No-go Decision Research Articles

Industry Perspective on First-in-Human and Clinical Pharmacology Strategies to Support Clinical Development of T-Cell Engaging Bispecific Antibodies for Cancer Therapy.

T-cell-engaging bispecific antibodies (TCEs) that target tumor antigens and T cells have shown great promise in treating cancer, particularly in hematological indications. The clinical development of TCEs often involves a lengthy first-in-human (FIH) trial with many dose-escalation cohorts leading up to an early proof of concept (POC), enabling either a no-go decision or dose selection for further clinical development. Multiple factors related to the target, product, disease, and patient population influence the efficacy and safety of TCEs. The intricate mechanism of action limits the translatability of preclinical models to the clinic, thereby posing challenges to streamline clinical development. In addition, unlike traditional chemotherapy, the top dose and recommended phase II doses (RP2Ds) for TCEs in the clinic are often not guided by the maximum tolerated dose (MTD), but rather based on the integrated dose-response assessment of the benefit/risk profile. These uncertainties pose complex challenges for translational and clinical pharmacologists (PK/PD scientists), as well as clinicians, to design an efficient clinical study that guides development. To that end, experts in the field, under the umbrella of the American Association of Pharmaceutical Scientists, have reviewed learnings from published literature and currently marketed products to share perspectives on the FIH and clinical pharmacology strategies to support early clinical development of TCEs.

Oral docetaxel plus encequidar – A pharmacokinetic model and evaluation against IV docetaxel

The development of optimized dosing regimens plays a crucial role in oncology drug development. This study focused on the population pharmacokinetic modelling and simulation of docetaxel, comparing the pharmacokinetic exposure of oral docetaxel plus encequidar (oDox + E) with the standard of care intravenous (IV) docetaxel regimen. The aim was to evaluate the feasibility of oDox + E as a potential alternative to IV docetaxel. The article demonstrates an approach which aligns with the FDA’s Project Optimus which aims to improve oncology drug development through model informed drug development (MIDD). The key question answered by this study was whether a feasible regimen of oDox + E existed. The purpose of this question was to provide an early GO / NO-GO decision point to guide drug development and improve development efficiency. Methods: A stepwise approach was employed to develop a population pharmacokinetic model for total and unbound docetaxel plasma concentrations after IV docetaxel and oDox + E administration. Simulations were performed from the final model to assess the probability of target attainment (PTA) for different oDox + E dose regimens (including multiple dose regimens) in relation to IV docetaxel using AUC over effective concentration (AUCOEC) metric across a range of effective concentrations (EC). A Go / No-Go framework was defined—the first part of the framework assessed whether a feasible oDox + E regimen existed (i.e., a PTA ≥ 80%), and the second part defined the conditions to proceed with a Go decision. Results: The overall population pharmacokinetic model consisted of a 3-compartment model with linear elimination, constant bioavailability, constant binding mechanics, and a combined error model. Simulations revealed that single dose oDox + E regimens did not achieve a PTA greater than 80%. However, two- and three-dose regimens at 600 mg achieved PTAs exceeding 80% for certain EC levels. Conclusion: The study demonstrates the benefits of MIDD using oDox + E as a motivating example. A population pharmacokinetic model was developed for the total and unbound concentration in plasma of docetaxel after administration of IV docetaxel and oDox + E. The model was used to simulate oDox + E dose regimens which were compared to the current standard of care IV docetaxel regimen. A GO / NO-GO framework was applied to determine whether oDox + E should progress to the next phase of drug development and whether any conditions should apply. A two or three-dose regimen of oDox + E at 600 mg was able to achieve non-inferior pharmacokinetic exposure to current standard of care IV docetaxel in simulations. A Conditional GO decision was made based on this result and further quantification of the “effective concentration” would improve the ability to optimise the dose regimen.

