is typically referred to as the opportunity to identify specific mutations that allow pharma companies t

168、o differentiate subpopulations in larger patient groups.Sex as a biological variable is seldom considered,despite being the easiest and least costly biological variable to measure.The same goes for how differential outcomes can be achieved for women versus men.Yet there can be notable differences in

169、 treatment efficacy between women and men:for example,inhaler therapy is about 20 percentage points less effective in reducing asthma in women,1 while the age-adjusted risk of death or of cardiac events in women is 20 percent higher.2 Four main factors drive gaps between mens and womens health:Under

170、standing and investigation in science of sex-related differences in biology are limited.For example,women with childbearing potential were excluded from clinical trials from 1977 to 1993.Healthcare delivery is typically calibrated toward male physiology,so clinical practice guidelines and care proto

171、cols rarely account for sex-based differences such as specific protocols for diagnosis or discharge that account for womens different symptomatology.Often,data does not track sex,gender,or both;even when it does,the results arent necessarily used to drive decisions.There is significant underinvestme

172、nt in research on female-only conditions(just 1 percent of all pharma pipelines)and in female-specific manifestation of diseases(for example,the National Institutes of Health allocated just 7 percent of its 2019 budget for rheumatoid arthritis to studies focused on women,3 even though some 70 percen

173、t of rheumatoid arthritis patients are women).4An opportunity to act now The addressable market is clear:McKinsey analysis finds that 60 percent of revenue and 55 percent of Phase II and III assets of the top 20 pharma companies are focused on conditions that distinctly affect women.In addition,ther

174、e is novel scientific evidence on the role of the X chromosome in disease manifestations.Regulatory agencies have begun to issue guidelines for recruitment goals by sex and race,and the World Health Organization and other agencies are promoting the reporting of sex-disaggregated data.R&D organizatio

175、ns can play an important role in closing the womens health gap by consciously acting to consider sex at every step from early research to clinical development(and beyond),including how stage gates and other critical decisions(such as protocol approvals)are taken.Many known levers can be applied,incl

176、uding the following:Tailor overall R&D strategies based on the relative prevalence of women versus men for a certain condition,defining the value proposition for both.Develop preclinical models that reflect female biology,including accounting for differences in genetics and hormones.Understanding se

177、x-based differences as a catalyst for improved outcomes and growth Ensure that protocol design reflects relevant differential symptoms and endpoints for men versus women,include those with sex-specific impact such as hormonal changes,and strengthen trial recruitment and participation by removing bar

178、riers specific to women,such as use of more patient-centric inclusion criteria.Always look for opportunities to disaggregate and analyze data by sex to ask whether there are sex-based differences,and use those insights to inform R&D to create a virtuous loop for deeper understanding of conditions.Ac

179、hieving sex parity in clinical outcomes could lead to significant impact with better adherence,adoption,and efficacy:for example,McKinsey analysis suggests that about 35 percent more asthma patients could be positively affected,7 percent more in colorectal cancer,and 5 percent more in atrial fibrill

180、ation.In short,investing in approaches that recognize sex-based differences and deepen the understanding of conditions unique to women is not just the right thing to do but also a business opportunity,leading to higher R&D productivity through personalized medicine and better outcomes for a signific

181、ant proportion of patients globally.1 Kweilin Ellingrud,Lucy Prez,Anouk Petersen,and Valentina Sartori,Closing the womens health gap:A$1 trillion opportunity to improve lives and economies,McKinsey,January 2024.2 Ibid.3 The WHAM Report:The case to fund womens health research,WHAM,2021.4 “Rheumatoid

182、arthritis,”World Health Organization,June 28,2023.24Charting the path to patientsExhibit 49.712.12027191616571.41.22.11.81.03.42.3199419982002 2006201020142018202220242028HemlibraRybelsusWegovyCagrisemaDupixentVictozaVyndaqelEliquisPerjetaTagrissoIbrancePadcevImfnziTrulicityTaltzTremfyaOzempicOcrevu

183、sCarvyktiTecvayliPluvictoZepboundOrforglipronCalquenceKisqaliLynparzaKeytrudaImbruvicaXtandiTecentriqEnhertuDato-DxdRetatrutideBrukinsaKesimptaHerceptinHumiraRevlimidLaunch yearDistribution of secondary endpoints for GLP-1sWeb 2024MCK240573 Path to PatientsExhibit 4 of 5Secondary endpoints for top 1

184、00 assets,average of all Phase III trials for each asset 1Includes respiratory,infectious,musculoskeletal,dermatology,and central nervous system diseases.2Patient-reported outcomes.Includes all endpoints explicitly mentioning use of patient self-reported data(eg,self-reported hypoglycemic events)or

185、patient subjective questionnaires(eg,SF-36v2 Health Survey Scores).Source:ClinicalTrials.gov;Evaluate Pharma;McKinsey analysisSecondary endpoints per trial are rising as companies seek to maximize the value of their studies.McKinsey&CompanyAverage secondary endpoint number/productAverage endpointsxx

186、Endocrine,cardiovascular,and bloodImmunologyOthers1OncologyAverage across assetsBottom quartileTop quartileMedianSecondary endpoint number in frst Phase III trialTrulicityOzempicWegovyDiabetesDiabetesObesityDiabetesObesityDiabetesObesityRybelsusCagrisema81726 3019 25 3065213137 4061015183541424825 3

187、0 31362021 2122PROs2 per trialNumber of trials01020304025Charting the path to patientsto support regulatory approval,justify premium pricing,and achieve broader market access.Beyond secondary endpoints,exploratory endpoints may also play a larger role,supported by advanced analytics enabling hypothe

