Master protocols and other innovative trial designs in inflammation and immunology to expedite clinical drug development.

Master protocol designs, such as umbrella and basket studies, allow multiple compounds or multiple target populations to be evaluated simultaneously within a single protocol, and have been widely adopted in oncology clinical trials. These novel designs can also be applied in other therapeutic areas, where they could have several benefits over conducting traditional randomized controlled trials. Here, we detail Pfizer's recent implementations of master protocol designs in inflammation and immunology clinical studies, focusing on the opportunities for cost and resource savings and how these designs can expedite the time required to bring new treatments to patients in need.

Combination MCP-Mod for two-drug combination dose-ranging studies.

Combination therapies with multiple mechanisms of action can offer improved efficacy and/or safety profiles when compared to a single therapy with one mechanism of action. Consequently, the number of combination therapy studies have increased multi-fold, both in oncology and non-oncology indications. However, identifying the optimal doses of each drug in a combination therapy can require a large sample size and prolong study timelines, especially when full factorial designs are used. In this paper, we extend the MCP-Mod design of Bretz, Pinheiro, and Branson to a three-dimensional space to model the dose-response surface of a two-drug combination under the framework of Combination (Comb) MCP-Mod. The resulting model yields a set of dosages for each drug in the combination that elicits the target response so that an optimal dose for the combination can be selected for pivotal studies. We construct three-dimensional dose-response models for the combination and formulate the contrast test statistic to select the best model, which can then be used to select the optimal dose. Guidance to calculate power and sample size calculations are provided to assist study design. Simulation studies show that Comb MCP-Mod performs as well as the conventional multiple comparisons approach in controlling the family-wise error rate at the desired alpha level. However, Comb MCP-Mod is more powerful than the classical multiple comparisons approach in detecting dose-response relationships when treatment is non-null. The probability of correctly identifying the underlying dose-response relationship is generally higher when using Comb MCP-Mod than when using the multiple comparisons approach.

Safety, Tolerability, and Pharmacokinetics of Single and Multiple Ascending Intravenous Infusions of PF-07304814 (Lufotrelvir) in Participants Hospitalized With COVID-19.

Background: An urgent need remains for antiviral therapies to treat patients hospitalized with COVID-19. PF-07304814-the prodrug (lufotrelvir) and its active moiety (PF-00835231)-is a potent inhibitor of the SARS-CoV-2 3CL protease. Method: Eligible participants were 18 to 79 years old and hospitalized with confirmed COVID-19. This first-in-human phase 1b study was designed with 2 groups: single ascending dose (SAD) and multiple ascending dose (MAD). Participants could receive local standard-of-care therapy. In SAD, participants were randomized to receive a 24-hour infusion of lufotrelvir/placebo. In MAD, participants were randomized to receive a 120-hour infusion of lufotrelvir/placebo. The primary endpoint was to assess the safety and tolerability of lufotrelvir. The secondary endpoint was to evaluate the pharmacokinetics of lufotrelvir and PF-00835231. Results: In SAD, participants were randomized to receive 250 mg lufotrelvir (n = 2), 500 mg lufotrelvir (n = 2), or placebo (n = 4) by continuous 24-hour infusion. In MAD, participants were randomized to receive 250 mg lufotrelvir (n = 7), 500 mg lufotrelvir (n = 6), or placebo (n = 4) by continuous 120-hour infusion. No adverse events or serious adverse events were considered related to lufotrelvir. At doses of 250 and 500 mg, concentrations for the prodrug lufotrelvir and active moiety PF-00835231 increased in a dose-related manner. Unbound concentrations of the lufotrelvir active metabolite reached steady state approximately 2- and 4-fold that of in vitro EC90 following 250- and 500-mg doses, respectively. Conclusions: These safety and pharmacokinetic findings support the continued evaluation of lufotrelvir in clinical studies. Clinical Trials Registration. ClinicalTrials.gov NCT04535167.

Innovative Randomized Phase I Study and Dosing Regimen Selection to Accelerate and Inform Pivotal COVID-19 Trial of Nirmatrelvir.