Go or No-Go Decision – How to Structure the Framework for the Investment Case Games Workshop

Go or No-Go Decision – How to Structure the Framework for the Investment Case Games Workshop

A Bayesian approach to pilot-pivotal trials for bioequivalence assessment

BackgroundTo demonstrate bioequivalence between two drug formulations, a pilot trial is often conducted prior to a pivotal trial to assess feasibility and gain preliminary information about the treatment effect. Due to the limited sample size, it is not recommended to perform significance tests at the conventional 5% level using pilot data to determine if a pivotal trial should take place. Whilst some authors suggest to relax the significance level, a Bayesian framework provides an alternative for informing the decision-making. Moreover, a Bayesian approach also readily permits possible incorporation of pilot data in priors for the parameters that underpin the pivotal trial.MethodsWe consider two-sequence, two-period crossover designs that compare test (T) and reference (R) treatments. We propose a robust Bayesian hierarchical model, embedded with a scaling factor, to elicit a Go/No-Go decision using predictive probabilities. Following a Go decision, the final analysis to formally establish bioequivalence can leverage both the pilot and pivotal trial data jointly. A simulation study is performed to evaluate trial operating characteristics.ResultsCompared with conventional procedures, our proposed method improves the decision-making to correctly allocate a Go decision in scenarios of bioequivalence. By choosing an appropriate threshold, the probability of correctly (incorrectly) making a No-Go (Go) decision can be ensured at a desired target level. Using both pilot and pivotal trial data in the final analysis can result in a higher chance of declaring bioequivalence. The false positive rate can be maintained in situations when T and R are not bioequivalent.ConclusionsThe proposed methodology is novel and effective in different stages of bioequivalence assessment. It can greatly enhance the decision-making process in bioequivalence trials, particularly in situations with a small sample size.

Replicate Testing of Clinical Endpoints Can Prevent No-Go Decisions for Beneficial Vaccines.

In vaccine efficacy trials, inaccurate counting of infection cases leads to systematic under-estimation-or "dilution"-of vaccine efficacy. In particular, if a sufficient fraction of observed cases are false positives, apparent efficacy will be greatly reduced, leading to unwarranted no-go decisions in vaccine development. Here, we propose a range of replicate testing strategies to address this problem, considering the additional challenge of uncertainty in both infection incidence and diagnostic assay specificity/sensitivity. A strategy that counts an infection case only if a majority of replicate assays return a positive result can substantially reduce efficacy dilution for assays with non-systematic (i.e., "random") errors. We also find that a cost-effective variant of this strategy, using confirmatory assays only if an initial assay is positive, yields a comparable benefit. In clinical trials, where frequent longitudinal samples are needed to detect short-lived infections, this "confirmatory majority rule" strategy can prevent the accumulation of false positives from magnifying efficacy dilution. When widespread public health screening is used for viruses, such as SARS-CoV-2, that have non-differentiating features or may be asymptomatic, these strategies can also serve to reduce unneeded isolations caused by false positives.

Single-arm phase II three-outcome designs with handling of over-running/under-running

Phase II clinical trials are commonly conducted as pilot studies to evaluate the efficacy and safety of the investigational drug in the targeted patient population with the disease or condition to be treated or prevented. When designing such a trial considering efficacy conclusions, people naturally think as follows: if efficacy evidence is very strong, a go decision should be made; if efficacy evidence is very weak, a no-go decision should be made; if the efficacy evidence is neither strong nor weak, no decision can be made (inconclusive). The designs presented in this paper match this natural thinking process with go/no-go/inconclusive outcomes. Both two-/three-stage designs are developed with three outcomes. Additionally, a general approach based on conditional error function is implemented such that new decision boundaries can be calculated to handle mid-course sample size change which results in either ‘over-running’ or ‘under-running’ and ensure the control of overall type I error. A free open-source R package tsdf that calculates the proposed two-/three-stage designs is available on CRAN.

Robust time selection for interim analysis in the Bayesian phase 2 exploratory clinical trial

ABSTRACT In phase 2 clinical trials, we expect to make a right Go or No-Go decision during the interim analysis (IA) and make this decision at the right time. The optimal time for IA is usually determined based on a utility function. In most previous research, utility functions aim to minimize the expected sample size or total cost in confirmatory trials. However, the selected time can vary depending on different alternative hypotheses. This paper proposes a new utility function for Bayesian phase 2 exploratory clinical trials. It evaluates the predictability and robustness of the Go and No-Go decision made during the IA. We can make a robust time selection for the IA based on the function regardless of the treatment effect assumptions.