188、sis generation from vast data sets.For example,AI-driven biomarker identification in early-stage trials could be tested as exploratory endpoints in late-stage trials to inform indication expansion strategies.Broadening the global trial footprint Expanding a trial footprint enhances the robustness an

189、d generalizability of clinical programs.Our analysis found that the total footprint of Phase III trials has doubled in the past two decades(Exhibit 5),consistent with increases in sample size and patient demand.Oncology trials tend to have larger footprints than average,likely reflecting the need fo

190、r more sites given high protocol complexity,targeting of distinct populations with specific tumor types,or significant patient attrition.Conversely,immunology trials have a more restricted footprint.We compared sites per trial across all trials initiated between 2005 and 2014 and between 2015 and 20

191、24.While oncology has the largest footprint,the number of sites increased by only 10 percent between the two windows;conversely,immunology sites increased by 31 percent,suggesting larger trials over time.Surprisingly,endocrine,cardiovascular,and blood trials showed a 14 percent decrease.This could b

192、e due to larger trials for Eliquis and Xarelto in the earlier window(200514),which involved ten trials(304 sites per trial)and 26 trials(280 sites per trial),respectively.Recent years have seen a trend toward diversifying beyond traditional site locations in North America and Western Europe.Accordin

193、g to McKinsey analysis,the share of US sites has declined amid a shift to emerging markets(China,AsiaPacific,and Latin America),which accounted for 65 percent of sites in 201524 versus 49 percent in 200514.Establishing a broader,more global trial footprint reflects an increasing need to access more

194、diverse patient populations,accelerate recruitment,and meet growing demands for more representative data.This strategy also allows companies to navigate several regulatory environments simultaneously,speeding up approval in multiple markets.What does the future hold?Expanding trial footprints will r

195、emain a key pillar of asset strategy as competition intensifies for patient populations globally.Digital advancements are likely to play a critical role:for example,digital health platforms and remote monitoring technologies could allow for the inclusion of patients from geographically remote or und

196、erserved regions,where traditional site infrastructure might be lacking.This expands the pool of eligible participants while ensuring that trials are more representative of the global population.The rise of precision medicine and biomarker approaches will further contribute to the expansion of trial

197、 footprint due to the need to enroll rare-patient subgroups.Beyond broadly increasing the quantity of sites,the use of advanced analytics is also likely to increase site quality.For example,AI-based site selection will help identify and eliminate poor performers,enabling companies to focus resources

198、 on high-performing sites.What does this mean for R&D leaders?To remain competitive,industry leaders will need to take an approach to asset strategy that balances speed,value,and cost while embracing innovation to optimize for long-term success.For priority assets,it is especially critical to have a

199、 comprehensive end-to-end strategy early in development,potentially during FIH trials.This requires gathering insights from other assets,mapping out strategic levers for each development stage,and identifying key winning tactics.None of this should happen in a vacuumR&D leaders should tailor their s

200、trategy to the specific asset context across differentiation and likelihood of disruption.For example,assets with low differentiation and high potential for disruption should prioritize speed to market.Conversely,assets with high differentiation and low potential for disruption should focus on enhan

201、cing differentiation,trading off against a longer development timeline to ensure a more robust and defensible market position.How to get started For R&D leaders seeking to optimize asset strategy,we recommend adopting a combination of the following strategic approaches.Conduct a comprehensive asset

202、diagnostic.This diagnostic should scrutinize each detail of the asset plan,leaving no stone unturned in identifying key 26Charting the path to patientsExhibit 5123136140120821077075200514201524200514201524200514201524200514201524+10%14%+31%+8%80847172727561642016292828253936Global distribution of si

203、tes,average number of sites across trials initiated within trial start windowWeb 2024MCK240573 Path to PatientsExhibit 5 of 5Clinical trial sites for top 100 assets,average of all Phase III trials for each asset 1Includes respiratory,infectious,musculoskeletal,dermatology,and central nervous system

204、diseases.Source:ClinicalTrials.gov;Evaluate Pharma;McKinsey analysisThe number of sites per clinical trial has doubled in the past two decades.McKinsey&CompanyAverage site number per trial by assetOncologyEndocrine,cardiovascular,and bloodImmunologyOthers1135392185206119244189126Number of trialsYear

205、 of trial startTAUS%by location:Non-US199419982002 2006201020142018202220242028Endocrine,cardiovascular,and bloodImmunologyOthers1OncologyAverage across assetsXareltoEliquusDatopotamab DeruxtecanPadcevErleadaEntrestoEnhertuVabysmoVerzenioIbranceTrulicityCosentyx SCVyndaqelTaltzInfnziTrelegy ElliptaO

206、zempicKeytrudaAvastinNeulastaRituxanHumiraLyricaTruvadaTecentriqDato-DxdRybelsusVerzenioCagrisemaOrforglipronBrukinsaDupixentZepboundDarzalexImbruvicaUltomirisWegovyDupixentTagrissoOfevCalquenceOcrevusVictozaProliaTradjentaRevlimid2040608010012014016018020022024026027Charting the path to patientsstr

207、ategic levers to improve return on investment.For example,targeted refinement of endpoints based on market research could support competitive differentiation in a crowded landscape.Along the same lines,introducing interim analyses could expedite registration filing and improve launch order to enhanc

208、e market share capture.The timing of this diagnostic is critical for success.It should be initiated following triggers that influence asset performance,including major competitive landscape shifts,early signs of suboptimal performance,and key life cycle milestones(for example,immediately following t

209、he conclusion of early-stage proof-of-concept trials).While important,this diagnostic will be challenging to conduct,given the number of moving variables and the need for both a granular understanding of asset strategy and a synthesized,high-level holistic view.Moreover,every assumption must be rigo