Coronavirus disease 2019 (COVID-19) is a continued leading cause of hospitalization and death. Safe, efficacious COVID-19 antivirals are needed urgently. Nirmatrelvir (PF-07321332), the first orally bioavailable, severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) Mpro inhibitor against the coronaviridae family, has demonstrated potent preclinical antiviral activity and benign safety profile. We report safety, tolerability, and pharmacokinetic data of nirmatrelvir with and without ritonavir as a pharmacokinetic enhancer, from an accelerated randomized, double-blind, placebo-controlled, phase I study. Two interleaving single-ascending dose (SAD) cohorts were evaluated in a three-period crossover. Multiple-ascending dose (MAD) with nirmatrelvir/ritonavir twice daily (b.i.d.) dosing was evaluated over 10 days in five parallel cohorts. Safety was assessed, including in a supratherapeutic exposure cohort. Dose and dosing regimen for clinical efficacy evaluation in phase II/III clinical trials were supported by integrating modeling and simulations of SAD/MAD data with nonclinical data and a quantitative systems pharmacology model (QSP). In SAD, MAD, and supratherapeutic exposure cohorts, nirmatrelvir/ritonavir was safe and well-tolerated. Nirmatrelvir exposure and half-life were considerably increased by ritonavir, enabling selection of nirmatrelvir/ritonavir dose and regimen for phase II/III trials (300/100 mg b.i.d.), to achieve concentrations continuously above those required for 90% inhibition of viral replication in vitro. The QSP model suggested that a 5-day regimen would significantly decrease viral load in SARS-CoV-2-infected patients which may prevent development of severe disease, hospitalization, and death. In conclusion, an innovative and seamless trial design expedited establishment of phase I safety and pharmacokinetics of nirmatrelvir/ritonavir, enabling high confidence in phase II/III dose selection and accelerated pivotal trials' initiation (NCT04756531).

Achieving end-to-end success in the clinic: Pfizer's learnings on R&D productivity.

Over the past decade, Pfizer has focused efforts to improve its research and development (R&D) productivity. By the end of 2020, Pfizer had achieved an industry-leading clinical success rate of 21%, a tenfold increase from 2% in 2010 and well above the industry benchmark of ∼11%. The company had also maintained the quality of innovation, because 75% of its approvals between 2016 and 2020 had at least one expedited regulatory designation (e.g., Breakthrough Therapy). Pfizer's Signs of Clinical Activity (SOCA) paradigm enabled better decision-making and, along with other drivers (biology and modality), contributed to this productivity improvement. These laid a strong foundation for the rapid and effective development of the Coronavirus 2019 (COVID-19) vaccine with BioNTech, as well as the antiviral candidate Paxlovid™, under the company's 'lightspeed' paradigm.

Clinical dose-response for a broad set of biological products: A model-based meta-analysis.

Characterizing clinical dose-response is a critical step in drug development. Uncertainty in the dose-response model when planning a dose-ranging study can often undermine efficiency in both the design and analysis of the trial. Results of a previous meta-analysis on a portfolio of small molecule compounds from a large pharmaceutical company demonstrated a consistent dose-response relationship that was well described by the maximal effect model. Biologics are different from small molecules due to their large molecular sizes and their potential to induce immunogenicity. A model-based meta-analysis was conducted on the clinical efficacy of 71 distinct biologics evaluated in 91 placebo-controlled dose-response studies published between 1995 and 2014. The maximal effect model, arising from receptor occupancy theory, described the clinical dose-response data for the majority of the biologics (81.7%, n = 58). Five biologics (7%) with data showing non-monotonic trend assuming the maximal effect model were identified and discussed. A Bayesian model-based hierarchical approach using different joint specifications of prior densities for the maximal effect model parameters was used to meta-analyze the whole set of biologics excluding these five biologics ( n = 66). Posterior predictive distributions of the maximal effect model parameters were reported and they could be used to aid the design of future dose-ranging studies. Compared to the meta-analysis of small molecules, the combination of fewer doses, narrower dosing ranges, and small sample sizes further limited the information available to estimate clinical dose-response among biologics.

Advancing cancer drug development through precision medicine and innovative designs.

Precision medicine has been a hot topic in drug development over the last decade. Biomarkers have been proven useful for understanding the disease progression and treatment response in precision medicine development. Advancement of high-throughput omics technologies has enabled fast identification of molecular biomarkers with low cost. Although biomarkers have brought many promises to drug development, steep challenges arise due to a large amount of data, complexity of technology, and lack of full understanding of biology. In this article, we discuss the technologies and statistical issues that are related to omics biomarker discovery. We also provide an overview of the current development of biomarker-enabled cancer clinical trial designs.

