Progress toward re‐engineering non‐ribosomal peptide synthetase proteins: a potential new source of pharmacological agents

Many important pharmaceutical agents, including vancomycin, bleomycin, cyclosporin, and several antibiotics, are produced by non‐ribosomal peptide synthetase (NRPS) enzymes in microorganisms. The NRPS pathway produces an extensive library of products using multienzyme complexes acting in an assembly‐line fashion. Engineering an NRPS system to produce an even greater variety of products, some of which may also have beneficial therapeutic value, would be an enormous advantage. Several approaches have been successful in generating novel NRPS products: mutational biosynthesis during which nonnatural substrates are fed to an organism; domain and module swapping between different species to generate hybrid enzymes; and rational site‐directed mutagenesis, based either on phylogeny or computational prediction, intended to switch substrate specificity and produce altered products. This review will highlight the progress in these areas and describe research in the future that will extend the capacity for re‐engineering NRPS systems. Drug Dev. Res. 66:9–18, 2006. © 2006 Wiley‐Liss, Inc.     

B cells as a target of immune modulation

B cells have recently been identified as an integral component of the immune system; they play a part in autoimmunity through antigen presentation, antibody secretion, and complement activation. Animal models of multiple sclerosis (MS) suggest that myelin destruction is partly mediated through B cell activation (and plasmablasts). MS patients with evidence of B cell involvement, as compared to those without, tend to have a worse prognosis. Finally, the significant decrease in new gadolinium-enhancing lesions, new T2 lesions, and relapses in MS patients treated with rituximab (a monoclonal antibody against CD20 on B cells) leads us to the conclusion that B cells play an important role in MS and that immune modulation of these cells may ameliorate the disease. This article will explore the role of B cells in MS and the rationale for the development of B cell–targeted therapeutics. MS is an immune-mediated disease that affects over 2 million people worldwide and is the number one cause of disability in young patients. Most therapeutic targets have focused on T cells; however, recently, the focus has shifted to the role of B cells in the pathogenesis of MS and the potential of B cells as a therapeutic target.     

螺旋CT及CAD技术在人工关节定制设计中的应用研究

随着生物医用材料研制和医学的迅速发展，以及生活水平、医疗保健、康复水平的提高，人们对自身组织、器官及骨骼缺损的修复和置换方面的要求日益提高，尤其对人造骨骼和人工关节的需求越来越广泛。由于计算机断层成像技术CT（computed tomography）已经成为显示和研究人体内部结构非常有用的手段，将计算机辅助设计技术CAD（Computer aided design）和计算机辅助工程CAE（Computer aided Engineering）等相关技术应用于人造骨骼和内置假体的设计，不仅可以提高产品的设计质量，同时，结合CT和计算机三维重建方法，     

Design and conduct of occupational epidemiology studies: III. Design aspects of case-control studies

Currently available approaches for the design of occupational case-control studies are reviewed. An accompanying paper reviews methods of analysis. We commence by drawing a distinction between cohort-based and registry-based studies. Methods for selecting cases and controls are then reviewed, including cumulative incidence and incidence density sampling, matching, sources of controls, and issues in control selection. Finally, the advantages and disadvantages of the case-control approach are summarized.     

Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations

We consider nested multiple response models which are used extensively in the area of pharmacometrics. Given the conditional nature of such models, differences in predicted responses are a consequence of different assumptions about how the models interact. As such, sequential versus simultaneous and First Order (FO) versus First Order Conditional Estimation (FOCE) techniques have been explored in the literature where it was found that the sequential and FO approaches can produce biased results. It is therefore of interest to determine any design consequences between the various methods and approximations. As optimal design for nonlinear mixed effects models is dependent upon initial parameter estimates and an approximation to the expected Fisher information matrix, it is necessary to incorporate any influence of nonlinearity (or parameter-effects curvature) into our exploration. Hence, sequential versus simultaneous design with FO and FOCE considerations are compared under low, typical and high degrees of nonlinearity. Additionally, predicted standard errors of parameters are also compared to empirical estimates formed via a simulation/estimation study in NONMEM. Initially, design theory for nested multiple response models is developed and approaches mentioned above are investigated by considering a pharmacokinetic–pharmacodynamic model found in the literature. We consider design for situations where all responses are continuous and extend this methodology to the case where a response may be a discrete random variable. In particular, for a binary response pharmacodynamic model, it is conjectured that such responses will offer little information about all parameters and hence a sequential optimization, in the form of product design optimality, may yield near optimal designs.     

芪月降脂片制剂处方的优化

[目的 ]优化芪月降脂片的制剂处方 .[方法 ]采用正交设计和多指标综合评分法对已筛选出的药剂辅料进行处方优化 .[结果 ]最佳制剂处方为糖粉 50 g ,辅料X 50g ,微晶纤维素 75g .[结论 ]该处方合理 ,成型性好     

Fisher information matrix for nonlinear mixed effects multiple response models: Evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model

We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic–pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation–maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first‐order linearization estimation methods implemented in the NONMEM software (first‐order (FO), first‐order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite. Copyright © 2009 John Wiley & Sons, Ltd.     

Genetics in multiple sclerosis: past and future perspectives

The enormous development in the field of molecular genetics during the last decades has lead to optimism concerning the possibilities for identifying the causes of multiple sclerosis (MS) through genetic studies. However, we have learned that dense mapping of large sample sets is needed, which only can be achieved through large collaborative studies. The contribution from each yet unidentified gene is probably weaker than that of the well established human leukocyte antigen association. The ultimate goal of the search for susceptibility genes in MS is to develop diagnostic tools and better treatments that can prevent or reduce the development of symptoms of this often devastating disease.     

概念设计在结构设计中的重要性

通过对某一工程的设计分析，表明了概念设计在结构设计中的重要性。     

One‐ and two‐stage design proposals for a phase II trial comparing three active treatments with control using an ordered categorical endpoint

Phase II clinical trials are performed to investigate whether a novel treatment shows sufficient promise of efficacy to justify its evaluation in a subsequent definitive phase III trial, and they are often also used to select the dose to take forward. In this paper we discuss different design proposals for a phase II trial in which three active treatment doses and a placebo control are to be compared in terms of a single‐ordered categorical endpoint. The sample size requirements for one‐stage and two‐stage designs are derived, based on an approach similar to that of Dunnett. Detailed computations are prepared for an illustrative example concerning a study in stroke. Allowance for early stopping for futility is made. Simulations are used to verify that the specified type I error and power requirements are valid, despite certain approximations used in the derivation of sample size. The advantages and disadvantages of the different designs are discussed, and the scope for extending the approach to different forms of endpoint is considered. Copyright © 2008 John Wiley & Sons, Ltd.