关于二次旋转组合设计共用统计方法的研究

本文改进 了二次旋转组合设计的统计方法,使其可为二次正交旋转组合设计和二次通用旋转组合设计所共用,计算简便,有利软件通用。     

Consistent development of bioprocesses from microliter cultures to the industrial scale

Bioprocess development today is slow and expensive compared to chemical process development. A drastic paradigm shift is necessary and possible by the consistent application of engineering strategies that are typically used in the process development phase already in the early product development. Aside from providing a consistent pathway, strategies such as statistical‐based design of experiments, fed‐batch, minibioreactors, new on‐line sensors, process modeling, and control tools in combination with automation of manual steps offer a higher success rate and the opportunity to find the optimum parameters and operation point. This also directly benefits the early phases of biomolecular screening and initial production of small amounts of the target molecule. The paper reviews the bioprocess developmental phases from a business perspective and the available systems and technologies.     

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy).This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable.     

Chemical genomics: a challenge for de novo drug design

De novo design provides an in silico toolkit for the design of novel small molecular structures to a set of specified structural constraints. With the avalanche of bioinformatics data, de novo design is ideally suited for exploring molecules that could be useful for chemical genomics. The design process involves manipulation of the input, modification of structural constraints, and further processing of the de novo generated molecules using various modular toolkits. The development of a theoretical framework for each of these stages will provide novel practical solutions to the problem of creating compounds with maximal chemical diversity. This short review describes the fundamental problems encountered in the application of novel chemical design technologies to chemical genomics by means of a formal representation. This notation helps to outline and clarify ideas and hypotheses that can then be explored using mathematical algorithms. It is only by developing this rigorous foundation that in silico design can progress in a rational way.     

Growth medium and electrolyte—How to combine the different requirements on the reaction solution in bioelectrochemical systems using Cupriavidus necator

Microbial electrosynthesis is a relatively new research field where microbial carbon dioxide fixation based on the energy supplied by a cathode is investigated. Reaction media used in such bioelectrochemical systems have to fulfill requirements of classical biotechnology as well as electrochemistry. The design and characterization of a medium that enables fast electroautotrophic growth of Cupriavidus necator in microbial electrosynthesis was investigated in detail. The identified chloride‐free medium mainly consists of low buffer concentration and is supplied with trace elements. Biotechnologically relevant parameters, such as high‐specific growth rates and short lag phases, were determined for growth characterization. Fast growth under all conditions tested, i.e. heterotrophic, autotrophic and electroautotrophic was achieved. The lag phase was shortened by increasing the FeSO? concentration. Additionally, electrochemical robustness of the reaction media was proven. Under reductive conditions, no deposits on electrodes or precipitations in the media were observed and no detectable hydrogen peroxide evolved. In the bioelectrochemical system, no lag phase occurred and specific growth rate of C. necator was 0.09 h?¹. Using this medium shortens seed train drastically and enables fast electrobiotechnological production processes based on C. necator .     

Flexible Designs for Genomewide Association Studies

Summary .  Genomewide association studies attempting to unravel the genetic etiology of complex traits have recently gained attention. Frequently, these studies employ a sequential genotyping strategy: A large panel of markers is examined in a subsample of subjects, and the most promising markers are genotyped in the remaining subjects. In this article, we introduce a novel method for such designs enabling investigators to, for example, modify marker densities and sample proportions while strongly controlling the family-wise type I error rate. Loss of efficiency is avoided by redistributing conditional type I error rates of discarded markers. Our approach can be combined with cost optimal designs and entails a greater flexibility than all previously suggested designs. Among other features, it allows for marker selections based upon biological criteria instead of statistical criteria alone, or the option to modify the sample size at any time during the course of the project. For practical applicability, we develop a new algorithm, subsequently evaluate it by simulations, and illustrate it using a real data set.     

Design of experiments reveals critical parameters for pilot‐scale freeze‐and‐thaw processing of L‐lactic dehydrogenase

Freezing constitutes an important unit operation of biotechnological protein production. Effects of freeze‐and‐thaw (F/T) process parameters on stability and other quality attributes of the protein product are usually not well understood. Here a design of experiments (DoE) approach was used to characterize the F/T behavior of L‐lactic dehydrogenase (LDH) in a 700‐mL pilot‐scale freeze container equipped with internal temperature and pH probes. In 24‐hour experiments, target temperature between –10 and –38°C most strongly affected LDH stability whereby enzyme activity was retained best at the highest temperature of –10°C. Cooling profile and liquid fill volume also had significant effects on LDH stability and affected the protein aggregation significantly. Parameters of the thawing phase had a comparably small effect on LDH stability. Experiments in which the standard sodium phosphate buffer was exchanged by Tris‐HCl and the non‐ionic surfactant Tween 80 was added to the protein solution showed that pH shift during freezing and protein surface exposure were the main factors responsible for LDH instability at the lower freeze temperatures. Collectively, evidence is presented that supports the use of DoE‐based systematic analysis at pilot scale in the identification of F/T process parameters critical for protein stability and in the development of suitable process control strategies.     

Planning incomplete block experiments when treatments are genetically related

Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.     

Intelligent bioprocessing for haemotopoietic cell cultures using monitoring and design of experiments

The need for successful ex-vivo expansion and directed differentiation of haematopoietic stem cells (HSCs) for therapeutic applications has increased over the past decade. Haematopoietic cell cultures are complex and full characterisation of the process environment has yet to be achieved. The complexity and transient nature of HSC cultures make the identification, maintenance and control of optimal operating conditions challenging. Application of real-time, on-line monitoring techniques and process control strategies enhances the ability to operate bioprocesses of desired reproducibility and high product quality. In this review, we discussed the methods by which in vitro culture information necessary for bioprocess control may be obtained, including process considerations, monitoring and analytical tools, and design of experiments (DOE). The successful application of these tools may result in time- and cost-effective cultures for directed differentiation and expansion of haematopoietic components intended for clinical use.     

响应面法优化蝙蝠蛾拟青霉发酵培养基配方

为了提高虫草无性型蝙蝠蛾拟青霉(Paecilomyces hepiali)菌丝体中的腺苷含量,采用响应面法对其液体发酵培养基配方进行了优化。首先采用Plackett-Burman设计法对影响蝙蝠蛾拟青霉腺苷收率的8个相关因素进行了筛选,从中确定其主要影响因子为马铃薯和蚕蛹粉。然后用最陡爬坡试验逼近上述2个因素的最大响应区域,并通过中心组合设计和响应面分析法,确定了主要影响因子的最佳浓度。优化后的培养基组成为:马铃薯8.25%,蔗糖1%,玉米粉1%,蛋白胨0.5%,蚕蛹粉0.81%,KH2PO40.1%,MgSO4.7H2O 0.1%,(NH4)2 SO40.1%。该配方所产生的蝙蝠蛾拟青霉菌丝体中腺苷含量由优化前的2.15 mg/g(干重)提高到3.44 mg/g(干重)。