Bayesian Adaptive Design Research Articles

The PRIME-CUT study: A single-arm phase 2 study of ADT with PD-1 blockade and docetaxel in men with metastatic hormone-sensitive prostate cancer.

e17089 Background: Overall survival of patients (pts) with metastatic hormone-sensitive prostate cancer (mHSPC) is improved with androgen deprivation therapy (ADT) and treatment intensification. Initially, ADT induces a robust and functional immune infiltrate into the tumor microenvironment (TME), with upregulation of immune checkpoint molecules. These effects diminish as castration-resistant prostate cancer (CRPC) invariably develops. We report the first results of the phase 2 PRIME-CUT study (modulating the PRostate cancer Immune MicroEnvironment with ChemoimmUnoTherapy for metastatic prostate cancer). Methods: Eligible pts had newly diagnosed mHSPC, ECOG performance status (PS) 0 or 1, serum testosterone levels > 150 ng/dL, agreed to undergo serial metastatic tumor biopsies, and had not received ADT in the prior 6 months. Treatment consisted of ADT (degarelix 240 mg subcutaneously (SC) for one dose, followed by leuprolide 22.5 mg SC every 12 weeks) followed by anti-PD-1 antibody (cemiplimab 350 mg IV every 3 weeks) beginning four weeks after ADT initiation. With the intent of immune priming, a two-cycle lead-in of anti-PD-1 therapy was administered prior to standard of care docetaxel (75 mg/m2 every 3 weeks for six cycles). Participants received ADT and cemiplimab until study completion (52 weeks) or until a lack of clinical benefit or intolerable side effects. The primary endpoint was the rate of undetectable PSA at 6 months after chemotherapy initiation (week 37) and compared to the historical rate from the phase III CHAARTED trial (32%). Subjects were monitored for toxicity using a Bayesian adaptive study design with an early stopping rule for toxicity. Results: The study completed accrual of 20 pts (median age 62 years) from Columbia University Irving Medical Center in Aug 17, 2022. Among them, 7 self-identified race as Black and 12 self-identified their ethnicity as Hispanic. Baseline PSA ranged from 8.15 to > 5000 ng/dL (median 2513.1 ng/dL). Site of metastatic disease included: 17/20 bone, 12/20 lymph nodes, 11/20 visceral organs. Overall, 14 of 20 patients received at least 4 cycles of docetaxel. Of the 12 patients that were still on-study at 37 weeks, 2 had an undetectable PSA, and 4 additional pts had PSA < 1.0 ng/dL. Twelve pts experienced ≥ Grade 3 adverse events (AEs), 6 AEs were attributed to study intervention including cytopenias (3), hypotension (1), pneumonitis (1), and stenosis of gastrointestinal stoma (1). Unfortunately, two patients deceased on-study (myocardial infarction after 13 weeks, severe SARS-CoV-2 infection after 19 weeks). Conclusions: The Prime-Cut study did not meet its primary endpoint. However, PSA kinetics and results from the pre-planned correlative science demonstrate ongoing role for immunotherapeutic approaches in mHSPC. No new safety signals were observed. Clinical trial information: NCT03951831 .

A Bayesian adaptive design for dual-agent phase I-II oncology trials integrating efficacy data across stages.

Combination of several anticancer treatments has typically been presumed to have enhanced drug activity. Motivated by a real clinical trial, this paper considers phase I-II dose finding designs for dual-agent combinations, where one main objective is to characterize both the toxicity and efficacy profiles. We propose a two-stage Bayesian adaptive design that accommodates a change of patient population in-between. In stage I, we estimate a maximum tolerated dose combination using the escalation with overdose control (EWOC) principle. This is followed by a stage II, conducted in a new yet relevant patient population, to find the most efficacious dose combination. We implement a robust Bayesian hierarchical random-effects model to allow sharing of information on the efficacy across stages, assuming that the related parameters are either exchangeable or nonexchangeable. Under the assumption of exchangeability, a random-effects distribution is specified for the main effects parameters to capture uncertainty about the between-stage differences. The inclusion of nonexchangeability assumption further enables that the stage-specific efficacy parameters have their own priors. The proposed methodology is assessed with an extensive simulation study. Our results suggest a general improvement of the operating characteristics for the efficacy assessment, under a conservative assumption about the exchangeability of the parameters apriori.

