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1、White PaperCombination Therapy Dose Optimization in Oncology Trials Design,modeling,and operational considerations for biotech andpharmaJEFFREY HODGE,MS,Vice President Early Phase Oncology,Hematology-Oncology Center of ExcellenceDAVID ALSADIUS,MD,PhD,Senior Medical Director,Solid Tumor Lead,Hematolo

2、gy-Oncology Center of ExcellenceJENNIFER UNDERWOOD,MSc,Senior Therapeutic Strategy Director,OncologyZHENG LIU,DSc,Director,Quantitative Clinical PharmacologyBRYCE DAVIES,MSc,Head of APAC Strategy,Early Phase Oncology and Innovative TherapiesTable of contentsIntroduction 1The growing role of combinat

3、ion therapies in oncology 2Dose optimization:The shift away from maximum tolerated dose 3Trial design,feasibility,and execution considerations 6Data analysis:Modeling and simulation for decision-making 10Conclusion 11References 12 |1Combination therapies represent the future of oncology innovation,o

4、ffering clinicians with regimens that have the potential to enhance efficacy,delay resistance and improve patients responses and outcomes.Yet,determining dose optimization for such regimens is among the fields most complex challenges and requires rigorous operational and statistical planning and exe

5、cution.This white paper reviews the design,operational,and analytic challenges that sponsors must consider when designing effective and efficient combination dose-finding trials.Sponsors who partner with clinical research organizations like IQVIA can leverage their experience in this setting to real

6、ize precision and efficiencies to advance combination therapies aligned with global regulatory expectations.Introduction2|Combination Therapy Dose Optimization in Oncology TrialsThe growing role of combination therapies in oncology The combination of drugs is now central to modern oncology clinical

7、practice,where the heterogeneity of patients tumors necessitates multifaceted therapeutic strategies.Figure 1 shows immunotherapies(IO),molecularly targeted small molecules,biologics,and cytotoxic chemotherapies are increasingly used together to overcome treatment resistance and enhance the durabili

8、ty of patient response.One of the most recent oncology regimens to receive U.S.Food and Drug Administration(FDA)approval combined the novel targeted agent inavolisib with the targeted drugs palbociclib and fulvestrant for adults with a genetically defined form of locally advanced or metastatic breas

9、t cancer following its recurrence on or after prior therapy.1,2Approvals for combination therapies have risen steadily,particularly for common cancers.3 Oncology regimens combining an experimental medicine to the existing standard of care or another novel investigational drug comprised one third of

10、the 292 FDA drug approvals for solid tumors from 2011 to 2023.These approved combinations received indications as first-line treatments nearly twice as often as monotherapies.They were also more than twice as likely as single drugs to use overall survival(OS)as a primary endpoint in pivotal studies.

11、3 Despite their increased availability,many combinations have yet to differentiate significantly from monotherapies in patient responses and survival and may increase treatment-related toxicities.To solve for improved patient responses and survival and superior safety profiles,pharmaceutical and bio

12、tech sponsors registered more than 1,750 clinical trials examining combination therapies as of early April 2025.4 By promoting earlier regulatory engagement,Project FrontRunner also incentivizes the design and initiation of combination studies in earlier treatment lines,potentially speeding up the d

13、evelopment of more effective multi-drug therapies.5Figure 1.Comparison of approval pathway and scenario between single-agent bination cancer therapy indications from 2011 to 2023.3 Drug classCytotoxic chemotherapy(N=12)Hormonal(N=14)Immunotherapy(N=107)4(4.0%)4(4.0%)42(42.4%)30(30.3%)19(19.2%)Combin

14、ation(N=99)Small molecular targeted agents(N=116)Biologic agents(N=37)|3This research and development strategy is anticipated to introduce into clinical practice regimens employing novel small molecules and a range of immunotherapies technologies,including adoptive cell transfer,cancer vaccines,immu

15、nomodulators,oncolytic viruses and targeted antibodies.6The market entry of such new interventions is predicted to expand its global value,with combinations including an IO estimated to reach at least U.S.$18 billion by 2028.4.7In this landscape,sponsors developing combination therapies in oncology

16、must adopt efficient and rational trial designs to determine their safety and efficacy in the most suitable patient population.Dose optimization:The shift away from maximum tolerated doseHistorically,the recommended dosing for the expansion of phase 1 oncology trials or the start of later-stage stud

