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Background and Objective Proprotein convertase subtilisin/kexin type 9 inhibition with monoclonal antibodies such as alirocumab significantly reduces low-density lipoprotein-cholesterol levels ± other lipid-lowering therapies. We aimed to develop and qualify a population pharmacokinetics (PopPK) model for alirocumab in healthy subjects and patients, taking into account the mechanistic target-mediated drug disposition (TMDD) process. Methods This TMDD model was developed using a subset of the alirocumab clinical trial database, including nine phase I/II/III studies ( n  = 527); the model was subsequently expanded to a larger data set of 13 studies ( n  = 2870). Potential model parameters and covariate relationships were explored, and predictive ability was qualified using a visual predictive check. Results The TMDD model was built using the quasi-steady-state approximation. The final TMDD–quasi-steady-state model included a significant relationship between distribution volume of the central compartment and disease state: distribution volume of the central compartment was 1.56-fold higher in patients vs. healthy subjects. Separately, application of the model to the expanded data set revealed a significant relationship between linear clearance and statin co-administration: linear clearance was 1.27-fold higher with statins. The good predictive performance of the TMDD model was assessed based on graphical and numerical quality criteria, together with the visual predictive check and comparison of the predictions to those from a PopPK model with parallel linear and Michaelis–Menten clearances (i.e., simplification of the TMDD PopPK model). Conclusions This mechanistic TMDD PopPK model integrates the interaction of alirocumab with its target and accurately predicts both alirocumab and total proprotein convertase subtilisin/kexin type 9 concentrations in healthy subjects and patients.

This paper proposes a two-stage phase I-II clinical trial design to optimize doseschedule regimes of an experimental agent within ordered disease subgroups in terms of the toxicity-efficacy trade-off. The design is motivated by settings where prior biological information indicates it is certain that efficacy will improve with ordinal subgroup level. We formulate a flexible Bayesian hierarchical model to account for associations among subgroups and regimes, and to characterize ordered subgroup effects. Sequentially adaptive decisionmaking is complicated by the problem, arising from the motivating application, that efficacy is scored on day 90 and toxicity is evaluated within 30 days from the start of therapy, while the patient accrual rate is fast relative to these outcome evaluation intervals. To deal with this in a practical manner, we take a likelihood-based approach that treats unobserved toxicity and efficacy outcomes as missing values, and use elicited utilities that quantify the efficacy-toxicity trade-off as a decision criterion. Adaptive randomization is used to assign patients to regimes while accounting for subgroups, with randomization probabilities depending on the posterior predictive distributions of utilities. A simulation study is presented to evaluate the design’s performance under a variety of scenarios, and to assess its sensitivity to the amount of missing data, the prior, and model misspecification.

Background Combination therapies involving novel agents, such as immunotherapies and targeted therapies, offer significant antitumor benefits by increasing dose intensity, targeting multiple pathways, and benefiting a broader patient population. To further explore these advantages, the National Cancer Institute (NCI) has initiated Combination Therapy Platform Trial with Molecular Analysis for Therapy Choice (ComboMATCH) to evaluate the effectiveness of new drug combinations in treating both adults and children. However, designing dose optimization trials for these combination therapies presents substantial challenges due to the complex interactions and unique mechanisms of action. Methods To address these challenges, we propose COMPACT, a Bayesian phase I-II randomized design for combination cancer therapies that uses progression-free survival (PFS) as the primary efficacy endpoint to identify the optimal dose combination (ODC) based on restricted mean survival time (RMST). The COMPACT design jointly evaluates both toxicity and PFS, with continuous toxicity monitoring throughout the trial. Toxicity probabilities are modeled using a partial ordering assumption without relying on complex parametric models, while PFS is modeled through a Bayesian Pareto proportional hazards model with gamma-shared frailty. The trial consists of two seamlessly connected stages. In the first stage, the dose space is explored primarily based on toxicity, while PFS data are concurrently collected. In the second stage, patients are adaptively randomized to safe and potentially promising dose combinations based on PFS, and the dose combination with the highest RMST among those deemed safe is selected as the ODC. Results Simulation studies demonstrate that COMPACT has desirable operating characteristics and outperforms conventional designs in identifying the ODC, allocating more patients to ODC, while maintaining patient safety. Sensitivity analysis is performed to examine the robustness of the proposed design. A trial example is provided to facilitate the practical implementation of the proposed COMPACT design. Conclusions The proposed COMPACT design offers a novel and robust framework for combination cancer therapies with progression-free survival end point.

