Evaluation of ANPR trials for traffic policing in Queensland. Report to the Queensland Police Service, State Traffic Support Branch

In response to the Travelsafe Committee Report No. 51 – report on the inquiry into Automatic Plate Recognition Technology – it was recommended that the Queensland Police Service continue to trial the deployment of ANPR technology for traffic enforcement work and to evaluate the road safety impacts and operational effectiveness of the technology. As such, the purpose of this report is to provide an independent evaluation of a trial of ANPR that was conducted by a project team within the State Traffic Support Branch of the Queensland Police Service (QPS) and provide recommendations as to the applicability and usability of the technology for use throughout Queensland...

Reliable, cloud-based communication for multi-robot systems

In contrast to single robotic agent, multi-robot systems are highly dependent on reliable communication. Robots have to synchronize tasks or to share poses and sensor readings with other agents, especially for co-operative mapping task where local sensor readings are incorporated into a global map. The drawback of existing communication frameworks is that most are based on a central component which has to be constantly within reach. Additionally, they do not prevent data loss between robots if a failure occurs in the communication link. During a distributed mapping task, loss of data is critical because it will corrupt the global map. In this work, we propose a cloud-based publish/subscribe mechanism which enables reliable communication between agents during a cooperative mission using the Data Distribution Service (DDS) as a transport layer. The usability of our approach is verified by several experiments taking into account complete temporary communication loss.

Australians may get their own stop online piracy act #SOPA: Christmas time for copyright owners

Christmas has come early for copyright owners in Australia. The film company, Roadshow, the pay television company Foxtel, and Rupert Murdoch's News Corp and News Limited--as well as copyright industries--have been clamoring for new copyright powers and remedies. In the summer break, the Coalition Government has responded to such entreaties from its industry supporters and donors, with a new package of copyright laws and policies. There has been significant debate over the proposals between the odd couple of Attorney-General George Brandis and the Minister for Communications, Malcolm Turnbull. There have been deep, philosophical differences between the two Ministers over the copyright agenda. The Attorney-General George Brandis has supported a model of copyright maximalism, with strong rights and remedies for the copyright empires in film, television, and publishing. He has shown little empathy for the information technology companies of the digital economy. The Attorney-General has been impatient to press ahead with a copyright regime. The Minister for Communications, Malcolm Turnbull, has been somewhat more circumspect, recognizing that there is a need to ensure that copyright laws do not adversely impact upon competition in the digital economy. The final proposal is a somewhat awkward compromise between the discipline-and-punish regime preferred by Brandis, and the responsive regulation model favored by Turnbull. In his new book, Information Doesn't Want to Be Free: Laws for the Internet Age, Cory Doctorow has some sage advice for copyright owners: Things that don't make money: Complaining about piracy. Calling your customers thieves. Treating your customers like thieves. In this context, the push by copyright owners and the Coalition Government to have a copyright crackdown may well be counter-productive to their interests.

Development of a new ultrasound-based system for tracking motion of the human lumbar spine: Reliability, stability and repeatability during forward bending movement trials

The aim of this study was to develop a new method for quantifying intersegmental motion of the spine in an instrumented motion segment L4–L5 model using ultrasound image post-processing combined with an electromagnetic device. A prospective test–retest design was employed, combined with an evaluation of stability and within- and between-day intra-tester reliability during forward bending by 15 healthy male patients. The accuracy of the measurement system using the model was calculated to be ± 0.9° (standard deviation = 0.43) over a 40° range and ± 0.4 cm (standard deviation = 0.28) over 1.5 cm. The mean composite range of forward bending was 15.5 ± 2.04° during a single trial (standard error of the mean = 0.54, coefficient of variation = 4.18). Reliability (intra-class correlation coefficient = 2.1) was found to be excellent for both within-day measures (0.995–0.999) and between-day measures (0.996–0.999). Further work is necessary to explore the use of this approach in the evaluation of biomechanics, clinical assessments and interventions.

Comparator clinical trials of surrogate endpoints with albiglutide are in HARMONY

Introduction: Agonists of glucagon-like peptide-1 (GLP-1) receptors are used in the treatment of type 2 diabetes. Albiglutide is a new long acting GLP-1 receptor agonist being developed for once-weekly use. Areas covered: This evaluation is of 2 clinical trials in the HARMONY clinical trials series. HARMONY 3 compares albiglutide to sitagliptin and glimepiride in subjects with type 2 diabetes poorly controlled with metformin, and HARMONY 6 compares albiglutide to insulin lispro in subjects poorly controlled with slow/medium release preparations of insulin. Expert opinion: Both studies showed that albiglutide lowered HbA1c, and had advantages over its comparator drugs. However, questions remain about the safety of albiglutide. Albiglutide is not being used in subjects with a history of thyroid cancer, as it is not known whether this is a rare adverse effect with albiglutide. Also, the safety of albiglutide in subjects with type 2 diabetes and high cardiovascular risk is unknown.

Are we waiting too long for the cardiovascular outcome trials with the glucagon-like peptide-1 receptor agonists?

Several new medicines are in development for the treatment of type 2 diabetes, and cardiovascular outcome trials are the gold standard for these medicines. This editorial demonstrates that despite being available for over 10 years, there are no cardiovascular outcome studies for any of the glucagon-like peptide-1 (GLP-1) receptor agonists, which demonstrate cardiovascular safety or benefit in subjects with high cardiovascular risk. The author argues that the FDA should be ensuring that clinical outcome studies for subjects with type 2 diabetes and high cardiovascular risk be undertaken in a timelier manner.