Ethical Considerations in Adaptive Design Clinical Trials.

Adaptive design clinical trial methodologies offer both opportunities and challenges for observing basic ethical principles in human subject research. Using both published and unpublished adaptive design clinical trials, we have selected and reviewed examples of clinical trials with different design adaptations to discuss the ethical obstacles presented and often successfully resolved by these approaches, including (1) confirmatory trials for treatments widely accepted on the basis of uncontrolled case series or open-label trials (clinical equipoise and "justice" in the sense of which trial groups will "receive the benefits of research and bear its burdens") (infantile hemangioma/propranolol); (2) interim results analysis by unblinded data monitoring committees ("withholding information necessary to make a considered judgment" ["respect for persons"] versus compromising the trial's scientific basis) (BIG 1-98); (3) adaptations involving sample size reassessment or dose adjustment via dropping or adding treatment arms, allowing fewer subjects to produce statistically significant results, fewer subjects treated with ineffective/toxic doses, and more subjects given doses showing tolerance and treatment activity ("beneficence" or "protecting from harm and making efforts to secure wellbeing") (ECMO, Neuromyelitis Optica); (4) adaptive randomization inferential problems balanced against ethical benefits (trastuzumab vs taxane in advanced gastric cancer; ADVENT); (5) more efficient allocation of societal resources for research, in both public and commercial realms, versus uncertain regulatory acceptance (indicaterol; VALOR); and (6) platform, umbrella, and basket trials offering additional efficiencies (I-SPY II, BATTLE, Lung-MAP). The importance of careful design, meticulous planning, and rigorous ethical review of adaptive design trials on a case-by-case basis cannot be overemphasized.

Safety and Efficacy of SBI-087, a Subcutaneous Agent for B Cell Depletion, in Patients with Active Rheumatoid Arthritis: Results from a Phase II Randomized, Double-blind, Placebo-controlled Study.

OBJECTIVE: To evaluate subcutaneous SBI-087 to treat rheumatoid arthritis (RA). METHODS: A total of 210 adult patients with active RA were randomized to receive either 200 mg SBI-087 or placebo (Pbo), according to one of these patterns: SBI/Pbo/Pbo (SBI on Day 1), SBI/SBI/Pbo (SBI days 1 and 15), SBI/Pbo/SBI (SBI days 1 and 84), SBI/SBI/SBI (SBI days 1, 15, and 84), or Pbo/Pbo/Pbo (Pbo all 3 days). All patients were seropositive and taking background methotrexate. The primary endpoint was proportion of patients achieving 20% improvement from baseline at Week 16 by American College of Rheumatology criteria (ACR20). Other outcomes included 28-joint Disease Activity Score (DAS28)-C-reactive protein (CRP), physician's and patient's global assessments of disease activity (PGA and PtGA, respectively) and Health Assessment Questionnaire-Disability Index (HAQ-DI). Peripheral CD19+ B cells were measured by high-sensitivity flow cytometer. Statistical significance was set at 2-sided α 0.10 level. RESULTS: The SBI/SBI/SBI group demonstrated significant improvement in ACR20 and DAS28-CRP from Week 8 onward, sustained improvement in CRP levels from Week 12 onward, and significant improvements in PGA and PtGA in weeks 16 through 24, and in HAQ-DI at Week 24. The SBI/Pbo/Pbo and SBI/SBI/Pbo groups did not meet the primary endpoint but demonstrated improvements in several secondary endpoints. All treatment groups exhibited depletion of peripheral CD19+ B cells throughout the study. Overall, 61.5% of patients receiving SBI-087 and 55.0% of patients receiving Pbo reported adverse events. CONCLUSION: SBI-087 effectively depleted peripheral CD20 B cells and was well tolerated. Improvements were consistently observed in the SBI/SBI/SBI group for the majority of efficacy and quality-of-life outcomes.

Safety, Tolerability, Pharmacokinetic and Pharmacodynamic Properties of SBI-087, a CD20-Directed B-cell Depleting Agent: Phase 1 Dose Escalating Studies in Patients With Either Mild Rheumatoid Arthritis or Systemic Lupus.