17、ies has defaulted to the maximum tolerated dose(MTD)approach determined in early phase trials.8 Reliance on MTD stems from the development of cytotoxic agents.The term reflects the concept that both efficacy and toxicity are monotonically consistently and predictably related to dose,and higher doses

18、 of these systemic therapies had greater anti-tumor activity.These cytotoxics also had high rates of side effects,which frequently resulted in dose reductions,treatment interruptions or patients stopping therapy altogether potentially reducing the overall effectiveness of the drugs.However,with nove

19、l therapies such as immunotherapies and targeted agents,the dose-response/toxicity curves may have other shapes than monotonically increasing.Higher doses of these interventions may not result in greater efficacy.In such cases,the optimal dose may actually be lower than the MTD.The FDAs Project Opti

20、mus now requests sponsors to step away from MTD and to emphasize therapeutic benefit-risk in dose optimization.This shift means sponsors must generate randomized safety and response data for a range of doses in early phase trials to justify dose selection for registration trials.9,10 This change,whi

21、le adding time and resources to protocol design planning,is expected to bring about efficiencies in trial execution.The optimization step should yield greater safety and tolerability for patients and an overall superior treatment regimen.IQIVIA suggests sponsors begin designs using data-and model-in

22、formed scenario planning,which the FDA encourages.With the right study design and delivery strategies,the impact of the additional time required for dose optimization can be minimized.For sponsors to align with the FDAs Project Optimus,it is critical they recognize and plan how to address the challe

23、nges of optimizing doses for multi-therapeutic regimens in early phase trials.Partnering with a clinical research organization(CRO)with deep experience in oncology and novel drug platforms can help sponsors determine a strategic approach to support identifying clinically effective doses that meet re

24、gulatory standards for the best patient outcomes.Sponsors have differed in their approaches to dose optimization of investigational combination regimens,depending on the agents mechanism of action,efficacy and safety while considering the variability of patient populations and the biology of their c

25、ancers and treatment responses.8,9 These strategies include using comparative arms or biomarker data,but all begin with a rigorous evaluation of the study drugs characteristics.9,10 Study drug characteristics pivotal to dose optimizationPlanning an optimization protocol to combine a novel agent with

26、 one or more novel or existing agents is complex.It entails meticulous measuring,analyzing and interpreting data about each agents pharmacologic features,interactions,sequential effects and patient-specific factors.9,11Sponsors must begin by establishing robust preclinical profiles from each agents

27、pharmacology,tumor growth inhibition(TGI),and toxicology studies.Consideration should also be given to available clinical safety data from agents in the same class.11 4|Combination Therapy Dose Optimization in Oncology TrialsSponsors should also determine if biomarkers can inform optimization by pro

28、viding valuable exploratory insights into the clinically active dose range.Liquid biopsies may enable longitudinal assessment of soluble biomarkers,such as cytokines and chemokine profiles across multiple treatment timepoints,including at disease progression.12 These markers represent dynamic indica

29、tors of tumor biology and pharmacologic response,like TGI.These markers also provide critical inputs for model-informed drug development(MIDD)approaches that support the characterization of exposure pharmacodynamics relationships and dose selection strategies for optimization.Sponsors may consider u

30、sing novel biomarkers when developing innovative therapies.For example,the circulating tumor DNA(ctDNA)may help monitor resistance and disease progression and characterize exposureresponse(E-R)relationships of investigational treatments.9,13 Despite the promise of ctDNA as a biomarker for monitoring

31、 treatment response in solid tumors,its clinical implementation faces some remaining challenges.These include,for example,low abundance of ctDNA early-stage cancers,lack of technical standardization in detection methods,and variability in pre-analytical and analytical protocols.Addressing these issu

32、es requires refining detection techniques,establishing standardized protocols,and conducting large-scale clinical trials to validate ctDNAs utility across diverse cancer populations.14With this foundation,sponsors can design clinical investigations to comprehensively analyze each drugs performance i

33、n humans,including pharmacokinetics(PK)variability,pharmacodynamics(PD)effects,therapeutic index(the ratio of the toxic dose to the effective dose)and other safety and tolerability endpoints.These clinical protocols must also account for the influence of potential drug-drug Interactions(DDI)for the