Antibodies against Anthrax Toxins: A Long Way from Benchlab to the Bedside.

Anthrax is an acute disease caused by the bacterium Bacillus anthracis, and is a potential biowarfare/bioterrorist agent. Its pulmonary form, caused by inhalation of the spores, is highly lethal and is mainly related to injury caused by the toxins secretion. Antibodies neutralizing the toxins of B. anthracis are regarded as promising therapeutic drugs, and two are already approved by the Federal Drug Administration. We developed a recombinant human-like humanized antibody, 35PA83 6.20, that binds the protective antigen and that neutralized anthrax toxins in-vivo in White New Zealand rabbits infected with the lethal 9602 strain by intranasal route. Considering these promising results, the preclinical and clinical phase one development was funded and a program was started. Unfortunately, after 5 years, the preclinical development was cancelled due to industrial and scientific issues. This shutdown underlined the difficulty particularly, but not only, for an academic laboratory to proceed to clinical development, despite the drug candidate being promising. Here, we review our strategy and some preliminary results, and we discuss the issues that led to the no-go decision of the pre-clinical development of 35PA83 6.20 mAb. Our review provides general information to the laboratories planning a (pre-)clinical development.

Go-/ no-go decisions based on gradually revealed visual information.

Go-/ no-go decisions based on gradually revealed visual information.

Harnessing the Power of Proteomics to Advance Precision Medicine

Clinical OMICsVol. 8, No. 3 Sponsored ContentFree AccessHarnessing the Power of Proteomics to Advance Precision MedicinePublished Online:18 Jun 2021https://doi.org/10.1089/clinomi.08.03.18AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Jennifer Van Eyk, PhD, Director, Precision Biomarker LabsWhat is the mission of Precision Biomarker Laboratories (PBL)?Precision Biomarker Laboratories is focused on releasing the power of precise proteomics by utilizing our growing understanding of the proteome to transform how medicine is practiced. Our goal is to reduce the barriers in translating therapies and biomarkers to the clinic for the benefit of precision health. PBL builds on the Cedars-Sinai Medical Center health network patient population to validate assays to meet clinical rigor as laboratory developed tests into our CAP/CLIA lab, and to implement these new protein markers within the context of thousands of individuals in a time- and cost-effective manner.How can a better understanding of the human proteome aid in advancing precision medicine?Our proteome, continuously changing from the time we are born until we reach old age, contributes more than genetics to disease risk over a lifetime. It can aid precision medicine since the proteome represents a personalized signature or timestamp for each patient of their current physiological status based on their response to multiple perturbations including stress, environment, smoking, and obesity, among other things.But the proteome can, and does, change rapidly in response to these perturbations, which makes it an active signature of a person's current physiological status and provides insights to how you will respond to a specific therapy. Your proteomic timestamp can thus help predict your future health and provide a responsive health readout.How is PBL well-positioned to deliver on this promise?For our clients, we can accelerate development, allowing faster go/ no-go decisions by providing precise and accurate protein data with full analytical support. We aid our partners to more quickly discover and develop drug targets by ensuring that the drug is targeting the protein or network of choice. We provide rapid, targeted protein panel development, which allows focusing on the key proteins or pathways with maximum biological insight. Finally, our affiliation with Cedars-Sinai provides access to a clinical infrastructure that is vital to establishing the validity of protein biomarkers.How do you accomplish all of this?We have three synergistic laboratories. Each works independently, but our clients can use any aspect of each or all of their capabilities.The proteomics contract research lab leverages our automated sample preparation, mass spectrometry, and integrated bioinformatic pipelines and expertise. It is focused on discovery and early research support to provide discovery services, or clients can use one of their own targeted assays. We have biomarkers of both biological and clinical relevance.Our commercial development lab provides clients with a bioinformatic and data analysis framework for clinical investigations with advanced analytical methods built to support clinical and commercial deployment. It also provides access to our clinical expertise and clinical cohorts, as needed.Finally, the clinical specialty lab completes the translation of research to clinical applications, to support a product launch either in the clinic or for clinical trials. It develops assays that define clinical use, supports validated assays from external sources, and supports clinical results interpretation.PBL uses mass spec for its assays and assay development. In what ways are you leveraging mass spec?PBL takes emerging and cutting-edge mass spec technologies and develops them into robust quantitative workflows. Using our plasma or dried blood assays (remote sampling) we can do discovery or use one of our in-house multiplexed protein targeted assays. For example, the Health Surveillance protein panel consists of 59 plasma proteins that represent nine pathological signatures such as the heart, kidneys, the lungs, inflammation, and immunity. It can be used for risk stratification in a clinical trial or to measure response to a therapy. We also have disease-specific assays such as our COVID-19 Acute Phase Protein assay. Upstream of our targeted and customizable assays we provide mass spec discovery services using data-independent acquisition workflows. Leveraging mass spec services on discovery and targeted workflows increases the likelihood of clinical translation for precision health applications.For more information: cedars-sinai.org/pblFiguresReferencesRelatedDetails Volume 8Issue 3May 2021 InformationCopyright © GEN PublishingTo cite this article:Clinical OMICs.May 2021.15-15.http://doi.org/10.1089/clinomi.08.03.18Published in Volume: 8 Issue 3: June 18, 2021PDF download