210、rously challenged,and external perspectives integrated with internal expertise and asset-specific insights.Deploy a targeted asset acceleration program.This should focus on operational levers to reduce time to launch,a metric that is becoming increasingly pertinent in a post-IRA landscape.While asse

211、t diagnostics are centered on strategic choices,asset accelerations should be highly tactical but similarly tailored to each assets unique challenges.The impact of asset acceleration is clear;for example,industry leaders have managed to gain up to one year of acceleration through leveraging data-dri

212、ven country and site selection to boost enrollment.Operational levers must be matched by executional excellence in the form of disciplined project management and granular oversight to ensure seamless delivery of daily activities and facilitate early risk identification and mitigation.Notably,in a cr

213、owded market,strategic differentiation is just as important as operational excellence,and industry leaders must seamlessly integrate both to remain in a position of strength.Actively embrace AI-enabled approaches.This could involve using AI for indication finding and prioritization,identification of

214、 underperforming sites,or support for trial management.Successful digital enablement will require significant investment in people,processes,and technology through capability building,talent acquisition,and upskilling initiatives.For example,this could be achieved by establishing a digital center of

215、 excellence,complemented by organization-wide change management.Embracing AI innovation and fostering a culture of digital agility will better position R&D organizations to accelerate development timelines,enhance operational efficiency,and stay ahead in an increasingly competitive landscape.Life sc

216、iences can ride a technology-driven wave of innovation but must simultaneously address the significant challenges the industry faces.We believe this is possible if companies optimize outcomes across the asset R&D life cycle,especially by focusing on strategic opportunities to expand indication bread

217、th and parallelization,number of endpoints,and global trial footprint.Copyright 2024 McKinsey&Company.All rights reserved.Guang Yang is a partner in McKinseys Charlotte office;Jeff Smith and Lucy Prez are senior partners in the Boston office,where Amelia Chang is a consultant;Valentina Sartori is a

218、partner in the Zurich office;and Ling Liu is an associate partner in the New Jersey office.28How biopharmaceutical leaders optimize their portfolio strategies Leading biopharmaceutical companies manage their clinical pipelines to optimize for risk and reward.Heres how.3Picking winning medicines2929H

219、ow biopharmaceutical leaders optimize their portfolio strategiesHow biopharmaceutical leaders optimize their portfolio strategiesLeading biopharmaceutical companies manage their clinical pipelines to optimize for risk and reward.Heres how.by Guang Yang and Jeff Smithwith Emily Wingrove and Eva Lopez

220、 VidalDiscovering and developing effective new medicines has always been difficultbut it is particularly hard today.The worlds biopharmaceutical companies face challenges ranging from rising R&D costs to the evolving impact of the US Inflation Reduction Act,all while focused on delivering innovative

221、 solutions for patients.Yet leading companies remain effective despite these pressures,with the past few years seeing the emergence of innovative modalities and novel mechanisms of action(MoAs)that can better treat patients in areas with high levels of unmet medical needs.We examined what can be lea

222、rned from their approaches and identified three actions leaders are taking to better position their portfolios1:1.increasing“shots on goal”while moving to quickly discontinue assets that do not meet established evidence targets 2.investing in established therapeutic areas(TAs)while maintaining suffi

223、cient breadth3.balancing portfolios with different types of distinctiveness,such as novel MoAs and capabilities in new modalities There is no“one size fits all”approach to a successful portfolio strategy,and mechanisms to optimize portfolio strategy are nuanced.Overall,we see leading biopharmas embr

224、acing a variety of tactics,including relying on depth of therapeutic area expertise,investing in a specific innovation(for example,novel modality)and then expanding that innovation across different diseases,and prioritizing external sourcing to further enhance pipeline blockbuster potential.We recom

225、mend players thoughtfully shape and execute their investment thesis while maintaining other healthy habitssuch as undertaking robust and consistent portfolio prioritization(rather than in response to a cost transformation effort or acquisition),opportunistically expanding into high-value areas beyon

226、d TAs currently in focus,and carefully balancing both first-in-class targets(higher biological risk)and differentiated modalities(higher technical risk)to better manage risks and optimize rewards of their portfolios.1.Increasing shots on goal and discontinuing assets early Stringent portfolio priori

227、tization has always been central to the portfolio strategy of biopharma companies.Among top biopharmas,the number of unique assets in the clinical pipeline increased by an average of 15 to 30 percent between 2018 1 Leading biopharmas are defined as the top 14 pharmaceutical companies by revenue in 2

228、02324.Some companies were not included in all analyses given data availability.Companies were anonymized for privacy purposes and are not consistently numbered across figures.30and 2024,2 indicating leading players were moving to grow their portfolios and total number of“shots on goal.”With larger p

229、ortfolios,top biopharmas routinely discontinue portions of their pipelines to focus on high-quality assets and create space for ongoing portfolio renewal.During this period,top biopharma companies discontinued an average of 22 percent of programs annually from 2018 to 2019 and 21 percent a year from

230、 2023 to 2024.Individual biopharma companies discontinued 11 to 37 percent of programs in any given year(Exhibit 1).While there were variations in the proportion of discontinued programs among leading biopharma companies,some that experienced larger“swings”had undertaken a sizable acquisition or gon

231、e through a cost transformation likely followed by a reprioritization of the portfolio.This suggests the Exhibit 116161113191624541Web Exhibit of Clinical programs discontinued by top biopharmas,1%of total pipeline Note:Companies are anonymized and numbers are randomized across exhibits.1Pipeline of