34、combinations starting dosages.The DDI effects can range from additive,where each agent independently contributes to efficacy,to bidirectional,where both agents enhance each others efficacy.Historical E-R relationships and relevant safety and efficacy data are invaluable to DDI assessments.A sponsor

35、then must balance between the selection of the dosing ranges and the number of combinations to evaluate and the trials practical feasibility.This directly impacts the total sample size and resources,and,ultimately,the robustness of the trial outcomes.PROJECT OPTIMUSThe U.S.Food and Drug Administrati

36、on(FDA)Oncology Center of Excellence launched Project Optimus in 2021 to improve“the dose optimization and selection paradigm in oncology drug development.”15 The final guidance,issued in August 2024,emphasizes characterizing dose-response and safety to determine optimal dosages in early phase trial

37、s before starting registrational studies.16 The FDAs goal was to encourage sponsors to move beyond MTD,which had contributed to combination therapies lacking adequate dose and scheduling characterization before they entered registration trials.Instead,the Project emphasizes dose selection that“maxim

38、izes not only the efficacy of a drug but the safety and tolerability as well.”15 The Project offers sponsors a tool kit and opportunities for early development meetings with the FDA Oncology Review Divisions to discuss dose-finding and optimization.The Project also emphasizes that sponsors should de

39、velop strategies that leverage nonclinical and clinical data early in their development programs,including randomized evaluations of dose ranges in early phased |5Efficacy and safety considerationsMaintaining the effective dose of the drug is crucial for regimens combining an investigational agent w

40、ith an approved drug.This helps avoid uncertainty in characterizing the novel agents clinical effects.Sponsors should ensure their protocols address how to measure delayed efficacy,where the therapeutic effects are not immediately apparent.Such efficacy considerations are significant for optimizing

41、combinations involving an IO,where the immune response can vary significantly between patients.Dose optimization also involves understanding each agents safety profile,therapeutic index and stability.A stable safety profile,with consistent short-term and long-term toxicity data,is crucial for planni

42、ng safe dosing for patients.Operational considerationsPlanning operational feasibility is key to successfully fielding and managing dose optimization trials.Sponsors need to establish realistic timelines and resource needs for patient enrollment and monitoring,data collection and readouts,and valida

43、tion and analysis processes.If a sponsor has limited expertise or resources,a CRO can partner to provide expertise,technologies,and staffing to plan for every trial stage and potential issues that may arise when enrolling patients with advanced disease.When selecting sites for fielding a global tria

44、l,sponsors must consider not just the market potential of countries or regions but also their regulatory requirements,dose-optimization and drug class expertise of potential trial sites,and availability of defined patient populations.In particular,global trials involve managing cohorts to control fo

45、r variations in patient profiles while ensuring patient safety and consistent trial site management,this becomes even more critical when combining two novel agents.For example,some regulators may impose country-specific enrollment requirements.When designing a multi-country randomized Phase 1 dose o

46、ptimization study that would include sites in China,the National Medical Products Administration(NMPA)may first require sponsors to provide Phase 1 data on each therapy from a population of Chinese patients.In such studies,sponsors must plan timelines that take into account the specified enrollment

47、criteria enabling the provision of the necessary data.Such considerations will impact the trials overall resources and completion.See Figure 2.Figure 2.Multi-country phase 1/2 dose optimization trial timing of cohort enrollment with required China phase 1 data.China contriubtes to expansion/optimiza

48、tion0Mar-24Apr-24May-24Jun-24Jul-24Aug-24Sep-24Oct-24Nov-24Dec-24Jan-25Feb-255101520253035404550Cohort 5 dose optimization dose 1Cohort 5 dose optimization dose 2Cohort 1Cohort 2China phase 1 cohortCohort 4Cohort 36|Combination Therapy Dose Optimization in Oncology TrialsSponsors also must determine

49、 how to ensure that local sites comply with federal,local and institutional research regulations and how to best harmonize across sites to realize trial efficiencies,such as using centralized laboratories or data monitoring.A CRO can streamline registration trial planning by leveraging established r

50、egulatory relationships and global reach to trial networks with known performance capabilities.Sites with experience managing combination therapy are more likely to successfully recruit and retain patients,ensuring the trial progresses as planned.For safety lead-in and escalation cohorts,which gener