Combining Bayesian active learning and conditional Gaussian process simulation for propagating mixed uncertainties through expensive computer simulators

Resulted from the limited information on both parameters and excitation at the early design stage of aerospace structures, evaluating the reliability with high accuracy has been recognized as a challenging task. Imprecise probability models have been widely developed and accepted due to their flexibility in separating the aleatory and epistemic uncertainties, and then the potential of estimating the reliability with high confidence. However, the propagation of these models through expensive-to-evaluate simulators remains to be a challenge due to the hierarchical model structure. To fill this gap, a new Bayesian active learning method is devised for efficiently learning the functional behavior of the failure probability and response variance over the epistemic input parameters. This information is especially useful for evaluating the safety of structures and for managing the uncertainties during the design process. The proposed method is based on training/updating a Gaussian Process Regression (GPR) model in the augmented space of aleatory and epistemic parameters, with the training data actively produced using two well-designed acquisition functions. The induced posterior features of the quantities of interest are inferred numerically based on efficient simulation of the GPR model. Benefiting from the decoupling scheme and the Bayesian adaptive design strategy, the proposed method is extremely efficient and provides accuracy guarantee for the numerical results. The effectiveness and superiority of the proposed method are demonstrated with numerical and engineering benchmarks, including the dynamic reliability analysis of a satellite structure.

Hybrid epicardial and endocardial sinus node–sparing ablation therapy for inappropriate sinus tachycardia: Rationale and design of the multicenter HEAL-IST IDE trial

Inappropriate sinus tachycardia (IST) is defined as resting heart rate >100 beats/min and average 24-hour heart rate >90 beats/min. It is associated with distressing symptoms and significant loss of quality of life. Drugs are not effective in symptom control of IST in up to 30% of patients. Catheter ablation of the sinus node has a high recurrence rate, and the complications are significant. Recently, a novel hybrid sinus node-sparing ablation approach for IST was described. The objective of the Hybrid Epicardial and Endocardial Sinus Node Sparing Ablation Therapy for Inappropriate Sinus Tachycardia (HEAL-IST) investigational device exemption trial (NCT05280093) is to evaluate safety and effectiveness of the hybrid sinus node-sparing ablation procedure for the treatment of symptomatic, drug-refractory or drug-intolerant IST. The HEAL-IST trial is a prospective, multicenter, pivotal, single-arm trial. Up to 142 subjects in up to 40 centers will be treated in the trial with a Bayesian adaptive design. Subjects will be assessed for primary safety through 30 days post-hybrid ablation procedure. The primary effectiveness endpoint will be freedom from IST at 12 months. Freedom from IST will be defined as mean heart rate of ≤90 beats/min or at least a 15% reduction in mean heart rate as compared with baseline, in the absence of new or higher dosage of previously failed medications at a 24-month follow-up assessment. The HEAL-IST trial is the first multicenter trial evaluating hybrid IST ablation in patients with symptomatic IST and refractory or intolerant to drugs. The results of this study will help guide decision making regarding the best management in this population.

381 Repeated Opening of the Blood-Brain Barrier With the Skull-implantable SonoCloud-9 (SC9) Device: Phase 1 Trial of Nab-Paclitaxel and SC9 in Recurrent Glioblastoma