232、 top biopharmas(ie,assets in Phases I,II,and III)at the beginning of 2018,2019,2023,and 2024.Assets studied across multiple indications that may be discontinued for one indication,but not all,are considered continued assets.Includes assets developed in-house or in partnership;data listed only where

233、available.Leading biopharma companies consistently discontinue programs that are not meeting established evidence targets.McKinsey&Company Company 1 Company 2 Company 3 Company 4 Company 5 Company 6 Company 7 Company 8 Company 9 Company 10Average191316373330231511112135292724141425191615222023242018

234、1910%increase10%decrease10%changeHow biopharmaceutical leaders optimize their portfolio strategies2 “Evaluate releases 2030 forecasts for global pharmaceutical market,”Evaluate Pharma,July 10,2024;company websites.31How biopharmaceutical leaders optimize their portfolio strategiesnarrative of progra

235、m“cuts”having increased in recent years may be an artifact of the growing size of the clinical pipeline for leading biopharmas(both organic and through M&A)and that the rate of typical pipeline“pruning”will likely vary year by year but has largely remained consistent across leading players.Discontin

236、ued assets skew toward early-pipeline programsIt is best practice to discontinue assets before they reach more expensive registrational trials and to use results from early-stage clinical trials to prioritize assets with the most compelling evidence for patient impact.About 50 percent of assets disc

237、ontinued by leading biopharma companies in both 2019 and 2024 were in PhaseI.While this trends in the right direction,it still leaves a large portion of the portfolio discontinued in Phase II or III(Exhibit 2).Our analysis found that no particular therapeutic area was subject to a disproportionate n

238、umber of discontinued clinical pipeline programs.2.Investing in established therapeutic areas while maintaining sufficient breadthTreatment of metabolic and endocrine-related diseases has experienced recent success(for example,GLP-1 agonists Ozempic and Wegovy)and is expected to have greater revenue

239、 growth than any other therapeutic area through 2028.3 While leading biopharma companies on average Exhibit 2Web Exhibit of Clinical pipeline discontinued between early 2018 and early 2019,1%Note:Figures may not sum,because of rounding.Companies are anonymized and numbers are randomized across exhib

240、its.1Pipeline of top biopharmas(ie,assets in Phases I,II,and III)at the beginning of 2018 and 2019.Assets present in 2018 and in 2019 for diferent indications are considered as continued assets.Includes assets developed in-house or in partnership;data listed only where available.Phase indicates asse

241、t development phase in early 2018 or early 2023.Some biopharmas may consider increasing their rate of discontinued programs early in clinical development.McKinsey&CompanyClinical pipeline discontinued between early 2023 and early 2024,1%Company 1 Company 2 Company 3 Company 4 Company 5 Company 6 Com

242、pany 7 Company 8 Company 9 Company 10Average2829161021210678133121075477565515222335292725241916151414221361017226363014136642116533146243433121913162337151111323021Phase IPhase IIPhase III%discontinued in 3“Evaluate releases 2030 forecasts for global pharmaceutical market,”Evaluate Pharma,July 10,2

243、024.32did not increase the proportion of their pipeline devoted to metabolic,endocrine,or cardiovascular diseases in 2023,we see movement by many leading players to heavily invest in a few select,cardiometabolic-focused assets that likely represent new strategic priorities for their organizations(fo

244、r example,Roches acquisition of Carmot Therapeutics obesity candidates CT-388 and CT-996 or Amgens MariTide).When we examined how the pipelines of leading biopharmas had changed during the past five years,we found that oncology remains the largest focus(37percent in 2023 compared with 35 percent in

245、2018),followed by anti-infectives and diseases of the central nervous system(Exhibit 3).4 In the period we examined,the percentage of the clinical pipeline focused on specific therapeutic areas barely shifted across leading players.Yet individual players did make moves:four leading biopharmas increa

246、sed their oncology presence by ten percentage points or more between 2018 and 2023,while there was a reduced pipeline focus in areas such as respiratory diseases.Other therapeutic areas showing adjustments in focus5 were cardiovascular disease,diseases of the central nervous system,gastrointestinal

247、issues,immunomodulators,and anti-infectives.The pattern of portfolio redistribution within a five-year span varied,with some big players making shifts of ten percentage points in either direction for one or two therapeutic areas and others“drifting”five or fewer percentage points across several.Many

248、 biopharmas are moving to treat smaller patient populationsWhile the mix of therapeutic areas has remained relatively unchanged,some leading biopharma companies are focusing on diseases that have smaller patient populations.Such efforts are likely a response to rising pressures,such as the Inflation

249、 Reduction Act and the push for targeted medicines that are relevant only to small patient subpopulations.For example,ten of the top 14 biopharmas focus a majority of early-stage new molecular entities(Phases I and II)on diseases with smaller patient populations(such as those with fewer than 100 mil

250、lion patients worldwide).3.Balancing portfolios with different types of distinctivenessAs McKinsey and others have previously reported,6 a relative dearth of both novel and biologically validated targets has contributed to increased target crowding.Across top biopharma,only a quarter of assets are p

251、ursuing unique targets,while the proportion of highly crowded targets increased by seven percentage points from 2021 to 2023.A similar increase was observed across the full industry(Exhibit 4).Biopharmas have explored two options in response to target crowding:invest in technology to identify and va

252、lidate novel targets,or invest in novel modalities to differentiate within crowded targets.Historically,a select group of biopharmas have been more comfortable pursuing the first option,acting A relative dearth of both novel and biologically validated targets has contributed to increased target crow

