A Bayesian approach for dose-escalation in a phase I clinical trial incorporating pharmacodynamic endpoints

Bayesian decision procedures have already been proposed for and implemented in Phase I dose-escalation studies in healthy volunteers. The procedures have been based on pharmacokinetic responses reflecting the concentration of the drug in blood plasma and are conducted to learn about the dose-response relationship while avoiding excessive concentrations. However, in many dose-escalation studies, pharmacodynamic endpoints such as heart rate or blood pressure are observed, and it is these that should be used to control dose-escalation. These endpoints introduce additional complexity into the modeling of the problem relative to pharmacokinetic responses. Firstly, there are responses available following placebo administrations. Secondly, the pharmacodynamic responses are related directly to measurable plasma concentrations, which in turn are related to dose. Motivated by experience of data from a real study conducted in a conventional manner, this paper presents and evaluates a Bayesian procedure devised for the simultaneous monitoring of pharmacodynamic and pharmacokinetic responses. Account is also taken of the incidence of adverse events. Following logarithmic transformations, a linear model is used to relate dose to the pharmacokinetic endpoint and a quadratic model to relate the latter to the pharmacodynamic endpoint. A logistic model is used to relate the pharmacokinetic endpoint to the risk of an adverse event.

Control of cocoa swollen shoot disease by eradicating infected trees in Ghana: A survey of treated and replanted areas

Cocoa farms that had been treated and replanted in Ghana during the most recent phase of the cocoa swollen shoot virus (CSSV) eradication campaign were surveyed. Farms that were replanted close to adjoining old cocoa farms or which contained old trees were common in most (38) of the 41 cocoa farms surveyed. CSSV infections were apparent in 20 (53%) out of these 38 farms and they pose a serious risk of causing early infections of the re-planted farms. Control strategies that isolate the newly planted farms by a boundary of immune crops as barriers to reduce CSSV re-infection are discussed. (c) 2005 Elsevier Ltd. All rights reserved.

Local roles of TGF-beta superfamily members in the control of ovarian follicle development

Members of the transforming growth factor-beta (TGF-beta) superfamily have wide-ranging influences on many tissue and organ systems including the ovary. Two recently discovered TGF-beta superfamily members, growth/differentiation factor-9 (GDF-9) and bone morphogenetic protein-15 (BMP-15; also designated as GDF-9B) are expressed in an oocyte-specific manner from a very early stage and play a key role in promoting follicle growth beyond the primary stage. Follicle growth to the small antral stage does not require gonadotrophins but appears to be driven by local autocrine/paracrine signals from both somatic cell types (granulosa and theca) and from the oocyte. TGF-beta superfamily members expressed by follicular cells and implicated in this phase of follicle development include TGF-beta, activin, GDF-9/9B and several BMPs. Acquisition of follicle-stimulating hormone (FSH) responsiveness is a pre-requisite for growth beyond the small antral stage and evidence indicates an autocrine role for granulosa-derived activin in promoting granulosa cell proliferation, FSH receptor expression and aromatase activity. Indeed, some of the effects of FSH on granulosa cells may be mediated by endogenous activin. At the same time, activin may act on theca cells to attenuate luteinizing hormone (LH)-dependent androgen production in small to medium-size antral follicles. Dominant follicle selection appears to depend on differential FSH sensitivity amongst a growing cohort of small antral follicles. Activin may contribute to this selection process by sensitizing those follicles with the highest "activin tone" to FSH. Production of inhibin, like oestradiol, increases in selected dominant follicles, in an FSH- and insulin-like growth factor-dependent manner and may exert a paracrine action on theca cells to upregulate LH-induced secretion of androgen, an essential requirement for further oestradiol secretion by the pre-ovulatory follicle. Like activin, BMP-4 and -7 (mostly from theca), and BMP-6 (mostly from oocyte), can enhance oestradiol and inhibin secretion by bovine granulosa cells while suppressing progesterone secretion; this suggests a functional role in delaying follicle luteinization and/or atresia. Follistatin, on the other hand, may favor luteinization and/or atresia by bio-neutralizing intrafollicular activin and BMPs. Activin receptors are expressed by the oocyte and activin may have a further intrafollicular role in the terminal stages of follicle differentiation to promote oocyte maturation and developmental competence. In a reciprocal manner, oocyte-derived GDF-9/9B may act on the surrounding cumulus granulosa cells to attenuate oestradiol output and promote progesterone and hyaluronic acid production, mucification and cumulus expansion.(C) 2003 Elsevier Science B.V. All rights reserved.