After 10 years of clinical trials with liraglutide, do we know whether it is beneficial in diabetes?

Type 2 diabetes remains an escalating world-wide problem, despite a range of treatments. The revelation that insulin secretion is under the control of a gut hormone, glucagon-like peptide 1 (GLP-1), led to a new paradigm in the management of type 2 diabetes. Liraglutide is a long acting GLP-1 receptor agonist used in the treatment of type 2 diabetes. The review considers the clinical trials with liraglutide. There are many comparator trials between liraglutide and other medicines for the treatment of type 2 diabetes, and these trials have shown that liraglutide lowers HbA1c and body weight, and is well tolerated. A large cardiovascular safety trial with liraglutide is presently being undertaken. After 10 years of clinical trials with liraglutide, we do not know whether liraglutide has cardiovascular safety in subjects with type 2 diabetes and high cardiovascular risk. Although this is not a requirement for registration by the Food and Drug Administration (FDA), in my opinion, they should reconsider this. We also do not presently know whether liraglutide has any beneficial effects on clinical cardiovascular outcomes.

A method for matching patients to advanced prostate cancer clinical trials

Objective: To illustrate a new method for simplifying patient recruitment for advanced prostate cancer clinical trials using natural language processing techniques. Background: The identification of eligible participants for clinical trials is a critical factor to increase patient recruitment rates and an important issue for discovery of new treatment interventions. The current practice of identifying eligible participants is highly constrained due to manual processing of disparate sources of unstructured patient data. Informatics-based approaches can simplify the complex task of evaluating patient’s eligibility for clinical trials. We show that an ontology-based approach can address the challenge of matching patients to suitable clinical trials. Methods: The free-text descriptions of clinical trial criteria as well as patient data were analysed. A set of common inclusion and exclusion criteria was identified through consultations with expert clinical trial coordinators. A research prototype was developed using Unstructured Information Management Architecture (UIMA) that identified SNOMED CT concepts in the patient data and clinical trial description. The SNOMED CT concepts model the standard clinical terminology that can be used to represent and evaluate patient’s inclusion/exclusion criteria for the clinical trial. Results: Our experimental research prototype describes a semi-automated method for filtering patient records using common clinical trial criteria. Our method simplified the patient recruitment process. The discussion with clinical trial coordinators showed that the efficiency in patient recruitment process measured in terms of information processing time could be improved by 25%. Conclusion: An UIMA-based approach can resolve complexities in patient recruitment for advanced prostate cancer clinical trials.

Manufacturing and use of human placenta-derived mesenchymal stromal cells for phase I clinical trials: Establishment and evaluation of a protocol

Background/Aim. Mesenchymal stromal cells (MSCs) have been utilised in many clinical trials as an experimental treatment in numerous clinical settings. Bone marrow remains the traditional source tissue for MSCs but is relatively hard to access in large volumes. Alternatively, MSCs may be derived from other tissues including the placenta and adipose tissue. In an initial study no obvious differences in parameters such as cell surface phenotype, chemokine receptor display, mesodermal differentiation capacity or immunosuppressive ability, were detected when we compared human marrow derived- MSCs to human placenta-derived MSCs. The aim of this study was to establish and evaluate a protocol and related processes for preparation placenta-derived MSCs for early phase clinical trials. Methods. A full-term placenta was taken after delivery of the baby as a source of MSCs. Isolation, seeding, incubation, cryopreservation of human placentaderived MSCs and used production release criteria were in accordance with the complex regulatory requirements applicable to Code of Good Manufacturing Practice manufacturing of ex vivo expanded cells. Results. We established and evaluated instructions for MSCs preparation protocol and gave an overview of the three clinical areas application. In the first trial, MSCs were co-transplanted iv to patient receiving an allogeneic cord blood transplant as therapy for treatmentrefractory acute myeloid leukemia. In the second trial, MSCs were administered iv in the treatment of idiopathic pulmonary fibrosis and without serious adverse effects. In the third trial, MSCs were injected directly into the site of tendon damage using ultrasound guidance in the treatment of chronic refractory tendinopathy. Conclusion. Clinical trials using both allogeneic and autologous cells demonstrated MSCs to be safe. A described protocol for human placenta-derived MSCs is appropriate for use in a clinical setting, relatively inexpensive and can be relatively easily adjusted to a different set of regulatory requirements, as applicable to early phase clinical trials.

A simple Bayesian decision-theoretic design for dose-finding trials

A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

Designs for phase I clinical trials with multiple courses of subjects at different doses

The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

A Bayesian decision approach for sample size determination in phase II trials

Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

Isotonic designs for phase I trials

The purpose of a phase I trial in cancer is to determine the level (dose) of the treatment under study that has an acceptable level of adverse effects. Although substantial progress has recently been made in this area using parametric approaches, the method that is widely used is based on treating small cohorts of patients at escalating doses until the frequency of toxicities seen at a dose exceeds a predefined tolerable toxicity rate. This method is popular because of its simplicity and freedom from parametric assumptions. In this payer, we consider cases in which it is undesirable to assume a parametric dose-toxicity relationship. We propose a simple model-free approach by modifying the method that is in common use. The approach assumes toxicity is nondecreasing with dose and fits an isotonic regression to accumulated data. At any point in a trial, the dose given is that with estimated toxicity deemed closest to the maximum tolerable toxicity. Simulations indicate that this approach performs substantially better than the commonly used method and it compares favorably with other phase I designs.