253、ding.How biopharmaceutical leaders optimize their portfolio strategies4 Clinical pipeline is defined as assets in Phase I,II,or III of clinical development.It excludes assets that are marketed or approved.5 Adjustment in focus is defined by a shift of more than 10 percent of the clinical portfolio(e

254、ither up or down)for at least one of the top biopharmas studied.6 Julie Cannon et al.,“Herding in the drug development pipeline,”Nature Reviews Drug Discovery,April 28,2023.33Exhibit 3DermatologyGenitourinarySensoryHematology2MusculoskeletalRespiratoryGastrointestinalImmuno-modulatorsOtherEndocrinem

255、etabolic3Central nervoussystemAnti-infectivesOncology11233557899132222236788813371823 1823 1823 1823 1823 1823 1823 1823 1823 1823 1823 1823 1823 1823Web Exhibit of Pipeline for top biopharmas,201823,1%1Pipeline does not include marketed or approved products;therapeutic area determination as reporte

256、d by Evaluate Pharma;assets treating malignant hematology included under oncology;psychology included in diseases related to the central nervous system;immunomodulators include immunostimulants,immunosuppressants,and interferons;company number is not consistent across fgures.2Nonmalignant hematology

257、.3Includes cardiovascular diseases.Source:Evaluate Pharma In terms of number of total pipeline assets,oncology remains an area of focus for leading biopharmas.McKinsey&CompanyTotal pipeline,%Company1 2 3 4 5 6 7 8 9 10 11 12 13 141823How biopharmaceutical leaders optimize their portfolio strategies3

258、4as“leaders”in validating new targets(first in class)rather than“followers”that aim to differentiate biologically derisked targets(best in class).Investment in new target discovery remains a critical aspect of pipeline strategy,and leading players must develop approaches to address this challenge ei

259、ther by acquiring discovery platforms or by building capabilities in-house.Leading biopharma companies have made deals focused on novel target discovery in recent years;for example,Pfizer invested in Flagship Pioneerings ProFound Therapeutics with the goal of uncovering new targets in obesity by lev

260、eraging a database of previously unannotated proteins in the human proteome.7 Others are trying to build novel target identification capabilities in-house;AstraZeneca invested in synthesizing information from publicly available data sources and merging it with the companys own proprietary data to fo

261、rm new connections among disease pathology,individual proteins,and signaling pathways.8 Building distinctive technical capabilities Given the increasingly competitive environment and challenges associated with novel target discovery,many players are building capabilities for novel modalities that al

262、low them to create a differentiated asset with a more established target.For example,the value of transactions for antibodydrug conjugates(ADCs)has surged by more than 216percent in recent years,driven by major deals Exhibit 4Pipeline proportion by degree of target crowding in 2021 and 2023,1%Note:F

263、igures may not sum to 100%,because of rounding.1Identifed targets within companies pipeline and the number of drugs actively investigating each of those targets(Phase I:registration).Combinations are treated as distinct targets(eg,GLP-1/GIP and GLP-1 treated separately).Company number is not consist

264、ent across fgures.Source:PharmaProjectsLeading biopharma companies are increasingly focusing on the same targets.McKinsey&CompanyIndustry14 top biopharma Change,202123,percentage point(p.p.)Change,202123,p.p.33+525+720212023282537343641202120232523433832391255Total number of assets pursuing target a

265、cross biopharma pipelineHow biopharmaceutical leaders optimize their portfolio strategies7 “Flagship Pioneering and ProFound Therapeutics announce agreement to identify novel first-in-class therapeutics for the treatment of obesity under strategic partnership with Pfizer,”Flagship Pioneering,June 12

266、,2024.8 David Geleta et al.,“Biological insights knowledge graph:An integrated knowledge graph to support drug development,”bioRxiv.org,November 1,2021;Anna Gogleva et al.,“Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutation non-small cell lung cancer,”Na

267、ture Communications,March 29,2022.35Exhibit 5Pipeline assets in Phases I,II,and III by innovation potential,%Note:Company number is not consistent across fgures.1Assets without a specifed target were not taken into consideration.Includes assets where the biopharma is the originator or the licensee.2

268、Excludes assets directed to a target that already has an approved drug;includes assets in the most advanced phase of development for a specifc target;multiple assets can be the most advanced when in the same clinical trial phase.Source:PharmaProjectsRoughly half of top biopharma portfolios have the

269、potential to be frst in class.McKinsey&CompanyAverage Company 1 Company 2 Company 3 Company 4 Company 5 Company 6 Company 7 Company 8 Company 9 Company 10 Company 11 Company 12 Company 13 Company 14465553534848474746464443433837544547475252535354545657576263Potential to be frst in class2Othersuch as

270、 Seagen and Pfizer($43 billion),Daiichi Sankyo and Merck($22 billion),and Immunogen and AbbVie($10 billion).9 Radioligand-based therapies are another“hot”emerging modality.While leading biopharmas once had limited interest in this space,around$14 billion in deals have been completed since 2022 follo

271、wing the success of several assets(for example,Pluvicto in metastatic,castration-resistant prostate cancer).Future activity may focus on a shift toward higher-potency payloads with reduced off-target effects(such as alpha emitters)as well as the expansion of available isotypes.Given the risk and uni

272、que considerations of identifying novel biology and developing novel modalities,a deliberately balanced approach to the makeup of portfolios may help minimize overall risk.On average,top biopharmas focus about half of their portfolio on molecules with the potential to be“first in class,”while the ot

273、her half focuses on targets that are more estab-lished but may hold a technological edge(Exhibit 5).Todays imperative:Continuous,effective portfolio managementWithout a consistent approach to portfolio evaluation and management,companies may take How biopharmaceutical leaders optimize their portfoli