INTRODUCTION: The blood-brain barrier (BBB) is a major impediment to pharmacological treatment of gliomas, as these infiltrate the brain. Low-intensity pulsed ultrasound with concomitant intravenous microbubbles (LIPU/MB), opens the BBB. METHODS: To perform LIPU/MB-based BBB opening prior to ABX infusions, we used a novel 6 x 6 cm device with 9 ultrasound emitters (SC9) that is implanted in a skull window after tumor resection. A Phase 1 dose-escalation trial using Bayesian adaptive design was initiated at our institution (NCT04528680). Patients with recurrent operable glioblastoma, a WHO PS ≤ 2 and normal bone marrow and organ function were eligible. After tumor resection and implantation of SC9, repeated cycles of BBB opening by LIPU/MB immediately followed by ABX, were performed Q3W. Intraoperative LIPU/MB and low dose ABX was given prior to tumor resection for pharmacokinetic studies. RESULTS: Seventeen patients were enrolled, and dose levels 40-260 mg/m2 were investigated. At dose of 260 mgm2, a grade 3 reversible taxane-associated encephalopathy was observed in one patient, considered a dose-limiting toxicity. The patient continued treatment at a lower dose in subsequent cycles. A second patient exhibited encephalopathy on cycle 2. Pharmacokinetic studies showed that ABX tissue concentrations in non-enhancing peri-tumoral brain were increased 3.7-fold after LIPU/MB. sc-RNA-sequencing showed transcriptional dysregulation of membrane transporters, pathways related to trans-cytosis as well as cell-cell and cell-matrix adhesion. Ultrastructural analysis of brain capillaries revealed that LIPU/MB led to time-dependent emergence of vesicles in endothelial cells CONCLUSIONS: The LIPU/MB using skull-implantable ultrasound enhances the penetration of ABX in large regions of the brain, a procedure that can be performed repeatedly and safely. LIPU-based BBB opening leads to ultrastructural transcriptional alterations in brain endothelium. Funding: NIH/NCI 1R01CA245969-01A1, CarThera (SC9 devices), BMS/Celgene (Abraxane®).

Rapid rEcognition of COrticosteRoiD resistant or sensitive Sepsis (RECORDS): study protocol for a multicentre, placebo-controlled, biomarker-guided, adaptive Bayesian design basket trial

IntroductionCorticosteroids affect variably survival in sepsis trials, suggesting heterogeneity in patients’ response to corticosteroids. The RECORDS (Rapid rEcognition of COrticosteRoiD resistant or sensitive Sepsis) trial aimed at defining endotypes associated...

Over-accrual in Bayesian adaptive trials with continuous futility stopping.

We explore frequentist operating characteristics of a Bayesian adaptive design that allows continuous early stopping for futility. In particular, we focus on the power versus sample size relationship when more patients are accrued than originally planned. We consider the case of a phase II single-arm study and a Bayesian phase II outcome-adaptive randomization design. For the former, analytical calculations are possible; for the latter, simulations are conducted. Results for both cases show a decrease in power with an increasing sample size. It appears that this effect is due to the increasing cumulative probability of incorrectly stopping for futility. The increase in cumulative probability of incorrectly stopping for futility is related to the continuous nature of the early stopping, which increases the number of interim analyses with accrual. The issue can be addressed by, for instance, delaying the start of testing for futility, reducing the number of futility tests to be performed or by setting stricter criteria for concluding futility.

Bayesian Adaptive Randomization with Compound Utility Functions

Bayesian adaptive designs formalize the use of previous knowledge at the planning stage of an experiment, permitting recursive updating of the prior information. They often make use of utility functions, while also allowing for randomization. We review frequentist and Bayesian adaptive design methods and show that some of the frequentist adaptive design methodology can also be employed in a Bayesian context. We use compound utility functions for the Bayesian designs, that are a trade-off between an optimal design information criterion, that represents the acquisition of scientific knowledge, and some ethical or utilitarian gain. We focus on binary response models on two groups with independent Beta prior distributions on the success probabilities. The treatment allocation is shown to converge to the allocation that produces the maximum utility. Special cases are the Bayesian Randomized (simply) Adaptive Compound (BRAC) design, an extension of the frequentist Sequential Maximum Likelihood (SML) design and the Bayesian Randomized (doubly) Adaptive Compound Efficient (BRACE) design, a generalization of the Efficient Randomized Adaptive DEsign (ERADE). Numerical simulation studies compare BRAC with BRACE when D-optimality is the information criterion chosen. In analogy with the frequentist theory, the BRACE-D design appears more efficient than the BRAC-D design.