PURPOSE: SBI-087 is a Small Modular Immunopharmaceutical Protein™(SMIP™) drug that binds to CD20 and has been reported to deplete B cells in murine/primate studies. The safety, tolerability and pharmacokinetic/pharmacodynamic properties of SBI-087 were evaluated in patients with rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE). METHODS: Single-dose SBI-087 was evaluated in 2 Phase I, open-label, escalating-dose studies in patients with RA or SLE. The studies included 6 IV/4 SC escalating doses (RA) and 1 IV/4 SC escalating doses (SLE). Escalation was determined by tolerability/rate of B-cell depletion. Serum was collected for analyses of pharmacokinetic and pharmacodynamic (CD19(+) B cells) properties and immunogenicity. Patients were followed until B-cell counts were normalized or stabilized. Safety, tolerability was evaluated from adverse events, physical examinations, vital sign measurements, ECG, and clinical laboratory results. FINDINGS: Sixty patients with RA (IV, 28; SC, 32) and 30 patients with SLE (6 per cohort) were enrolled. Mild to moderate infusion reactions occurred in several patients at the top doses in the RA study despite a pretreatment regimen of IV doses. Unanticipated reactions after SC administration of SBI-087 included fever, chills, and malaise, seen on the day of dosing in the lowest-dose cohorts in both studies. These events were abrogated in subsequent cohorts by a pre/postdose treatment regimen consisting of oral corticosteroids, acetaminophen, and an antihistamine. SBI-087 clearance (IV) ranged from 22 to 229 mL/h; volume of distribution at steady state ranged from 5 to 12 L. Apparent clearance (SC) ranged from 44.7 to 105 mL/h; volume of distribution ranged from 14.3 to 32.1 L. Overall, PK properties were similar at equivalent doses between IV/SC administrations in patients with RA/SLE. Mean t½ (IV) ranged from 2.1 to 10.7 days (less at lower doses). SBI-087 concentration and B-cell depletion were generally dose proportional across IV and SC cohorts. However, the extent of B-cell depletion was less, and rate of repletion was faster, in patients with SLE versus RA. In both studies, B-cell repletion to baseline did not occur in the majority of patients by the end of the observation period. Overall, the prevalence and type of adverse events were similar to those seen with other anti-CD20-depleting agents. IMPLICATIONS: In patients with mild RA/SLE, SBI-087 was well tolerated when administered intravenously or subcutaneously with pre- and posttreatment regimens. B-cell depletion is long lasting, and the duration and extent of depletion may be greater in RA compared with SLE. SBI-087 exhibited slow elimination and low distribution in both populations. Clinicaltrials.gov identifiers: NCT00641225 (RA) and NCT00714116 (SLE).

Biomarker informed add-arm design for unimodal response.

In this article, we propose a biomarker informed add-arm design for unimodal response. The new design contributes to optimizing the procedure of dose-finding when a biomarker of the study primary endpoint exists and prior evidence indicates a unimodal dose-response relationship. Designs with up to seven active treatment arms were considered. We propose the statistical approach for the Type I error control and carry out extensive simulation studies for the power performance of the design. The proposed design is shown to outperform the corresponding biomarker informed two-stage winner design in power on an average.

On model selections for repeated measurement data in clinical studies.

Repeated measurement designs have been widely used in various randomized controlled trials for evaluating long-term intervention efficacies. For some clinical trials, the primary research question is how to compare two treatments at a fixed time, using a t-test. Although simple, robust, and convenient, this type of analysis fails to utilize a large amount of collected information. Alternatively, the mixed-effects model is commonly used for repeated measurement data. It models all available data jointly and allows explicit assessment of the overall treatment effects across the entire time spectrum. In this paper, we propose an analytic strategy for longitudinal clinical trial data where the mixed-effects model is coupled with a model selection scheme. The proposed test statistics not only make full use of all available data but also utilize the information from the optimal model deemed for the data. The performance of the proposed method under various setups, including different data missing mechanisms, is evaluated via extensive Monte Carlo simulations. Our numerical results demonstrate that the proposed analytic procedure is more powerful than the t-test when the primary interest is to test for the treatment effect at the last time point. Simulations also reveal that the proposed method outperforms the usual mixed-effects model for testing the overall treatment effects across time. In addition, the proposed framework is more robust and flexible in dealing with missing data compared with several competing methods. The utility of the proposed method is demonstrated by analyzing a clinical trial on the cognitive effect of testosterone in geriatric men with low baseline testosterone levels.