51、ally have fewer participants,sponsors may want to restrict the number of initial sites that are open.However,they must ensure the remaining sites are prepared and able to recruit patients as soon as the safety lead-in endpoint is met or the recommended phase 2 dose is determined or both.The study de

52、sign and drug combination may impact enrollment rates and overall study durations,especially when considering dose escalation.For example,first-in-human drug studies may take longer to enroll and execute due to the required assessment of any adverse events and dose-limiting toxicities.Operational pl

53、anning also must address the needs for biostatistics and data management to support the complexity of the trial with both safety lead-in and dose escalation.Effective data management is essential for ensuring the integrity and reliability of the trial data,which is critical for making informed decis

54、ions on dose optimization.Trial design,feasibility,and execution considerationsDesigning combination trials involves several critical considerations to ensure their feasibility and successful execution.Prioritizing treatment indicationsSelecting the indication or lead indication for dose-optimizatio

55、n of a combination therapy is a critical decision that will impact the overall clinical development plan.Selecting the indication impacts the strategic development of immediate trials in the short term.In the longer term,it impacts expanding the trial to other indications in the same study,if using

56、a platform design,or conducting additional trials.Modeling different approaches to clinical trials helps sponsors plan and prioritize the design,resources and timing for execution.It can also identify how to approach critical choices,noting what decisions permit flexibility.A two-tiered strategy for

57、 site selection may benefit some studies.In this approach,sites are selected for their ability to execute dose escalation evaluations,but another group of sites may be enlisted to refine dose optimization because of their expertise in the target indication.To advance a trial into one or additional i

58、ndications,the protocol requires defined trigger points.Like a safety lead-in and the dose escalation plan,these triggers inform the trials data cuts and safety monitoring requirements.However,triggers also raise questions about whether the optimization decisions and expansion decisions require the

59、same data standards.For example,regulators may request different definitions and standards,which can be spelled out in the protocol and the review requirements.A safety monitoring committee,rather than an independent data monitoring committee,can perform the reviews in most cases.Selecting treatment

60、 settings and goalsSponsors must ensure their trial protocol clearly defines the treatment goals and use setting of the investigational combination therapy.For example,is the goal to prolong the duration of treatment response and delay the onset of treatment resistance?Or is it to increase the depth

61、 of response,such as the degree of tumor shrinkage?|7Trial designs focused on maintaining prolonged efficacy are appropriate when the treatment goal is delaying de novo or acquired resistance.17 For example,a phase 1b trial used safety endpoints as the primary outcome measures and PFS and OS as seco

62、ndary endpoints to evaluate TQB2450,an anti-PD-L1 antibody,combined with anlotinib as a maintenance therapy after definitive chemoradiotherapy in patients with limited-stage small-cell lung cancer.The trial found the combination has manageable adverse events,and promising clinical efficacy,including

63、 100 percent OS and disease control rates and an 87 percent PFS at 12 months.18Trial designs must also account for the dynamic nature of tumor biology,such as a study evaluating a combination therapy for later-line use to reverse acquired resistance from exposure to prior agents.Investigational sett

64、ings that introduce a new agent on top of the prior first-line therapy in a patient population previously exposed to that drug can complicate interpretations of the findings.The evolution of tumor cells can result in tumor subclones that may still respond to the original drug.This overlap can obscur

65、e the independent contribution of the new agent to any observed clinical outcomes.FDA guidance emphasizes the need to demonstrate the efficacy and safety contributions of each individual drug or treatment component to the novel combination.19 Sponsors should consider several aspects when developing

66、their trial strategy,such as the availability of supportive in vivo,in vitro or real world data for each agent and the indications of any approved drugs in the combination.In the case of rare diseases,it may not be feasible to assess the contribution of a component within a study population.In such

67、situations,regulators might agree to use non-clinical data for this purpose,particularly to support a statement that a treatment has no efficacy as a monotherapy.For novel-novel agent combinations,sponsors should consider obtaining monotherapy data for each as part of the phase 1 dose-escalation stu

68、dy.When the combination includes drugs approved for different indications,sponsors should talk with regulators early in the process about how available data might be used to address each drugs contribution in the combination therapy being evaluated.Incorporating a monotherapy run-in with a novel age

69、nt in a combination dose-escalation design may be an option in select cases where data support the selection of a biologically active starting dose.Planning dose escalation Unlike monotherapy dose-escalation studies,combination trials must account for the dose-finding of two or more agents,necessita