274、o strategies9 “Pfizer completes acquisition of Seagen,”Pfizer,December 14,2023;“Daiichi Sankyo and Merck announce global development and commercialization collaboration for three Daiichi Sankyo DXd ADCs,”Merck,October 19,2023;Angus Liu,“AbbVie pays$10B to acquire ImmunoGen,doubling down on red-hot A

275、DC cancer field,”Fierce Pharma,November 30,2023.36Exhibit 637231311151613523512521213401032361228181031211151410311516114214611123616954138121311811371212721147141534139322267917165321CardiovascularNervous systemOncologyHematologyImmunologyHepatobiliaryHematologyInfectious diseasesOncologyImmunology

276、Nervous systemHematologyHepatobiliaryMet/Endo1CardiovascularNephrologyMet/Endo1HepatobiliaryImmunologyInfectious diseasesOncologyHematologyNervous systemCardiovascularMet/Endo1ImmunologyOncologyInfectious diseasesHematologyHepatobiliaryCardiovascularInfectious diseasesImmunologyHematologyOncologyNer

277、vous systemOphthalmologyCardiovascularNephrologyHematologyImmunologyOncologyMet/Endo1Nervous systemOphthalmologyENTHepatobiliaryCardiovascularImmunologyMet/Endo1Nervous systemOncologyHematologyGenitourinary diseasesInfectious diseasesImmunologyHematologyOncologyNervous systemOphthalmologyMet/Endo1In

278、fectious diseasesHepatobiliaryCardiovascularNephrologyOncologyImmunologyHematologyNervous systemMet/Endo1CardiovascularMet/Endo1Infectious diseasesHematologyImmunologyOncologyNervous systemOphthalmologyNephrologyOtherCardiovascularMet/Endo1Infectious diseasesNervous systemHematologyImmunologyOncolog

279、yNephrologyOtherOphthalmologyHepatobiliaryCompany 1Company 2Company 3Company 4Company 5Company 6Company 7Company 8Company 9Company 10Company 11Company 12Breadth number of TAsDepth Scale of pipeline in targeted TAsBuilding a portfolio in a T shape can provide depth in focus areas as well as the agili

280、ty to move quickly to capture emerging opportunities.Pipeline focus by therapeutic area(TA),number of assets(new molecular entities or indication expansions)with active clinical trials per TAMcKinsey&CompanyNote:Assets in Phases I,II,and III;may noore than once(for more than one indication)within th

281、e same TA,the asset is only counted once.Companies are anonymized and numbers are randomized across exhibits.Hematological cancers are included in hematology.Nervous system includes psychiatry.Other includes reproductive medicine,surgery,and miscellaneous.1 Metabolic and endocrine-related diseases.S

282、ource:Company websites,May 2024How biopharmaceutical leaders optimize their portfolio strategies37too many risks or become too cautious.As a result,potentially competitive assets can be out-licensed or discontinued during times of financial stress.Finding the right balance can be challenging,but it

283、starts with the data-driven,objective setting of accurate stage gates and stringency in upholding these stage gates consistently.One trend we did not observe was a quantifiable shift in therapeutic area focus across leading players,as measured by the total number of pipeline assets.However,we did ob

284、serve many leading biopharmas enter more selectively into the cardiometabolic space with a few high-priority cardiometabolic assets.The subtle changes in portfolio makeup in a fast-renewing pipeline point to the historic success top biopharmas enjoyed in building therapeutic area expertise and their

285、 hesitancy to rapidly shift portfolio makeup.One approach for players to consider and maintain is designing a portfolio in a“T”shape:building significant depth in two to three therapeutic areas while maintaining sufficient breadth of coverage to rapidly and opportunistically engage in new and emergi

286、ng science(Exhibit 6).The risks involved in uncovering new biology remain a clear pain point for the industry.Investing in capabilities that can uncover novel biology at scale(for example,leveraging AI to mine relevant preclinical literature from leading journals)may jump-start leading players abili

287、ty to develop first-in-class assets in-house.On the other hand,becoming an industry leader in a novel modality(such as ADCs,radiotherapies,or T-cell engagers)or,even better,having a portfolio with a diverse modality suite may allow for differentiation in competitive MoAs.We recommend biopharma compa

288、nies carefully balance both first-in-class targets(higher biological risk)and differentiated modalities(higher technical risk)to better manage risk and optimize the rewards of their portfolios.Copyright 2024 McKinsey&Company.All rights reserved.Guang Yang is a partner in McKinseys Charlotte office.J

289、eff Smith is a senior partner in the Boston office,where EmilyWingrove and Eva Lopez Vidal are consultants.How biopharmaceutical leaders optimize their portfolio strategies38Operational excellence in biopharma research and early development Leading companies are revamping research and early developm

290、ent to curb lengthy drug development timelines and rising costs.Accelerating clinical trials to improve biopharma R&D productivity Biopharma sponsors are seeking to accelerate clinical trials and reduce costs through a set of targeted actions aimed at improving patient and site engagement and enroll

291、ment productivity.4Working simply and smartly473939Accelerating clinical trials to improve biopharma R&D productivityAccelerating clinical trials to improve biopharma R&D productivityBiopharma sponsors are seeking to accelerate clinical trials and reduce costs through a set of targeted actions aimed

292、 at improving patient and site engagement and enrollment productivity.This article is a collaborative effort by Gaurav Agrawal,Jacob Kautzky,Harriet Keane,Brandon Parry,Valentina Sartori,and Amy Silverstein,representing views from McKinseys Life Sciences Practice.Biopharmaceutical(biopharma)R&D stan