Self-assembly of two-component gels: stoichiometric control and component selection

Two-component systems capable of self-assembling into soft gel-phase materials are of considerable interest due to their tunability and versatility. This paper investigates two-component gels based on a combination of a L-lysine-based dendron and a rigid diamine spacer (1,4-diaminobenzene or 1,4-diaminocyclohexane). The networked gelator was investigated using thermal measurements, circular dichroism, NMR spectroscopy and small angle neutron scattering (SANS) giving insight into the macroscopic properties, nanostructure and molecular-scale organisation. Surprisingly, all of these techniques confirmed that irrespective of the molar ratio of the components employed, the "solid-like" gel network always consisted of a 1:1 mixture of dendron/diamine. Additionally, the gel network was able to tolerate a significant excess of diamine in the "liquid-like" phase before being disrupted. In the light of this observation, we investigated the ability of the gel network structure to evolve from mixtures of different aromatic diamines present in excess. We found that these two-component gels assembled in a component-selective manner, with the dendron preferentially recognising 1,4-diaminobenzene (>70%). when similar competitor diamines (1,2- and 1,3-diaminobenzene) are present. Furthermore, NMR relaxation measurements demonstrated that the gel based oil 1,4-diaminobenzene was better able to form a selective ternary complex with pyrene than the gel based oil 1,4-diaminocyclohexane, indicative of controlled and selective pi-pi interactions within a three-component assembly. As such, the results ill this paper demonstrate how component selection processes in two-component gel systems call control hierarchical self-assembly.

Prospects for bio-molecular control using femtosecond transients parametrised in the wavelet domain [poster]

We discuss the parametrisation of am-plitude and phase genes corre-sponding to space encoded femto-second transients in the wavelet domain. Differential evolution is used to improve the speed of con-vergence of the genetic algorithm. We discuss prospects of bio-molecular control using such methodology.

'Flat phase' PID controllers

Flat Phase PID Controllers have the property that the phase of the transfer function round the associated feedback loop is constant or flat around the design frequency, with the aim that the phase margin and overshoot to a step response is unaffected when the gain of the device under control changes. Such designs have been achieved using Bode Integrals and by ensuring the phase is the same at two frequencies. This paper extends the ‘two frequency’ controller and describes a novel three frequency controller. The different design strategies arc compared.

Switching curve control of functional electrical stimulation assisted rowing exercise in paraplegia

An indoor rowing machine has been modified for functional electrical stimulation (FES) assisted rowing exercise in paraplegia. To perform the rowing manoeuvre successfully, however, the voluntarily controlled upper body movements must be co-ordinated with the movements of the electrically stimulated paralysed legs. To achieve such co-ordination, an automatic FES controller was developed that employs two levels of hierarchy. At the upper level, a finite state controller identifies the state or phase of the rowing cycle and activates the appropriate lower-level controller, in which electrical stimulation to the paralysed leg muscles is applied with reference to switching curves representing the desired seat velocity as a function of the seat position. In a pilot study, the hierarchical control of FES rowing was shown to be intuitive, reliable and easy to use. Compared with open-loop control of stimulation, all three variants of the closed-loop switching curve controllers used less muscle stimulation per rowing cycle (73% of the open-loop control on average). Further, the closed-loop controller that used switching curves derived from normal rowing kinematics used the lowest muscle stimulation (65% of the open-loop control) and was the most convenient to use for the client.

Simplified parameter adaptive control

A simple parameter adaptive controller design methodology is introduced in which steady-state servo tracking properties provide the major control objective. This is achieved without cancellation of process zeros and hence the underlying design can be applied to non-minimum phase systems. As with other self-tuning algorithms, the design (user specified) polynomials of the proposed algorithm define the performance capabilities of the resulting controller. However, with the appropriate definition of these polynomials, the synthesis technique can be shown to admit different adaptive control strategies, e.g. self-tuning PID and self-tuning pole-placement controllers. The algorithm can therefore be thought of as an embodiment of other self-tuning design techniques. The performances of some of the resulting controllers are illustrated using simulation examples and the on-line application to an experimental apparatus.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Power control requirements in linear decorrelating detectors for CDMA

This paper addresses the effects of synchronisation errors (time delay, carrier phase, and carrier frequency) on the performance of linear decorrelating detectors (LDDs). A major effect is that all LDDs require certain degree of power control in the presence of synchronisation errors. The multi-shot sliding window algorithm (SLWA) and hard decision method (HDM) are analysed and their power control requirements are examined. Also, a more efficient one-shot detection scheme, called “hard-decision based coupling cancellation”, is proposed and analysed. These schemes are then compared with the isolation bit insertion (IBI) approach in terms of power control requirements.