70、ting more arms,longer durations,and specialized infrastructure.Consequently,strategic planning is necessary to ensure that protocols are feasible to execute.Employing model-based designs like continual reassessment method(CRM)can help.CRM estimates relationships between dose and toxicities in trials

71、 of monotherapies has some applicability in combination therapy studies.However,ordering the combinations for escalation evaluation might be best served by a CRM that uses a partial order approach(POCRM).20 POCRM pre-specifies the order of dose combinations and then uses CRM on each.21 Two other esc

72、alation designs that perform well for combination therapy evaluations are the model-assisted design combinational bayesian optimal interval design(cBOIN)that sets lower and upper cutoff parameters,and the combinational keyboard design(cKeyboard)that starts with specifying a target toxicity interval.

73、21 The inclusion of a comparator arm needs to be carefully considered and is dependent on several factors,such as the stage of development,targeted indication and“When the combination includes drugs approved for different indications,sponsors should talk with regulators early in the process about ho

74、w available data might be used to address each drugs contribution in the combination therapy being evaluated.”8|Combination Therapy Dose Optimization in Oncology Trialsproposed treatment setting.If a comparator arm is used,the protocol could randomize participants across doses with a standard of car

75、e comparator when possible.22 The trial protocol must also address short-term responses and toxicities.OS,progression-free survival(PFS)or response duration should also be considered when it is feasible because they can provide a robust estimate of efficacy instead of relying on response rate or oth

76、er early estimates,which are rarely a reliable surrogate for long-term outcomes.Of note,the lag time between observable efficacy and safety endpoints may inhibit the feasibility of using efficacy data to guide dose assignments in adaptive trial settings.20,22The protocol should also include screenin

77、g rules that chart when to drop unsafe or ineffective doses and how to enrich enrollment into the remaining dose cohorts so as not to impact overall sample sizes.This will help ensure the trial is powered to make scientifically sound evaluations and reliable conclusions.22WHEN A COMBINATION INCLUDES

78、 AN APPROVED THERAPYSponsors of regimens that add an investigational agent to an approved therapy should consider one of the following four dose escalation designs.11 See Figure 3.The choice between these approaches depends on the pharmacology of the drug class,potential DDIs,E-R relationships,and o

79、verlapping toxicity profiles.The most common scenario with using an approved drug in a combination therapy is to keep its dose fixed and only change the new drug.1.Sequential escalation involves increasing the dose of one drug at a time.The dosing of the investigational agent in the combination shou

80、ld be based on studies of its dose escalation as a monotherapy.The dosing of the approved drug can be its indicated dose or a level lower.Sponsors may be able to perform both the Figure 3.Four dose escalation designs to consider when a combination includes an approved therapy11(1)Sequential escalati

81、on(2)Parallel(staggered)escalationMonotherapyCombinationDose level 2Dose level 1RP2DMonoRP2D-1Mono.RP2DComboRP2D-1MonoRP2D-2MonoMonotherapyCombinationDose level NDose level 1RP2DMonoRP2D-1Mono.RP2DComboDose level N-1Dose level N-2.(4)Monotherapy lead-in(Intra-patient“crossover”)MonotherapyDose level

82、 2Dose level 1RP2DMonoRP2DMonoRP2D-1MonoRP2D-1Mono.Dose level 2Dose level 1.Initiate combinatorial agent*(3)HP FIH prior to FIPdose escalationSelect starting dose in FIPdose escalationDose level NDose level 1Dose level X(MAD).FIH SAD studyin HPs |9monotherapy and combination therapy evaluations in o

83、ne first-in-human(FIH)protocol.This design typically uses one or two dosing cohorts,which can limit E-R data.For example,sequential escalation may be used for a regimen combining two approved therapies anticipated to have an additive effect,such as a cytotoxic drug and a targeted therapy(TT).The tri

84、al starts with a lower dose of TT and the MTD of the cytotoxic agent.The TT dose is escalated to the approved level if the combination is tolerable.This approach is particularly suitable when there are no overlapping toxicities or significant PK interactions between the drugs.Sponsors might employ t

85、his strategy for combinations of other approved therapies,such as hormonal agents,radionuclide therapeutics or antibody-drug conjugates.23Another use of this approach is for regimens that add a novel agent to an approved IO.This design begins with optimizing the novel agent as a monotherapy,followed