Application-specific software supporting engineers and physicians to manage risks in 3DP

Abstract: To allow easier judgement about successfully 3D printed parts Kumovis develops a proprietary software as guiding instrument for physicians and engineers operating the filament printer R1 to manufacture surgical guides, instruments and implants. The software takes multiple parameters into account to manage the risk of failed print jobs and provides a Go / NoGo decision for the printer operator. Aim of the software is the raise of success rate per printed parts in a regulated market and reduction of failed print jobs.

A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder.

Whether children with attention deficit hyperactivity disorder (ADHD) have deficits in sustained attention remains unresolved due to the ongoing use of cognitive paradigms that are not optimized for studying vigilance and the fact that relatively few studies report performance over time. In three independent samples of school-age children with (total N = 128) and without ADHD (total N = 59), we manipulated event rate, difficulty of discrimination, and use signal detection (SDT) and diffusion models (DM) to evaluate the cause of the vigilance decrement during a continuous performance task. For both groups of children, a bias toward "no-go" over time (as indexed by the SDT parameter B″ and the DM parameter z/a) was responsible for generating the vigilance decrement. However, among children with ADHD, the rate at which information accumulated to make a no-go decision (vNoGo) also increased with time on task, representing a possible secondary mechanism that biases children against engagement. At all time points, children with ADHD demonstrated reduced sensitivity to discriminate targets from nontargets. Children with ADHD are particularly sensitive to the cost of task engagement, but nonspecific slower drift rate may ultimately provide a better conceptualization of the cognitive atypicalities commonly observed in that group. Results are interpreted in the context of updated conceptualizations of sustained attention and vigilance. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Abstract IA08: Use of liquid biopsy to facilitate drug development in early-stage disease—FDA perspective

Abstract Background: With advances in precision oncology, liquid biopsies have shown promise as a minimally invasive means to potentially diagnose cancer, detect resistance mutations and monitor tumor evolution, predict relapse, provide prognosis, and guide treatment decisions. One unique setting for the use of liquid biopsy to facilitate drug development is in early-stage disease where there is the potential for use in patient selection, prognostication, and drug activity demonstration. Discussion: From the regulatory and clinical trial perspective, liquid biopsies can be used as prognostic biomarkers to identify the likelihood of disease recurrence in early-stage cancer. For example, circulating cell-free tumor DNA (ctDNA) in an adjuvant cancer setting affords the potential to select a high-risk population that could be utilized as a stratification factor, or selection of an enriched high-risk population in which specific drug development could be pursued. Use of liquid biopsy as a putative surrogate endpoint or efficacy-response biomarker, in this setting, would require a large body of evidence demonstrating biologic plausibility, demonstration of studies of prognostic value of the surrogate endpoint for the clinical outcome, and evidence from clinical trials (or meta-analysis) that the treatment effects on the biomarker correlate to the long-term outcome. Another use of liquid biopsy as an efficacy-response biomarker could allow for go or no-go decision making earlier on in drug development, which could also be applied in the adjuvant setting. Conclusions: Liquid biopsies will continue to play a role in the clinical management of malignancies and have the potential to support drug approval and become more broadly incorporated and utilized in early-stage clinical trials. Citation Format: Julia A. Beaver. Use of liquid biopsy to facilitate drug development in early-stage disease—FDA perspective [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr IA08.