RESTART trial design: two-stage seamless transition design with operational considerations

ABSTRACT Oncology/hematology is a competitive therapeutic area where the landscape is constantly evolving. With regulatory support, many drug developers have spent a lot of resources on the operationalization of innovative clinical trial designs, for example, adaptive Bayesian designs in confirmatory clinical trial settings. While overall survival is considered the gold standard in these designs, it is often not a viable choice in identifying treatment efficacy at a reasonable pace, especially for early-stage therapies. In recent years, several binary response surrogate endpoints have been used for accelerated or conditional approval of novel cancer therapies. Utilizing surrogate endpoints in the study design to predict objective clinical outcomes, such as overall survival, is particularly fundamental in cancer treatment clinical development. This manuscript will investigate logistic and statistical considerations of our proposed RESTART design, a new two-stage, seamless, single- to double-arm Bayesian design. This design could be used for single-arm dose expansion to a randomized confirmatory study. The operating characteristics of the RESTART design are evaluated based on simulations. Future directions and further modifications of this design will also be elaborated.

Early and late preterm birth rates in participants adherent to randomly assigned high dose docosahexaenoic acid (DHA) supplementation in pregnancy

Intention-to-treat analyses do not address adherence. Per protocol analyses treat nonadherence as a protocol deviation and assess if the intervention is effective if followed. To determine the rate of early preterm birth (EPTB, <34 weeks gestation) and preterm birth (PTB, <37 weeks gestation) in participants who adhered to a randomly assigned docosahexaenoic acid (DHA) dose of 1000mg/day. Eleven hundred women with a singleton pregnancy were enrolled before 20-weeks' gestation, provided a capsule with 200mg/day DHA and randomly assigned to two additional capsules containing a placebo or 800mg of DHA. In the Bayesian Adaptive Design, new randomization schedules were determined at prespecified intervals. In each randomization, the group with the most EPTB was assigned fewer participants than the other group. Adherence was defined a priori as a postpartum red blood cell phospholipid DHA (RBC-PL-DHA) ≥5.5%.and post hoc as ≥8.0% RBC-PL-DHA, the latter after examination of postpartum RBC-PL-DHA. Bayesian mixture models were fitted for gestational age and dichotomized for EPTB and PTB as a function of baseline RBC-PL-DHA and dose-adherence. Bayesian hierarchical models were also fitted for EPTB by dose adherence and quartiles of baseline RBC-PL-DHA. Adherence to the high dose using both RBC-PL-DHA cut points resulted in less EPTB compared to 200mg [Bayesian posterior probability (pp)=0.93 and 0.92, respectively]. For participants in the two lowest quartiles of baseline DHA status, adherence to the higher dose resulted in lower EPTB (≥5.5% RBC-PL-DHA, quartiles 1 and 2, pp=0.95 and 0.96; ≥8% RBC-PL-DHA, quartiles 1 and 2, pp=0.94 and 0.95). Using the Bayesian model, EPTB was reduced by 65%, from 3.45% to 1.2%, using both cut points. Adherence also reduced PTB before 35, 36 and 37 weeks using both cut points (pp≥0.95). In general, performance of the nonadherent subgroup mirrored that of participants assigned to 200mg. Adherence to high dose DHA reduced EPTB and PTB. The largest effect of adherence on reducing EPTB was observed in women with low baseline DHA levels. gov (NCT02626299).

Design and logistical considerations for the randomized adaptive non-inferiority storage-duration-ranging CHIlled Platelet Study.