86、 by its escalation while maintaining the optimized IO dose and schedule.Understanding any delayed toxicities and E-R relationships for both agents is crucial,and randomized dose-finding strategies,along with patient-reported outcomes,can further refine dose selection.232.Parallel escalation,also ref

87、erred to as staggered,involves increasing the dosage of the investigational agent as a monotherapy and of the combination therapy simultaneously.The combination therapy begins by using the safe and tolerable dose found in the monotherapy arm.This design offers sponsors more E-R data from both arms a

88、nd the possibility of detecting early efficacy signals.Dose-finding for combinations involving anti-PD-1/PD-L1 agents as the foundational backbone often employs a parallel design.3.Healthy participant FIH prior to first-in-patient combination escalation is used in early clinical studies for targeted

89、 agents and immunotherapies when good laboratory practice toxicity data are supportive.This design permits evaluating a single ascending dose(SAD)in healthy participants(HP),garnering biomarker and clinical safety data in the absence of other medicines or illnesses.These data may permit the use of h

90、igher starting doses avoiding subtherapeutic doses in first-in-patient studies.Because of these benefits,the relatively small investment in HP studies can shorten development times and lower overall costs.4.Monotherapy lead-in(intrapatient“crossover”)involves patients receiving the investigative age

91、nt as a monotherapy for a predefined number of cycles or until disease progression.They then can crossover to another cohort to receive the additional drug of the combination regimen.This regimen uses a dose of the approved agent as indicated or adjusted for potential DDI or toxicity.This design can

92、 speed the collection of PK and safety data and may lead to more aggressive starting dosing for the combination therapy escalation.However,it adds complexity to trial operations and data analysis.10|Combination Therapy Dose Optimization in Oncology TrialsWHEN A COMBINATION INCLUDES ONLY NOVEL THERAP

93、IESDose-optimization studies of therapies combining two or more investigational agents may also use these designs,but sponsors should anticipate additional complexities that a CRO can help navigate.11 One design to consider using is a two-dimensional dose escalation.23This innovative trial design em

94、phasizes the importance of a tailored,data-driven approach to dose optimization in combination therapies,leveraging all available data and close collaboration with regulators to enhance efficacy and safety.In the trials initial period,each agent is dose-optimized as a monotherapy in the same populat

95、ion that will be enrolled in the combination therapy trial.When evaluation of the combination therapy begins,one cohort of patients receives a regimen that escalates the dose of one agent(A)while keeping the dose of the other agent(B)constant.In parallel,a second cohort receives escalating doses of

96、agent B while agent As dose is constant.This approach focuses on identifying the dose-response ranges that maximize efficacy and minimize toxicity.The protocol should use Bayesian designs and E-R modeling to ensure the dose ranges tolerability,reveal DDI potential and identify overlaps of toxicities

97、.BACKFILLING CONSIDERATIONSAcross these different escalation designs,sponsors should consider operationalizing cohort backfilling.This step,informed by interim trial analyses,enables enrollment of additional patients to expand existing cohorts and garner more characterization data at dose levels det

98、ermined as safe and well tolerated.23 Backfilling may also help enroll patients with defined molecular tumor subtypes or inform the selection of doses or patient populations for subsequent dose-expansion.Data analysis:Modeling and simulation for decision-makingMIDD leverages both analytic approaches

99、 and simulations to provide a robust framework for evaluating the totality of data and enhancing precision in dose optimization decision-making.A CRO with a skilled pharmacometrics team can help sponsors develop models and simulations tailored to their combination therapys clinical development progr

100、am.E-R modelling and simulation analysis has proven value in both monotherapy and combination therapy dose optimization trials because it helps identify the benefit of the different dosing levels.24 The E-R analysis identifies optimized doses by evaluating variables such as the area under the curve(

101、AUC)for active drug exposure,overall response rate(ORR)for drug efficacy,and adverse events(AE)Graded 3 or higher for drug safety.Data analytics typically use simple regression models to analyze E-R relationships,providing a straightforward approach to understanding the dose-response dynamics.Howeve

102、r,to improve accuracy and reliability,the E-R analysis must consider evaluating covariates and removing confounding factors.For example,patients clinical symptoms,performance status,primary tumor site and inflammatory biomarkers are among the prognostic factors that trials frequently use to predict