Social Sustainability Dilemma: Escape or Communicate? Managing Social Risks Upstream of the Bioenergy Supply Chain

Supply chain risk management has been well researched over the years. However, management of social risks in bioenergy supply chains has been studied less in contemporary research. The ability of bioenergy companies to identify, properly address, and communicate social sustainability has become crucial for many global producers. In order to meet current EU’s energy and climate targets, the development of sustainable bioenergy production is vital. However, over last decade, research of bioenergy production supply chains has indicated that upstream areas of global bioenergy production systems are vulnerable in terms of social sustainability risks. The main objective of this research was to demonstrate how the socially sustainable supply chain practices in bioenergy supply chains can help a production company manage social risks and resources-use related conflicts upstream of the supply chain. These practices can be applied in the process of negotiation between bioenergy producers, local authorities, and communities for creating win-win situations for all parties while planning new bioenergy production systems. This study pays special attention to social sustainability risks at the upstream of the supply chain in countries of raw material origin. Use of social sustainability practices intends to help identify, assess, and address social risks of supply chain activities for bioenergy companies. Moreover, such practices aim at supporting companies and their stakeholders in making right choices and preparing effective strategies ahead of time. We based our research on empirical evidence and offer solutions to multi-national bioenergy production companies on how to manage social risks, allowing them to make the right decisions and necessary adjustments before entering potential markets. Our findings show that even avoidance of market entrance can carry sustainability-related social risks for both the company and the local communities. We suggest that although the financial element plays an important role in decision-making, the no-go decision often means missed opportunities for local communities to improve their respective sustainability states.

The effects of self-efficacy, process feedback, and task complexity on escalation of commitment in new product development

PurposeThe purpose of this paper is to investigate the effects of self-efficacy, process feedback and task complexity on decisions by managers to continue or discontinue a new product after receiving negative performance feedback.Design/methodology/approachThis paper uses a classroom experiment design and uses logistic regression and a chi-square test to analyze the data.FindingsThe findings of this paper show that self-efficacy, process feedback and task complexity have not only main effects but also interactive effects on managers’ go or no-go decisions; further, the main effects are mediated by interactions. The effect of self-efficacy is moderated by process feedback and task complexity. Process feedback and task complexity also have an interactive effect on decisions about new products by decision-makers.Research limitations/implicationsThis paper extends the theory of escalation of commitment (EOC) by showing that self-efficacy, process feedback and task complexity can influence decision-makers’ go or no-go decisions after they have received negative performance feedback.Practical implicationsThis paper provides useful guidelines for managers on how to reduce the likelihood of EOC.Originality/valueThe originality and value of this paper lie in its being the first to examine the effects of process feedback and task complexity on the EOC.

A Phase 2, Randomized, Double-Blind, Placebo-Controlled Trial of CX-8998, a Selective Modulator of the T-Type Calcium Channel in Inadequately Treated Moderate to Severe Essential Tremor: T-CALM Study Design and Methodology for Efficacy Endpoint and Digital Biomarker Selection.