Platelet transfusion is a potentially life-saving therapy for actively bleeding patients, ranging from those undergoing planned surgical procedures to those suffering unexpected traumatic injuries. Platelets are currently stored at room temperature (20°C-24°C) with a maximum storage duration of 7 days after donation. The CHIlled Platelet Study trial will compare the efficacy and safety of standard room temperature-stored platelets with platelets that are cold-stored (1°C-6°C), that is, chilled, with a maximum of storage up to 21 days in adult and pediatric patients undergoing complex cardiac surgical procedures. CHIlled Platelet Study will use a Bayesian adaptive design to identify the range of cold storage durations for platelets that are non-inferior to standard room temperature-stored platelets. If cold-stored platelets are non-inferior at durations greater than 7 days, a gated superiority analysis will identify durations for which cold-stored platelets may be superior to standard platelets. We present example simulations of the CHIlled Platelet Study design and discuss unique challenges in trial implementation. The CHIlled Platelet Study trial has been funded and will be implemented in approximately 20 clinical centers. Early randomization to enable procurement of cold-stored platelets with different storage durations will be required, as well as a platelet tracking system to eliminate platelet wastage and maximize trial efficiency and economy. The CHIlled Platelet Study trial will determine whether cold-stored platelets are non-inferior to platelets stored at room temperature, and if so, will determine the maximum duration (up to 21 days) of storage that maintains non-inferiority. ClinicalTrials.gov, NCT04834414.

A novel Bayesian adaptive design incorporating both primary and secondary endpoints for randomized IIB chemoprevention study of women at increased risk for breast cancer

BackgroundOur randomized controlled clinical trial will explore the potential of bazedoxifene plus conjugated estrogen to modulate breast tissue-based risk biomarkers as a surrogate for breast cancer risk reduction. This paper investigates the statistical design features of the trial and the rationale for the final choice of its design. Group sequential designs are a popular design approach to allow a trial to stop early for success or futility, potentially saving time and money over a fixed trial design. While Bayesian adaptive designs enjoy the same properties as group sequential designs, they have the added benefit of using prior information as well as inferential interpretation conditional on the data. Whether a frequentist or Bayesian trial, most adaptive designs have interim analyses that allow for early stopping, typically utilizing only the primary endpoint. A drawback to this approach is that the study may not have enough data for adequate comparisons of a single, key secondary endpoint. This can happen, for example, if the secondary endpoint has a smaller effect than the primary endpoint.MethodsIn this paper, we investigate a trial design called two-endpoint adaptive, which stops early only if a criterion is met for primary and secondary endpoints. The approach focuses the final analysis on the primary endpoint but ensures adequate data for the secondary analysis. Our study has two arms with a primary (change in mammographic fibroglandular volume) and secondary endpoint (change in mammary tissue Ki-67).ResultsWe present operating characteristics including power, trial duration, and type I error rate and discuss the value and risks of modeling Bayesian group sequential designs with primary and secondary endpoints, comparing against alternative designs. The results indicate that the two-endpoint adaptive design has better operating characteristics than competing designs if one is concerned about having adequate information for a key secondary endpoint.DiscussionOur approach balances trial speed and the need for information on the single, key secondary endpoint.

Safety and Efficacy of the Addition of the Protein Translation Inhibitor Omacetaxine to Induction with Cytarabine and Idarubicin in Newly Diagnosed AML