103、patient outcomes,yet they may confound E-R for overall survival endpoints.An E-R analysis that doesnt account for confounding factors may deliver false positive E-R relationships that may result in lower dosing that is not optimal.24To address such confounding factors,sponsors should strongly consid

104、er multiple-dose protocols,and a CRO can help develop a practical approach for the appropriate use of resources,given the complexity of the design,higher potential costs and feasibility concerns,particularly in patients with rare cancers.Among the models that help mitigate confounding factors are24

105、Tumor growth inhibition-OS modeling that evaluates tumor dynamics as disease status and a predictor or covariate on OS.This approach permits the separation of disease-specific effects on OS from those that may be related to the |11 Cox-proportional hazards modelling evaluates the association between

106、 OS and hazards/covariates,which can be validated by vetting statistical significance.However,any relationships between the covariates and E-R must be known or estimated.Case-matching modeling evaluates datasets of treatment and control cohorts comprised of patients with similar baseline characteris

107、tics.This approach might not be suitable for trials with very small cohorts and requires screening to bring objectivity to selecting covariates.MIDD for combinations of novel agents,particularly those including IOs or biologics,may simulate E-R by employing quantitative systems pharmacology(QSP)meth

108、ods employing the totality of data.These models integrate data from preclinical testing and clinical PK and PD data to estimate E-R in a variety of patients.The QSP method can help determine any biological or disease-related mechanisms that might account for or influence patient responses.9,23Conclu

109、sion As combination therapies redefine the oncology landscape,dose optimization emerges as a pivotal determinant of clinical and commercial success.Sponsors face mounting pressure from regulators,clinicians,and patients to move beyond traditional paradigms and embrace data-rich,patient-centered stra

110、tegies that maximize therapeutic value.Sponsors must integrate translational science,adaptive trial designs,and model-informed drug development to meet the evolving standards of initiatives like FDAs Project Optimus.By collaborating with experienced CRO partners such as IQVIA,biotech and pharmaceuti

111、cal companies can accelerate their development of optimized,effective,and well-tolerated combination regimens that align with regulatory expectations and,most importantly,improve outcomes for patients with cancer.12|Combination Therapy Dose Optimization in Oncology Trials 1.U.S.Food and Drug Adminis

112、tration.FDA approves inavolisib with palbociclib and fulvestrant for endocrine-resistant,PIK3CA-mutated,HR-positive,HER2-negative,advanced breast cancer.FDA.October 10,2024.https:/www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-inavolisib-palbociclib-and-fulvestrant-endocrine-res

113、istant-pik3ca-mutated-hr-positive.2.Genentech.New England Journal of Medicine publishes landmark Phase III results for Genentechs Itovebi,showing more than doubling of progression-free survival in certain type of HR-positive advanced breast cancer.Genentech press release.October 30,2024.https:/ EY,R

114、ai M,Tadikonda Y,et al.Trends in complexity of single-agent and combination therapies for solid tumor cancers approved by the U.S.Food and Drug Administration.Oncologist.2025;30(3):oyae302.doi:10.1093/oncolo/oyae302.4.ClinicalTrials.gov.Search of:combination immunotherapy AND cancer.U.S.National Lib

115、rary of Medicine.Accessed April 12,2025.https:/clinicaltrials.gov/search?cond=cancer&intr=combination%20immunotherapy.5.U.S.Food and Drug Administration.Project FrontRunner.Revised December 16,2024.https:/www.fda.gov/about-fda/oncology-center-excellence/project-frontrunner.6.Cancer Research Institut

116、e.Immunotherapy by Treatment Types.Cancer Research Institute.Accessed April 12,2025.https:/www.cancerresearch.org/immunotherapy-by-treatment-types.7.Kuick Research.Global Combination Cancer Immunotherapy Market Opportunity and Clinical Trials Insight 2028.Kuick Research.June 9,2022.https:/ RK,Guo C,

117、Drescher SK,Yin D.Oncology dose optimization paradigms:knowledge gained and extrapolated from approved oncology therapeutics.Cancer Chemother Pharmacol.2022;90(3):207-216.doi:10.1007/s00280-022-04444-0.9.Venkatakrishnan K,Jayachandran P,Seo SK,van der Graaf PH,Wagner JA,Gupta N.Moving the Needle for