293、ds at an inflection point,with the limiting factor for innovation no longer science or funding but the speed at which clinical trials can be completed because of a shortage of study participants and clinical site professionals such as principal investigators(PIs)site coordinators,and nurses.In this

294、environment,the most successful clinical trial sponsors(that is,biopharma manufacturers that are responsible for trial initiation,management,and financing)will be the biopharma companies that evolve their clinical trial delivery model to create a compelling value proposition for study participants a

295、nd sites.This article explores the barriers to improving R&D productivity,including long clinical trial timelines and challenges to clinical trial recruitment,and actions sponsors can take to increase trial participants and improve the experience of clinical trial sites.A golden era for biopharma in

296、novation Today,the biopharma industry has its largest and most diverse clinical pipeline in history,the culmination of decades of innovative research.The total number of distinct drugs in development grew from 3,200 in 2012 to 6,100 in 2022.1 Furthermore,this pipeline is increasingly diverse;14 perc

297、ent of assets use modalities validated over the past five years(predominantly various forms of cell and gene therapy).2The ability to deliver on this expansive pipeline has been enabled by government investmentincluding an estimated$18 billion made available for Operation Warp Speed and$48 billion i

298、nvested each year by the National Institutes of Health alone3and private markets,with an estimated$146 billion in life sciences venture capital funding in the past three years.4 1 Based on McKinsey analysis of PharmaProjects data 2022.2 Ibid.3 “Operation Warp Speed:Implications for global vaccine se

299、curity,”The Lancet Global Health,March 26,2021;“Budget,”National Institutes of Health,reviewed October 24,2023.4 McKinsey analysis of BioCentury Inc.,accessed February 2023.40Accelerating clinical trials to improve biopharma R&D productivityLow R&D productivity driven by lengthy clinical trial timel

300、ines and increasing trial costs Although the current climate for biopharma innovation is seemingly ideal,with 4,300 clinical trials starting in 2022 alone,R&D productivity remains stubbornly low.From 2012 to 2022,inflation-adjusted industry R&D spending increased 44 percent,from about$170 billion to

301、$247 billion,(Exhibit 1).5 However,the number of US novel drug approvals remains flat at an average of 43 per year,meaning the attrition-adjusted cost to develop a single novel asset is now estimated to be as high as$2.8 billion.6Multiple factors underlie low R&D productivity,including consistently

302、low success rates;only about 13 percent of assets that enter the Phase 1 trial stage go on to launch.7 In addition,development costs remain high(accounting for as much as 60 to 70 percent of total costs)8 and development cycles are long(taking an average of 12 years to develop a novel medicine).9 Fu

303、rthermore,development timelines have extended.For example,according to McKinsey analysis,between the periods of 2011 to 2015 and 2016 to 2021,the average clinical trial lengthened from 41 to 44 months for Phase 3 trials and from 37 to 41 months for Phase 2 trials.10 Today,it is estimated that up to

304、80 percent of clinical trials fail to finish on time.11 At the same time,speed of clinical development is critical for biopharma companies and patients.For companies,the rise in“herding,”in which multiple companies focus on the same high-potential mechanisms of action(MoAs),increases the pressure to

305、 be first to market.Over the past 20 years,the top five most active MoAs in a given year saw an almost fivefold increase in the number of assets being developed,with the first product to market achieving outsize success.12 Furthermore,the passage of the US Inflation Reduction Act,which includes prov

306、isions to reduce drug prices,will influence which indications companies pursue and increase the importance of being first to market.For patients of many indications,unmet need remains acute;more than 6,000 rare diseases have no known therapy,13 and numerous cancers(for example,pancreatic cancers,mes

307、otheliomas,and brain cancers)have a five-year survival rate of less than 35 percent.14 For a pharma company with three to five investigational drugs entering first in human studies each year,a 12-month development acceleration applied across the portfolio can translate to more than$400 million in ne

308、t present value for the sponsor and deliver incalculable benefits for patients and their families.15Challenges in recruitment for clinical trials Although there are multiple levers to pull to improve R&D productivity,development acceleration is one R&D leaders can explore immediately and one that ca

309、n have a greater impact on patients.In clinical trials,treatment durations are often fixed,and study start-up and close-out account for only a small portion of overall trial duration(with best-in-class timelines of about two months and one month,respectively).Therefore,the biggest opportunity for sp

310、onsors to accelerate clinical trials is to increase the speed and improve the efficiency of clinical trial enrollment;however,participant recruitment is increasingly difficult.For example,the rate of clinical trial participants enrolled per site per month in oncology and nononcology Phase 3 trials d

311、eclined by 14 percent and 54 percent,respectively,in the periods 2012 to 2014 and 2021 to 2023(Exhibit 2).5 Based on McKinsey analysis of data from Pharmaprojects,2022 and Evaluate Pharma,August 2023.6 “CDERs annual novel drug approvals:2013 2022,”New Drug Therapy Approvals 2022,U.S.Food&Drug Admini

312、stration,current as of January 10,2023.7 McKinsey analysis.8 2022 PhRMA Annual Membership Survey,PhRMA.9 Gaurav Agrawal,Felix Bader,Jan Gnthner,and Stephan Wurzer,“Fast to first-in-human:Getting new medicines to patients more quickly,”McKinsey,February 10,2023.10 “Protocol design scope and execution

313、 burden continue to rise,most notably in Phase III,”Tufts CFSD Impact report,May/June 2023,Volume 25,Number 3;Jason Scott,“Phase 3 trials significantly rising in complexity,says CSDD,”CenterWatch,May 15,2023.11 Mette Brgger-Mikkelsen et al.,“Online patient recruitment in clinical trials:Systematic r