Background: Omacetaxine mepesuccinate (OM), a semi-synthetic form of homoharringtonine (HHT), mechanistically inhibits aminoacyl-tRNA binding to ribosomal acceptor "A” sites, preventing mRNA translation (Wetzler,Curr Pharm Des 2011, 17:59-64), and causing a rapid decline of short-lived proteins e.g., c-myc, cyclin D, the anti-apoptotic proteins cFLIP, survivin and Mcl-1, an important anti-apoptotic regulator in AML.While HHT added to cytarabine and an anthracycline improved CR and 3-yr EFS in de novo AML patients (pts; Jin et al, Lancet Oncology 2013, 7:599-608), meta-analysis of Chinese studies in elderly pts indicated a CR of 47.5%. Aims: Early analysis of AML-02, a phase Ib trial of escalating doses of OM (an FDA-approved drug) added to a standard 7 + 3 induction regimen was described (NCT02440568; Christian et al., Blood, 2018, 132:5218). Here we report long-term pt outcomes and studies of their correlation with in vitro OM effects on protein translation and apoptosis sensitivity. Methods: From June 2015 to June 2018, 22 pts aged 18-70 yrs with newly diagnosed AML entered AML-02, receiving escalating doses of OM administered SQ q12h d1-7 with cytarabine (100mg/m2 CIV) d1-7 and Idarubicin 12mg/m2 IV d1-3. Four OM dose levels were tested starting with cohort #1 at 0.625mg/m2 sc q12h (also 1.25, 2.0, and 3.0mg/m2 q12h cohorts). The primary endpoint, the optimally safe and active dose (OD) was determined using a Bayesian adaptive design, EFFTOX, which considers trade-offs between efficacy and toxicity to establish the OD (Shah et al, Leukemia, 2015; 29:1945). Secondary endpoints included OS, RFS and EFS. Residual disease at d14 was deemed a study failure and pts were taken off study. Hematological toxicity (HT) was defined as incomplete hematologic recovery at d49 with the BM free of leukemia. Post-induction therapy consisted of standard high dose cytarabine consolidation chemotherapy or allogeneic HSCT, based on cytogenetic risk (ELN 2010). Potential correlations of the effects of OM on protein translation rates, measured using the OP-Puro technique, and apoptosis sensitivity, measured using BH3 profiling techniques, on pretreatment AML samples and subsequent patient outcomes were also examined. Follow-up is complete to August 1st, 2022. Results: Median age was 58 yrs, 12 pts had adverse cytogenetics, 6 intermediate and 3 favorable risk (1 unknown due to fibrosis); overall 73% (16) had adverse cytogenetics or secondary AML. Earlier results (Christian et al) indicated no HTs in 21 evaluable pts, and OD was established as 2.0mg/m2. CR was 45.5%, median OS 22.7 months (OS at 4 yrs 45%), and EFS 80 days. The median OS is now 24.2 months (95% CI 18.3-39.7), median EFS is 80 days (95% CI 280-964), and OS at 6 years remains at 45%. There were no new TEAEs. Notably, of 10 pts achieving CR, 1 pt relapsed at D60, 1 was lost to follow-up and 1 died of opiate overdose (in CR). Five of the remaining 7 underwent HSCT and all 7 remain in remission. In pts achieving CR, median RFS is 62.4 months (95% CI 42.6-82.2; Fig.1), suggesting potential LSC impact. Common adverse effects included neutropenia (82%), nausea (64%), vomiting (59%), diarrhea (45%), hyperglycemia (41%), and a transient desquamating skin reaction (27%) that is dose-related and may be due to OM-mediated downregulation of cFLIP levels in sweat glands (Hwang et al, British Journal of Haematology, 2021; 195:e138-e146). In in vitro studies, 3 pretreatment AML pt BM samples were analyzed after a short-term (non-cytotoxic) OM treatment for 4 hours at a dose (75 nM) equivalent to calculated systemic OM levels achieved in cohort#3 (2mg/m2). Responding pt samples (CR;n=2) had a greater reduction in protein translation than the non-responder (NR). With exposure to OM, CR pts also had greater reductions of proteins with a short T1/2, such as anti-apoptotic protein MCL-1, with a marked increase in cytochrome C loss, indicating high mitochondrial priming and sensitivity to apoptosis (Fig.2). Conclusion: This small phase Ib study of the addition of OM to a standard 7 + 3 regimen in a diverse population with predominantly high-risk AML and frequent co-morbidities demonstrates a manageable safety profile, acceptable efficacy and resulted in a prolonged DoR. Studies of pretreatment pt samples suggest that analysis of blast protein translation inhibition and especially BH3 profiling responses to OM may predict susceptibility of LSC to Omacetaxine, and potentially patient outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

CTNI-37. REPEATED OPENING OF THE BLOOD-BRAIN BARRIER WITH THE SKULL-IMPLANTABLE SONOCLOUD-9 (SC9) DEVICE: PHASE 1 TRIAL OF NAB-PACLITAXEL AND SC9 IN RECURRENT GLIOBLASTOMA