118、 Oncology Dose Optimization:A Call for Action.Clin Pharmacol Ther.2024;115(6):1187-1197.doi:10.1002/cpt.3263.10.Jiang L,Yuan Y.Seamless phase II/III design:a useful strategy to reduce the sample size for dose optimization.J Natl Cancer Inst.2023;115(9):1092-1098.doi:10.1093/jnci/djad103.11.Zhou L,Re

119、ddy MB,Mittapalli RK,Yang J,Yin D.Oncology Combination Dose-Finding Study Design for Targeted and Immuno-Oncology Therapies.Clin Pharmacol Ther.2024;115(1):29-35.doi:10.1002/cpt.3085.12.Samineni D,Venkatakrishnan K,Othman AA,et al.Dose Optimization in Oncology Drug Development:An International Conso

120、rtium for Innovation and Quality in Pharmaceutical Development White Paper.Clin Pharmacol Ther.2024;116(3):531-545.doi:10.1002/cpt.3298.References |13 13.Hernando-Calvo A,Garralda E.Patient-Centric Approaches for Phase I Combination Trials Come on Stage.Cancer Discov.2023;13(8):1762-1764.doi:10.1158

121、/2159-8290.CD-23-0534.14.Bartolomucci A,Nobrega M,Ferrier T,et al.Circulating tumor DNA to monitor treatment response in solid tumors and advance precision oncology.NPJ Precis Oncol.2025;9(1):84.Published 2025 Mar 24.doi:10.1038/s41698-025-00876-y.15.U.S.Food and Drug Administration.Project Optimus.

122、FDA.Updated December 6,2024.https:/www.fda.gov/about-fda/oncology-center-excellence/project-optimus.16.U.S.Food and Drug Administration.Optimizing the Dosage of Human Prescription Drugs and Biological Products for the Treatment of Oncologic Diseases.August 2024.https:/www.fda.gov/media/164555/downlo

123、ad.17.Lopez JS,Banerji U.Combine and conquer:challenges for targeted therapy combinations in early-phase trials.Nat Rev Clin Oncol.2017;14(1):57-66.doi:10.1038/nrclinonc.2016.96.18.Liu X,Yin X,Zhuang L,et al.Efficacy and safety of TQB2450 combined with anlotinib as maintenance therapy for LS-SCLC af

124、ter definitive concurrent or sequential chemoradiotherapy:a prospective phase Ib study.BMC Cancer.2025;25(1):509.Published 2025 Mar 20.doi:10.1186/s12885-025-13885-8.19.U.S.Food and Drug Administration.Codevelopment of Two or More New Investigational Drugs for Use in Combination.June 2013.https:/www

125、.fda.gov/files/drugs/published/Codevelopment-of-Two-or-More-New-Investigational-Drugs-for-Use-in-Combination.pdf.20.Wages NA,Dillon PM,Portell CA,Slingluff CL Jr,Petroni GR.Applications of the partial-order continual reassessment method in the early development of treatment combinations.Clin Trials.

126、2024;21(3):331-339.doi:10.1177/17407745241234634.21.Wang S,Sayour E,Lee JH.Evaluation of phase I clinical trial designs for combinational agents along with guidance based on simulation studies.J Appl Stat.2022;50(9):2055-2078.Published 2022 Aug 3.doi:10.1080/02664763.2022.2105827.22.Thall PF,Zang Y,

127、Chapple AG,et al.Novel Clinical Trial Designs with Dose Optimization to Improve Long-term Outcomes.Clin Cancer Res.2023;29(22):4549-4554.doi:10.1158/1078-0432.CCR-23-2222.23.Yap TA,Bullock J,Chong S,et al.Oncology Combination Drug Development Strategies for Project Optimus.Clin Cancer Res.2024;30(23

128、):5237-5241.doi:10.1158/1078-0432.CCR-24-1836.24.Kawakatsu S,Bruno R,Kgedal M,et al.Confounding factors in exposure-response analyses and mitigation strategies for monoclonal antibodies in oncology.Br J Clin Pharmacol.2021;87(6):2493-2501.doi:10.1111/bcp.14662.2025.All rights reserved.IQVIA is a registered trademark of IQVIA Inc.in the United States,the European Union,and various other countries.05.2025.RDS.BCS2025-1266-05MAYCONTACT US