314、eview and meta-analysis,”Journal of Medical Internet Research,November 2020.12 Christian Fougner et al.,“Herding in the drug development pipeline,”Nature Reviews Drug Discovery,April 28,2023,Volume 22.13 McKinsey analysis of Orphanet.14 “Cancer stat facts:Pancreatic cancer,”Surveillance,Epidemiology

315、,and End Results Program(SEER),National Cancer Institute,accessed November 2023;“Survival rates for malignant mesothelioma,”American Cancer Society,last revised March 2,2023;“Cancer stat facts:Brain and other nervous system cancer,”SEER,National Cancer Institute,accessed November 2023.15“Fast to fir

316、st-in-human,”February 10,2023.41Accelerating clinical trials to improve biopharma R&D productivityFactors contributing to enrollment challenges exist on both the sponsor and site side of the equation.Sponsors require more participants than ever and are defining eligibility more specifically.Meanwhil

317、e,more complex protocols have increased the demands placed on sites at a time when clinical trial site staff turnover(PIs,clinical trial coordinators,and nurses)is at an all-time high,16 and physicians are less motivated to participate in clinical research because of changes to incentive models.Incr

318、easing demand for trial participants According to McKinsey analysis,over the past decade demand for trial participants has increased almost 10 percent as a result of more and larger trials;comparing 2019 to 2022,the total target enrolment of trials starting in those years grew 18 percent,from 2.2 mi

319、llion to 2.6 million(Exhibit 3).Moreover,demand is spread unevenly,with disproportionately high trial volumes compared to overall incidence for some indications(for instance,multiple myeloma,cystic fibrosis,multiple sclerosis,non-Hodgkin lymphoma,and thalassemia).Oncology poses a particular challeng

320、e;the number of required participants has increased from about 1.1 million in 2019 to about 1.3 million in 2022.17(As a point of comparison,an estimated 1.9 million individuals were diagnosed with cancer in the Exhibit 101,0002,0003,0004,0005,000201220132014201520162017201820192020202120222050100150

321、200250300Number of industry-sponsored interventional clinical trial startsPharma R&D spending,$billion(infation adjusted to 2022)1For all therapeutic areas,excluding reformulations and biosimilars.2Probability of total regulatory success data not yet reported for 2022.3Based on reported fnancials fo

322、r public companies and Evaluate estimates for private ones.Source:Clinicaltrials.gov;Evaluate Pharma 2022;Pharmaprojects July 2022;McKinsey analysisInfation-adjusted pharma R&D spending has outpaced clinical trial starts,with no corresponding improvement in technical and regulatory success.McKinsey&

323、CompanyProbabilityof success(Phase 13),%141911131013151313N/A13Clinical trial startsIndustry pharma R&D spending 16 Grace Sun et al.,“Crisis of the clinical trials staff attrition after the COVID-19 pandemic,”JCO Oncology Practice,August 1,2023,Volume 19,Number 8.17 Clinicaltrials.gov;McKinsey analy

324、sis including all trials currently recruiting for breast cancer,cervical cancer,CRC,leukemia,melanoma,multiple myeloma,NHL,NSCLC,prostate cancer,and renal cell carcinoma.42Accelerating clinical trials to improve biopharma R&D productivityExhibit 220121420151720182020212327242426201214201517201820202

325、123171918162012142015172018202021235.74.95.05.82012142015172018202021230.220.210.190.19201214201517201820202123131416182012142015172018202021232424201620121420151720182020212310.49.87.18.52012142015172018202021230.840.720.440.39OncologyNon-oncology(excl infectious disease)Recruitment duration inmont

326、hsNumber of participants enrolled per month of recruitmentNumber of participants enrolled per siteNumber of participants enrolled per site per monthIndustry enrollment productivity for Phase 3 regulatory trials has declined,with sites enrolling fewer patients per month and per site.4%4%+2%14%+38%36%

327、19%54%Source:Clinicaltrials.govMcKinsey&Company43Accelerating clinical trials to improve biopharma R&D productivityUnited States in 2022.18)Despite this considerable clinical research activity,only about 6 percent of US cancer patients are estimated to participate in a clinical trial.This participat

328、ion rate is only 4 percent for patients receiving care at nonNational Cancer Institute(NCI)centers compared to 19 percent at NCI centers.19 These trends in concentration of care are applicable across the world,including in other geographies where clinical trials are commonly run(for example,Eastern

329、Europe and Western Europe).The enrollment challenge is further exacerbated by an increased focus on precision medicine,whereby study groups are tightly defined with the goal of developing medicines that are highly effective in subsets of participants.20 For example,as of 2022,more than half of oncol

330、ogy trials are estimated to have a biomarker-defined target subpopulation.21 This is the case even with indications traditionally viewed as homogenous,such as lung cancer,which has more than ten subpopulations being investigated in clinical trials.22These industry-wide dynamics have made recruiting

331、increasingly challenging.Whereas a site may have only a handful of(or zero)eligible participants for a given study,the time and financial burden of standing up a clinical trial at even a single site is undiminished for sponsor and site.Rising burden on sitesAs sponsors strive to generate more compel

332、ling data packages for regulators and internal translational research(to inform the next generation of drug discovery),the burden on sites has continued to rise.As a measure of trial complexity,the average number Exhibit 3Number of patients1Based on all industry-sponsored trials with a start date in

333、 target year.2Based on all Phase 3 clinical trials(excluding infectious diseases)reaching primary completion in target year.3Based on all noninfectious disease Phase 14 clinical trials active in target year(for example,starting before or on target year and fnishing after or in target year).Source:Clinicaltrials.gov;McKinsey analysisDemand for clinical trial patients grew by about 10 percent betwee