Background: Essential tremor (ET) is a common, progressive neurological syndrome with bilateral upper-limb dysfunction of at least 3-year duration, with or without tremor in other body locations. This disorder has a negative impact on daily function and quality of life. A single oral therapy has been approved by FDA for ET. Off-label pharmacotherapies have inadequate efficacy and poor tolerability with high rates of patient dissatisfaction and discontinuation. Safe and efficacious pharmacotherapies are urgently needed to decrease tremor and improve daily living. T-CALM (Tremor-CAv3 modulation) protocol is designed to assess safety and efficacy of CX-8998, a selective modulator of the T-type calcium channel, for ET therapy.Methods/Design: T-CALM is a phase 2, proof of concept, randomized, double-blind, placebo-controlled trial. Titrated doses of CX-8998 to 10 mg BID or placebo will be administered for 28 days to moderate to severe ET patients who are inadequately treated with existing therapies. The primary endpoint will be change from baseline to day 28 of The Essential Tremor Rating Assessment Performance Subscale (TETRAS-PS). Secondary efficacy endpoints for clinician and patient perception of daily function will include TETRAS Activity of Daily Living (ADL), Quality of Life in Essential Tremor Questionnaire (QUEST), Clinical Global Impression-Improvement (CGI-I), Patient Global Impression of Change (PGIC), and Goal Attainment Scale (GAS). Kinesia One, Kinesia 360, and iMotor will biometrically evaluate motor function and tremor amplitude. Safety will be assessed by adverse events, physical and neurological exams and laboratory tests. Sample size of 43 patients per group is estimated to have 90% power to detect a 5.5-point difference between CX-8998 and placebo for TETRAS-PS. Efficacy analyses will be performed with covariance (ANCOVA) and 2-sided test at 0.05 significance level.Discussion: T-CALM has a unique design with physician rating scales, patient-focused questionnaires and scales and objective motor measurements to assess clinically meaningful and congruent efficacy. Patient perception of ET debilitation and therapy with CX-8998 will be key findings. Overall goal of T-CALM is generation of safety and efficacy data to support a go, no-go decision to further develop CX-8998 for ET. Design of T-CALM may guide future clinical studies of ET pharmacotherapies.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03101241

Primary Tactile Thalamus Spiking Reflects Cognitive Signals.

Little is known about whether information transfer at primary sensory thalamic nuclei is modified by behavioral context. Here we studied the influence of previous decisions/rewards on current choices and preceding spike responses of ventroposterior medial thalamus (VPm; the primary sensory thalamus in the rat whisker-related tactile system). We trained head-fixed rats to detect a ramp-like deflection of one whisker interspersed within ongoing white noise stimulation. Using generative modeling of behavior, we identify two task-related variables that are predictive of actual decisions. The first reflects task engagement on a local scale ("trial history": defined as the decisions and outcomes of a small number of past trials), whereas the other captures behavioral dynamics on a global scale ("satiation": slow dynamics of the response pattern along an entire session). Although satiation brought about a slow drift from Go to NoGo decisions during the session, trial history was related to local (trial-by-trial) patterning of Go and NoGo decisions. A second model that related the same predictors first to VPm spike responses, and from there to decisions, indicated that spiking, in contrast to behavior, is sensitive to trial history but relatively insensitive to satiation. Trial history influences VPm spike rates and regularity such that a history of Go decisions would predict fewer noise-driven spikes (but more regular ones), and more ramp-driven spikes. Neuronal activity in VPm, thus, is sensitive to local behavioral history, and may play an important role in higher-order cognitive signaling.SIGNIFICANCE STATEMENT It is an important question for perceptual and brain functions to find out whether cognitive signals modulate the sensory signal stream and if so, where in the brain this happens. This study provides evidence that decision and reward history can already be reflected in the ascending sensory pathway, on the level of first-order sensory thalamus. Cognitive signals are relayed very selectively such that only local trial history (spanning a few trials) but not global history (spanning an entire session) are reflected.

No-go decision: A newly identified adverse event in orthopaedic surgery -causes and medico-legal implications.