Introduction Patellar tendon overuse injuries are common in athletes. Imaging may show a change in tissue structure with tendon thickening and disruption of the intratendinous substance. We wish to test the hypothesis that both autologous bone marrow expanded mesenchymal stem cells and autologous leukocyte-poor platelet-rich plasma (LP-PRP) implanted into the area of the disrupted tendinopathic patellar tendon will restore function, but tendon regeneration tissue will only be observed in the subjects treated with autologous bone marrow expanded mesenchymal stem cells. Methods and analysis This is a single-centre, pilot phase I/II, double-blinded clinical trial with randomisation with active control. Twenty patients with a diagnosis of patellar tendinopathy with imaging changes (tendon thickening and disruption of the intratendinous substance at the proximal portion of the patellar tendon) will be randomised in a 1:1 ratio to receive a local injection of either bone-marrow autologous mesenchymal stem cells (MSC), isolated and cultured under GMP at T he Institute of Biology and Molecular Genetics (IBGM) (Spain) or P-PRP. The study will have two aims: first, to ascertain whether a clinically relevant improvement after 3, 6 and 12 months according to the visual analogue scale (VAS), Victorian Institute of Sport Assessment for patellar tendons (VISA-P) and dynamometry scales (DYN) will be achieved; and second, to ascertain whether the proposed intervention will restore tendon structure as determined by ultrasonography (US), Doppler ultrasonography (DUS), and innovative MRI and ultrasound techniques: Magnetic Resonance T2 FAT SAT (UTE, Ultrashort Echo TE) sequence and Ultrasound Tissue Characterization (UTC). Patients who are randomised to the P-PRP treatment group but do not achieve a satisfactory primary endpoint after 6 months will be offered treatment with MSC. Trial registration NCT03454737 .

All new medicines and devices undergo early phase trials to assess, interpret and better understand their efficacy, tolerability and safety. An Introduction to Statistics in Early Phase Trials describes the practical design and analysis of these important early phase clinical trials and provides the crucial statistical basis for their interpretation. It clearly and concisely provides an overview of the most common types of trials undertaken in early phase clinical research and explains the different methodologies used. The impact of statistical technologies on clinical development and the statistical and methodological basis for making clinical and investment decisions are also explained. ● Conveys key ideas in a concise manner understandable by non-statisticians ● Explains how to optimise designs in a constrained or fixed resource setting ● Discusses decision making criteria at the end of Phase II trials ● Highlights practical day-to-day issues and reporting of early phase trials An Introduction to Statistics in Early Phase Trials is an essential guide for all researchers working in early phase clinical trial development, from clinical pharmacologists and pharmacokineticists through to clinical investigators and medical statisticians. It is also a valuable reference for teachers and students of pharmaceutical medicine learning about the design and analysis of clinical trials.

The aims of Phase 1 trials in oncology have broadened considerably from simply demonstrating that the agent/regimen of interest is well tolerated in a relatively heterogeneous patient population to addressing multiple objectives under the heading of early-phase trials and, if possible, obtaining reliable evidence regarding clinical activity to lead to drug approvals via the Accelerated Approval approach or Breakthrough Therapy designation in cases where the tumours are rare, prognosis is poor or where there might be an unmet therapeutic need. Constructing a Phase 1 design that can address multiple objectives within the context of a single trial is not simple. Randomisation can play an important role, but carrying out such randomisation according to the principles of equipoise is a significant challenge in the Phase 1 setting. If the emerging data are not sufficient to definitively address the aims early on, then a proper design can reduce biases, enhance interpretability, and maximise information so that the Phase 1 data can be more compelling. This article outlines objectives and design considerations that need to be adhered to in order to respect ethical and scientific principles required for research in human subjects in early phase clinical trials.

Background Many candidate vaccine strategies against human immunodeficiency virus (HIV) infection are under study, but their clinical development is lengthy and iterative. To accelerate HIV vaccine development optimised trial designs are needed. We propose a randomised multi-arm phase I/II design for early stage development of several vaccine strategies, aiming at rapidly discarding those that are unsafe or non-immunogenic. Methods We explored early stage designs to evaluate both the safety and the immunogenicity of four heterologous prime-boost HIV vaccine strategies in parallel. One of the vaccines used as a prime and boost in the different strategies (vaccine 1) has yet to be tested in humans, thus requiring a phase I safety evaluation. However, its toxicity risk is considered minimal based on data from similar vaccines. We newly adapted a randomised phase II trial by integrating an early safety decision rule, emulating that of a phase I study. We evaluated the operating characteristics of the proposed design in simulation studies with either a fixed-sample frequentist or a continuous Bayesian safety decision rule and projected timelines for the trial. Results We propose a randomised four-arm phase I/II design with two independent binary endpoints for safety and immunogenicity. Immunogenicity evaluation at trial end is based on a single-stage Fleming design per arm, comparing the observed proportion of responders in an immunogenicity screening assay to an unacceptably low proportion, without direct comparisons between arms. Randomisation limits heterogeneity in volunteer characteristics between arms. To avoid exposure of additional participants to an unsafe vaccine during the vaccine boost phase, an early safety decision rule is imposed on the arm starting with vaccine 1 injections. In simulations of the design with either decision rule, the risks of erroneous conclusions were controlled <15%. Flexibility in trial conduct is greater with the continuous Bayesian rule. A 12-month gain in timelines is expected by this optimised design. Other existing designs such as bivariate or seamless phase I/II designs did not offer a clear-cut alternative. Conclusions By combining phase I and phase II evaluations in a multi-arm trial, the proposed optimised design allows for accelerating early stage clinical development of HIV vaccine strategies.