Performance analysis of the unconstrained FxLMS algorithm for active noise control

The paper analyzes the performance of the unconstrained filtered-x LMS (FxLMS) algorithm for active noise control (ANC), where we remove the constraints on the controller that it must be causal and has finite impulse response. It is shown that the unconstrained FxLMS algorithm always converges to, if stable, the true optimum filter, even if the estimation of the secondary path is not perfect, and its final mean square error is independent of the secondary path. Moreover, we show that the sufficient and necessary stability condition for the feedforward unconstrained FxLMS is that the maximum phase error of the secondary path estimation must be within 90°, which is the only necessary condition for the feedback unconstrained FxLMS. The significance of the analysis on a practical system is also discussed. Finally we show how the obtained results can guide us to design a robust feedback ANC headset.

Brain computer interface control via functional connectivity dynamics

The dynamics of inter-regional communication within the brain during cognitive processing – referred to as functional connectivity – are investigated as a control feature for a brain computer interface. EMDPL is used to map phase synchronization levels between all channel pair combinations in the EEG. This results in complex networks of channel connectivity at all time–frequency locations. The mean clustering coefficient is then used as a descriptive feature encapsulating information about inter-channel connectivity. Hidden Markov models are applied to characterize and classify dynamics of the resulting complex networks. Highly accurate levels of classification are achieved when this technique is applied to classify EEG recorded during real and imagined single finger taps. These results are compared to traditional features used in the classification of a finger tap BCI demonstrating that functional connectivity dynamics provide additional information and improved BCI control accuracies.

Seamless phase II/III designs

In recent years, there has been a drive to save development costs and shorten time-to-market of new therapies. Research into novel trial designs to facilitate this goal has led to, amongst other approaches, the development of methodology for seamless phase II/III designs. Such designs allow treatment or dose selection at an interim analysis and comparative evaluation of efficacy with control, in the same study. Methods have gained much attention because of their potential advantages compared to conventional drug development programmes with separate trials for individual phases. In this article, we review the various approaches to seamless phase II/III designs based upon the group-sequential approach, the combination test approach and the adaptive Dunnett method. The objective of this article is to describe the approaches in a unified framework and highlight their similarities and differences to allow choice of an appropriate methodology by a trialist considering conducting such a trial.

A tutorial on pseudospectral methods for computational optimal control

[English] This paper is a tutorial introduction to pseudospectral optimal control. With pseudospectral methods, a function is approximated as a linear combination of smooth basis functions, which are often chosen to be Legendre or Chebyshev polynomials. Collocation of the differential-algebraic equations is performed at orthogonal collocation points, which are selected to yield interpolation of high accuracy. Pseudospectral methods directly discretize the original optimal control problem to recast it into a nonlinear programming format. A numerical optimizer is then employed to find approximate local optimal solutions. The paper also briefly describes the functionality and implementation of PSOPT, an open source software package written in C++ that employs pseudospectral discretization methods to solve multi-phase optimal control problems. The software implements the Legendre and Chebyshev pseudospectral methods, and it has useful features such as automatic differentiation, sparsity detection, and automatic scaling. The use of pseudospectral methods is illustrated in two problems taken from the literature on computational optimal control. [Portuguese] Este artigo e um tutorial introdutorio sobre controle otimo pseudo-espectral. Em metodos pseudo-espectrais, uma funcao e aproximada como uma combinacao linear de funcoes de base suaves, tipicamente escolhidas como polinomios de Legendre ou Chebyshev. A colocacao de equacoes algebrico-diferenciais e realizada em pontos de colocacao ortogonal, que sao selecionados de modo a minimizar o erro de interpolacao. Metodos pseudoespectrais discretizam o problema de controle otimo original de modo a converte-lo em um problema de programa cao nao-linear. Um otimizador numerico e entao empregado para obter solucoes localmente otimas. Este artigo tambem descreve sucintamente a funcionalidade e a implementacao de um pacote computacional de codigo aberto escrito em C++ chamado PSOPT. Tal pacote emprega metodos de discretizacao pseudo-spectrais para resolver problemas de controle otimo com multiplas fase. O PSOPT permite a utilizacao de metodos de Legendre ou Chebyshev, e possui caractersticas uteis tais como diferenciacao automatica, deteccao de esparsidade e escalonamento automatico. O uso de metodos pseudo-espectrais e ilustrado em dois problemas retirados da literatura de controle otimo computacional.