No-go designates a decision not to perform surgery when it becomes apparent that safety and/or feasibility requirements are not met. No-go decisions can occur at any time between patient admission to a hospital department and immediately before the first incision. The primary objective of this study was to assess the causes of no-go decisions reported as healthcare-associated adverse events (HAAEs). Most no-go decisions in orthopaedic surgery are related to problems with medical devices. A preliminary retrospective study assessed HAAEs reported over the 1-year period from 1st October 2014 to 30th September 2015, using the risk-management tool ALARM. A prospective survey was then performed by emailing a 15-item questionnaire to the 1828 members of Orthorisq (the French orthopaedic surgeon accreditation agency). Responses were either yes/no or open. Statistical comparisons were performed, using the paired Wilcoxon signed-rank test to estimate p values. Among reported HAAEs, 5.6% were no-go decisions. Of the 101 reported no-go decisions, 43.5% and 45.2% were due to problems with managing implantable medical devices in the retrospective and prospective assessments, respectively. In over 85% of cases, surgery was cancelled or postponed. Over half the no-go decisions were associated with unnecessary anaesthesia. Checklist completion was performed in only half the cases and was not associated with no-go decisions (p>0.8). This study provides descriptive data on no-go decisions in orthopaedic surgery. Healthcare professionals use many methods to enhance patient safety by preventing adverse events or diminishing their impact. Errors in managing implantable medical devices are the leading cause of no-go decisions. The current checklist is not appropriate for managing implantable medical devices in orthopaedic surgery, in part because it does not include checking devices upon receipt. Before surgery, patients should be informed of the risk of a no-go decision, since unnecessary anaesthesia occurs in over half the cases. IV, prospective study.

BLAST: Bayesian Latent Subgroup Design for Basket Trials Accounting for Patient Heterogeneity

SummaryThe basket trial refers to a new type of phase II cancer trial that evaluates the therapeutic effect of a targeted agent simultaneously in patients with different types of cancer that involve the same genetic or molecular aberration. Although patients who are enrolled in the basket trial have the same molecular aberration, it is common for the targeted agent to be effective for patients with some types of cancer, but not others. We propose a Bayesian latent subgroup trial (BLAST) design to accommodate such treatment heterogeneity across cancer types. We assume that a cancer type may belong to the sensitive subgroup, which is responsive to the treatment, or the insensitive subgroup, which is not responsive to the treatment. Conditionally on the latent subgroup membership of the cancer type, we jointly model the binary treatment response and the longitudinal biomarker measurement that represents the biological activity of the targeted agent. The BLAST design makes the interim go–no-go treatment decision in a group sequential fashion for each cancer type on the basis of accumulating data. The simulation study shows that the BLAST design outperforms existing trial designs. It yields high power to detect the treatment effect for sensitive cancer types that are responsive to the treatment and maintains a reasonable type I error rate for insensitive cancer types that are not responsive to the treatment.

Cardiovascular Outcome Trials of Diabetes and Obesity Drugs: Implications for Conditional Approval and Early Phase Clinical Development

Over the past decade, clinical development and regulatory review of investigational drugs for diabetes and obesity have been guided by heightened standards for pre- and post-marketing assessment of cardiovascular safety. In high-risk patients with type 2 diabetes, several large multicentre cardiovascular outcome trials (CVOTs) have confirmed non-inferiority, i.e. cardiovascular safety for several glucose-lowering agents. More recent diabetes CVOTs have demonstrated major cardiovascular benefits for drugs representing two newer classes, sodium–glucose cotransporter (SGLT)-2 inhibition and glucagon-like peptide (GLP)-1 receptor agonists. Collectively, hard endpoint data from diabetes CVOTs have ushered in a new era of type 2 diabetes drug development and clinical care. Moreover, some unexpected cardiovascular side-effects have been unearthed for certain drugs. With respect to the history of obesity pharmacotherapy, there have been several instances over the years in which weight-reducing medications were withdrawn from the market because of unacceptable cardiotoxicity, including aminorex, fenfluramine and dexfenfluramine, phenylpropanolamine, and sibutramine. Development programmes for novel anti-obesity drugs are also now required to provide evidence of cardiovascular safety. However, while weight reduction with more recently approved anti-obesity medications has been shown to improve multiple cardiometabolic risk factors, more definitive demonstration of cardiovascular risk/benefit through completion of CVOTs is still awaited. Thus, a marked disparity exists between the CVOT evidence bases for cardiovascular safety of newer glucose-lowering and weight-reducing medications. We believe that in this modern era of metabolic drug development cardiovascular effects of new drug candidates can and should be more rigorously assessed during the early phases of development, to inform go-/no-go decisions. Incorporating advanced imaging-, circulating-, and/or functional biomarkers into early phase development has the potential to identify early signals of cardiovascular risk or benefit, that may not be readily apparent through routine monitoring of traditional risk factors that have been relied upon to date.