Abstract BACKGROUND The blood-brain barrier (BBB) is a major impediment to pharmacological treatment of gliomas. Low-intensity pulsed ultrasound with concomitant administration of intravenous microbubbles (LIPU/MB), temporarily opens the BBB. Here we investigate the pharmacokinetics and safety of this approach of repeated delivery of albumin-bound paclitaxel (Abraxane®, ABX) to the peri-tumoral brain. To perform LIPU/MB-based BBB opening prior to ABX infusions, we used a novel 6 x 6 cm device with 9 ultrasound emitters (SC9) that is implanted in a skull window after tumor resection. METHODS A Phase 1 dose-escalation trial using Bayesian adaptive design was conducted (NCT04528680). Patients with recurrent operable glioblastoma, a WHO PS ≤ 2 and adequate bone marrow and organ function were eligible. After tumor resection and implantation of SC9, repeated cycles of BBB opening by LIPU/MB immediately followed by ABX, was performed every 3 weeks. Intraoperative LIPU/MB and low dose ABX was given prior to tumor resection allowed for investigation tissue concentrations and pharmacokinetics. RESULTS Seventeen patients have been treated at six escalating ABX dose levels (40-260 mg/m2). At dose of 260 mg/m2, a grade 3 reversible taxane-associated dose limiting encephalopathy was observed in one patient. The patient continued treatment at a lower dose in subsequent cycles. A second patient exhibited encephalopathy on cycle 2. One patient developed grade 2 cumulative peripheral neuropathy. Intraoperative pharmacokinetic studies showed that ABX tissue concentrations in non-enhancing peri-tumoral brain were increased 3.7-fold after LIPU/MB. sc-RNA-sequencing showed transcriptional dysregulation of membrane transporters, pathways related to trans-cytosis as well as cell-cell and cell-matrix adhesion. CONCLUSIONS The LIPU/MB using skull-implantable ultrasound enhances the penetration of ABX in large regions of the brain. The procedure can be performed repeatedly and safely. LIPU-based BBB opening leads to transcriptional alterations in brain endothelium. Funding: NIH/NCI 1R01CA245969-01A1, CarThera (SC9 devices), BMS/Celgene (Abraxane®).

Exploration of V–Cr–Fe–Co–Ni high-entropy alloys with high yield strength: A combination of machine learning and molecular dynamics simulation

Improving the strength of Cr–Fe–Co–Ni high-entropy alloys is a key issue in expanding their applicability. Herein, a framework combining machine learning and molecular dynamics is employed to improve the yield strength of Cr–Fe–Co–Ni high-entropy alloys through vanadium addition. The results indicate that by specifying the valence electron concentration, vacancy formation energy, and mismatch in cohesive energy as input features, a support vector regression model with a radial bias function kernel displays the highest performance among numerous combinations of machine learning models and material features. According to the Shapley additive explanation, the vacancy formation energy and valence electron concentration show a negative correlation with the yield strength above 1.66 eV and 7.60, respectively, and a positive correlation otherwise. The mismatch in the cohesive energy always shows a negative correlation. By utilizing a Bayesian adaptive alloy design, V5Cr16Fe9Co35Ni35 has been identified to have the highest yield strength. The simulated tensile deformation of polycrystalline high-entropy alloys confirms the predicted trend in yield strength, and the events observed during plastic deformation are consistent with previous experimental observations. The proposed framework provides a promising prospect for accelerating the design of high-entropy alloys with reduced dependence on costly trial-and-error experiments.

Demonstration of a 'leapfrog' randomized controlled trial as a method to accelerate the development and optimization of psychological interventions.

The scale of the global mental health burden indicates the inadequacy not only of current treatment options, but also the pace of the standard treatment development process. The 'leapfrog' trial design is a newly-developed simple Bayesian adaptive trial design with potential to accelerate treatment development. A first leapfrog trial was conducted to provide a demonstration and test feasibility, applying the method to a low-intensity internet-delivered intervention targeting anhedonia. At the start of this online, single-blind leapfrog trial, participants self-reporting depression were randomized to an initial control arm comprising four weeks of weekly questionnaires, or one of two versions of a four-week cognitive training intervention, imagery cognitive bias modification (imagery CBM). Intervention arms were compared to control on an ongoing basis via sequential Bayesian analyses, based on a primary outcome of anhedonia at post-intervention. Results were used to eliminate and replace arms, or to promote them to become the control condition based on pre-specified Bayes factor and sample size thresholds. Two further intervention arms (variants of imagery CBM) were added into the trial as it progressed. N = 188 participants were randomized across the five trial arms. The leapfrog methodology was successfully implemented to identify a 'winning' version of the imagery CBM, i.e. the version most successful in reducing anhedonia, following sequential elimination of the other arms. The study demonstrates feasibility of the leapfrog design and provides a foundation for its adoption as a method to accelerate treatment development in mental health. Registration: clinicaltrials.gov, NCT04791137.