An Adaptive Staggered Dose Design for a Normal Endpoint.

In a clinical trial where several doses are compared to a control, a multi-stage design that combines both the selection of the best dose and the confirmation of this selected dose is desirable. An example is the two-stage drop-the-losers or pick-the-winner design, where inferior doses are dropped after interim analysis. Selection of target dose(s) can be based on ranking of observed effects, hypothesis testing with adjustment for multiplicity, or other criteria at interim stages. A number of methods have been proposed and have made significant gains in trial efficiency. However, many of these designs started off with all doses with equal allocation and did not consider prioritizing the doses using existing dose-response information. We propose an adaptive staggered dose procedure that allows explicit prioritization of doses and applies error spending scheme that favors doses with assumed better responses. This design starts off with only a subset of the doses and adaptively adds new doses depending on interim results. Using simulation, we have shown that this design performs better in terms of increased statistical power than the drop-the-losers design given strong prior information of dose response.

Protein expression of the chemokine receptor CXCR4 and its ligand CXCL12 in primary cutaneous melanoma--biomarkers of potential utility?

Dysregulation of the CXCR4/CXCL12 axis, relevant in melanoma progression, activates cell cycle progression and migration via stimulation of the MAPK pathway. We sought to ascertain the cooperativity of the CXCR4/CXCL12 axis with established prognosticators and BRAF status in melanoma. Samples (n = 107) of primary cutaneous melanoma were assessed for protein expression of CXCR4 and CXCL12, and molecular analyses were performed to ascertain BRAF status. Univariate analyses of CXCR4 protein showed that the proportion of CXCR4 positives was greater in melanomas with absence of mitoses (P < .0001), absence of ulceration (P = .0008), and absence of regression (P = .02). Patients presenting at shallower stages (American Joint Committee on Cancer [AJCC] 1-2) exhibited a larger proportion of CXCR4 positives (76.9%, P < .0001 and 69.0%, P = .008), whereas those at deeper stages (AJCC 3-4) exhibited a larger proportion of negatives (75.0%, P = .004 and 66.7%, P = .22). In a multivariate analysis, lower odds of CXCR4 protein expression were associated with AJCC stage 3 (odds ratio [OR]=0.16, P = .01), AJCC stage 4 (OR=0.17, P = .04), and mitoses (OR=0.21, P = .01). Univariate analyses of CXCL12 protein showed that the proportion of CXCL12 negatives was significantly smaller in melanomas with depth of at least 1 mm, absence of ulceration, and absence of vascular invasion (P < .0001 for all). CXCR4 and CXCL12 appear to be biomarkers associated with established prognosticators of good and poor clinical outcome, respectively, in primary cutaneous melanoma. A BRAF mutation does not appear to be associated with CXCR4/CXCL12 axis upregulation in primary cutaneous melanoma.

Inference of equivalence for the ratio of two normal means with unspecified variances.

Equivalence trials aim to demonstrate that new and standard treatments are equivalent within predefined clinically relevant limits. We focus on when inference of equivalence is made in terms of the ratio of two normal means. In the presence of unspecified variances, methods such as the likelihood-ratio test use sample estimates for those variances; Bayesian models integrate them out in the posterior distribution. These methods limit the knowledge on the extent to which equivalence is affected by variability of the parameter of interest. In this article, we propose a likelihood approach that retains the unspecified variances in the model and partitions the likelihood function into two components: F-statistic function for variances, and t-statistic function for the ratio of two means. By incorporating unspecified variances, the proposed method can help identify a numeric range of variances where equivalence is more likely to be achieved, which cannot be accomplished by current analysis methods. By partitioning the likelihood function into two components, the proposed method provides more inference information than a method that relies solely on one component. Using a published set of real example data, we show that the proposed method produces the same results as the likelihood-ratio test and is comparable to Bayesian analysis in the general case. In a special case where the ratio of two variances is directly proportional to the ratio of two means, the proposed method yields better results in inference about equivalence than either the likelihood-ratio test or the Bayesian method. Using a published set of real example data, the proposed likelihood method is shown to be a better alternative than current analysis methods for equivalence inference.