The design of clinical trials for new antiretroviral agents poses unique challenges, given the availability of highly active antiretroviral therapy (HAART). These challenges include the selection of appropriate populations, the methods used to partition the effects of the study drug under observation from those of the other concurrently administered medications in early studies, performance of dose-ranging studies for disease states in which suboptimal drug exposure may lead to the development of viral resistance that limits future treatment options, and the need to fulfill the obligations of international regulatory agencies. Throughout, science and ethics are tightly woven elements in study designs for antiretroviral drug trials. Fast-track drug approval status and successful lobbying by advocates for patients with acquired immunodeficiency syndrome aimed at the US Food and Drug Administration, the National Institutes of Health, the Centers for Disease Control and Prevention, university teaching centers, pharmaceutical companies, and members of Congress undoubtedly contributed to the development and swift regulatory approvals of the 17 antiretroviral medications now available in the United States for the treatment of human immunodeficiency virus infection.

Background The investigational oral DNA vaccine VXM01 targets the vascular endothelial growth factor receptor 2 (VEGFR-2) and uses Salmonella typhi Ty21a as a vector. The immune reaction elicited by VXM01 is expected to disrupt the tumor neovasculature and, consequently, inhibit tumor growth. VXM01 potentially combines the advantages of anti-angiogenic therapy and active immunotherapy. Methods/Design This phase I trial examines the safety, tolerability, and immunological and clinical responses to VXM01. The randomized, placebo-controlled, double blind dose-escalation study includes up to 45 patients with locally advanced and stage IV pancreatic cancer. The patients will receive four doses of VXM01 or placebo in addition to gemcitabine as standard of care. Doses from 10 6  cfu up to 10 10  cfu of VXM01 will be evaluated in the study. An independent data safety monitoring board (DSMB) will be involved in the dose-escalation decisions. In addition to safety as primary endpoint, the VXM01-specific immune reaction, as well as clinical response parameters will be evaluated. Discussion The results of this study shall provide the first data regarding the safety and immunogenicity of the oral anti-VEGFR-2 vaccine VXM01 in cancer patients. They will also define the recommended dose for phase II and provide the basis for further clinical evaluation, which may also include additional cancer indications. Trial registration EudraCT No.: 2011-000222-29, NCT01486329, ISRCTN68809279

The purpose of a clinical trial is to determine whether a new drug is safe, efficacious, and has fewer side effects than products that may already be on the market. They are essential for ensuring that new potential therapies will advance patient outcomes in some way. This may represent a therapy for a previously untreatable condition, or it may represent an improvement in the efficacy or safety compared with an existing treatment. A new therapy should improve patients’ quality of life in a meaningful way, and it should do so for as many potential patients as possible. To meet this goal, companies should consider the lived experiences and exposures of different populations that are included in the target population for therapies in development. This is why it is generally beneficial to advocate diversity in trials as early as possible in the drug development (Phase I and II trials), as doing so expands the number of trials having inclusivity of racial and ethnic minority groups and are inclusive of more women. Although some improvements in diversity in early-phase trials have been observed in recent years, the overall participation of minority populations in these types of trials continues to be disproportionately lower than their representation in the overall population. In 2023, the minority makeup of the US population was 18.7% Latino and 12.1% Black. In comparison, data reported by the National Cancer Institute in 2023 found the racial makeup in early-phase trials to be 6.9% Latino and 7.1% Black, well below their representation in the larger population. The authors, who have been involved in numerous clinical trial study design discussions, understand that people from different backgrounds can experience the same disease differently, and thus, it is important to explore these differences in all communities. These differences represent an important consideration in addition to the acknowledged benefit diversity plays to ensure therapies are appropriately tested in the target patient population. This article explores the need for earlier collaboration/discussion on including diversity in the earlier clinical studies. Our commentary calls for key opinion leaders, study Investigators, study leads, study site recruiters, and coordinators to be open to going beyond the current paradigm of diversity only in pivotal trials, generally Phase III, and explore remedies for inclusion of diversity in early trials.