A Bayesian adaptive design for clinical trials of rare efficacy outcomes with multiple definitions.

Bayesian adaptive designs for clinical trials have gained popularity in the recent years due to the flexibility and efficiency that they offer. We consider the scenario where the outcome of interest comprises events with relatively low risk of occurrence and different case definitions resulting in varying control group risk assumptions. This is a scenario that occurs frequently for infectious diseases in global health research. We propose a Bayesian adaptive design that incorporates different case definitions of the outcome of interest that vary in stringency. A set of stopping rules are proposed where superiority and futility may be concluded with respect to different outcome definitions and therefore maintain a realistic probability of stopping in trials with low event rates. Through a simulation study, a variety of stopping rules and design configurations are compared. The simulation results are provided in an interactive web application that allows the user to explore and compare the design operating characteristics for a variety of assumptions and design parameters with respect to different outcome definitions. The results for select simulation scenarios are provided in the article. Bayesian adaptive designs offer the potential for maximizing the information learned from the data collected through clinical trials. The proposed design enables monitoring and utilizing multiple composite outcomes based on rare events to optimize the trial design operating characteristics.

Optimizing a Bayesian hierarchical adaptive platform trial design for stroke patients

BackgroundPlatform trials are well-known for their ability to investigate multiple arms on heterogeneous patient populations and their flexibility to add/drop treatment arms due to efficacy/lack of efficacy. Because of their complexity, it is important to develop highly optimized, transparent, and rigorous designs that are cost-efficient, offer high statistical power, maximize patient benefit, and are robust to changes over time.MethodsTo address these needs, we present a Bayesian platform trial design based on a beta-binomial model for binary outcomes that uses three key strategies: (1) hierarchical modeling of subgroups within treatment arms that allows for borrowing of information across subgroups, (2) utilization of response-adaptive randomization (RAR) schemes that seek a tradeoff between statistical power and patient benefit, and (3) adjustment for potential drift over time. Motivated by a proposed clinical trial that aims to find the appropriate treatment for different subgroup populations of ischemic stroke patients, extensive simulation studies were performed to validate the approach, compare different allocation rules, and study the model operating characteristics.Results and conclusionsOur proposed approach achieved high statistical power and good patient benefit and was also robust against population drift over time. Our design provided a good balance between the strengths of both the traditional RAR scheme and fixed 1:1 allocation and may be a promising choice for dichotomous outcomes trials investigating multiple subgroups.

1559P Towards more efficient multi-arm exercise trials in oncology: Application of a Bayesian adaptive decision-theoretic approach

Conducting a traditional, adequately powered multi-arm exercise trial is often challenging in terms of time and available resources. Novel, efficient trial designs are needed for rigorous comparison of multiple treatment arms. This study illustrates a Bayesian adaptive decision-theoretic design using a multi-arm exercise oncology trial.

Bayesian adaptive clinical trial designs for respiratory medicine.

The use of Bayesian adaptive designs for clinical trials has increased in recent years, particularly during the COVID‐19 pandemic. Bayesian adaptive designs offer a flexible and efficient framework for conducting clinical trials and may provide results that are more useful and natural to interpret for clinicians, compared to traditional approaches. In this review, we provide an introduction to Bayesian adaptive designs and discuss its use in recent clinical trials conducted in respiratory medicine. We illustrate this approach by constructing a Bayesian adaptive design for a multi‐arm trial that compares two non‐invasive ventilation treatments to standard oxygen therapy for patients with acute cardiogenic pulmonary oedema. We highlight the benefits and some of the challenges involved in designing and implementing Bayesian adaptive trials.