Covariate effect on constancy assumption in noninferiority clinical trials.

Noninferiority (NI) clinical trials are getting a lot of attention of late due to their direct application in biosimilar studies. Because of the missing placebo arm, NI is an indirect approach to demonstrate efficacy of a test treatment. One of the key assumptions in the NI test is the constancy assumption, that is, that the effect of the reference treatment is the same in current NI trials as in historical superiority trials. However, if a covariate interacts with the treatment arms, then changes in distribution of this covariate will likely result in violation of constancy assumption. In this article, we propose four new NI methods and compare them with two existing methods to evaluate the change of background constancy assumption on the performance of these six methods. To achieve this goal, we study the impact of three elements-(1) strength of covariate, (2) degree of interaction between covariate and treatment, and (3) differences in distribution of the covariate between historical and current trials-on both the type I error rate and power using three different measures of association: difference, log relative risk, and log odds ratio. Based on this research, we recommend using a modified covariate-adjustment fixed margin method.

Inference of bioequivalence for log-normal distributed data with unspecified variances.

Two drugs are bioequivalent if the ratio of a pharmacokinetic (PK) parameter of two products falls within equivalence margins. The distribution of PK parameters is often assumed to be log-normal, therefore bioequivalence (BE) is usually assessed on the difference of logarithmically transformed PK parameters (δ). In the presence of unspecified variances, test procedures such as two one-sided tests (TOST) use sample estimates for those variances; Bayesian models integrate them out in the posterior distribution. These methods limit our knowledge on the extent that inference about BE is affected by the variability of PK parameters. In this paper, we propose a likelihood approach that retains the unspecified variances in the model and partitions the entire likelihood function into two components: F-statistic function for variances and t-statistic function for δ. Demonstrated with published real-life data, the proposed method not only produces results that are same as TOST and comparable with Bayesian method but also helps identify ranges of variances, which could make the determination of BE more achievable. Our findings manifest the advantages of the proposed method in making inference about the extent that BE is affected by the unspecified variances, which cannot be accomplished either by TOST or Bayesian method.

A Practical Guide to Data Monitoring Committees in Adaptive Trials.

Adaptive clinical trials require access to interim data to carry out trial modification as allowed by a prespecified adaptation plan. A data monitoring committee (DMC) is a group of experts that is charged with monitoring accruing trial data to ensure the safety of trial participants and that in adaptive trials may also play a role in implementing a preplanned adaptation. In this paper, we summarize current practices and viewpoints and provide guidance on evolving issues related to the use of DMCs in adaptive trials. We describe the common types of adaptive designs and point out some DMC-related issues that are unique to this class of designs. We include 3 examples of DMCs in late-stage adaptive trials that have been implemented in practice. We advocate training opportunities for researchers who may be interested in serving on a DMC for an adaptive trial since qualified DMC members are fundamental to the successful execution of DMC responsibilities.

Design of oncology clinical trials: a review.

Cancer is a disease that occurs due to the uncontrolled multiplication of cells that invade nearby tissues and can spread to other parts of the body. An increased incidence of cancer in the world has led to an increase in oncology research and in the number of oncology trials. Well designed oncology clinical trials are a key part of developing effective anti-cancer drugs. This review focuses on statistical considerations in the design and analysis of oncology clinical trials.

Corrected profile likelihood confidence interval for binomial paired incomplete data.

Clinical trials often use paired binomial data as their clinical endpoint. The confidence interval is frequently used to estimate the treatment performance. Tang et al. (2009) have proposed exact and approximate unconditional methods for constructing a confidence interval in the presence of incomplete paired binary data. The approach proposed by Tang et al. can be overly conservative with large expected confidence interval width (ECIW) in some situations. We propose a profile likelihood-based method with a Jeffreys' prior correction to construct the confidence interval. This approach generates confidence interval with a much better coverage probability and shorter ECIWs. The performances of the method along with the corrections are demonstrated through extensive simulation. Finally, three real world data sets are analyzed by all the methods. Statistical Analysis System (SAS) codes to execute the profile likelihood-based methods are also presented.