Optimal adaptive randomized designs for clinical trials

Optimal decision-analytic designs are deterministic. Such designsare appropriately criticized in the context of clinical trialsbecause they are subject to assignment bias. On the other hand,balanced randomized designs may assign an excessive number ofpatients to a treatment arm that is performing relatively poorly.We propose a compromise between these two extremes, one thatachieves some of the good characteristics of both. We introducea constrained optimal adaptive design for a fully sequentialrandomized clinical trial with k arms and n patients. An r-designis one for which, at each allocation, each arm has probabilityat least r of being chosen, 0 r 1/k. An optimal design amongall r-designs is called r-optimal. An r₁-design is also an r₂-designif r₁ r₂. A design without constraint is the special case r = 0and a balanced randomized design is the special case r = 1/k.The optimization criterion is to maximize the expected overallutility in a Bayesian decision-analytic approach, where utilityis the sum over the utilities for individual patients over a‘patient horizon’ N. We prove analytically thatthere exists an r-optimal design such that each patient is assignedto a particular one of the arms with probability 1 – (k – 1)r,and to the remaining arms with probability r. We also show thatthe balanced design is asymptotically r-optimal for any givenr, 0 r < 1/k, as N/n  . This implies that everyr-optimal design is asymptotically optimal without constraint.Numerical computations using backward induction for k = 2arms show that, in general, this asymptotic optimality featurefor r-optimal designs can be accomplished with moderate trialsize n if the patient horizon N is large relative to n. We alsoshow that, in a trial with an r-optimal design, r < 1/2,fewer patients are assigned to an inferior arm than when followinga balanced design, even for r-optimal designs having the samestatistical power as a balanced design. We discuss extensionsto various clinical trial settings.     

The economics of escape behaviour in the pea aphid,Acyrthosiphon pisum

Summary Pea aphids have several alternative responses to the detection of alarm pheromone produced by conspecifics. One of these, dropping from the feeding site to the ground, is potentially costly owing to the risk of desiccation-induced mortality on the ground before another host plant can be reached. Both dropping and walking from the feeding site incur a cost due to lost feeding opportunity. The aphids' decision as to which anti-predator tactic to use should be sensitive to the costs of their behaviour. Consequently, aphids should be less likely to drop when the risk of desiccation is higher, and less likely to drop or walk when the lost opportunity cost is higher. We tested these predictions by manipulating climatic severity (temperature and humidity) and host quality, respectively. As predicted, aphids are less likely to drop or walk in response to pheromone when feeding on high quality than on low quality hosts, and less likely to drop when the environment is hot and dry than when it is more benign. The latter is true whether the aphids are feeding on real or simulated leaves. Since all aphids were of the same clone, these results show that individual aphid genotypes possess the ability to adaptively modify their escape behaviour with changes in prevailing conditions. A number of other behavioural observations in the aphid literature may be interpreted in an economic or cost-benefit framework. The approach holds considerable promise for understanding many aspects of the anti-predator behaviour of aphids and other animals.     

Ants andPolyommatus icarus immatures (Lycaenidae) —sex-related developmental benefits and costs of ant attendance

Summary Third and fourth instar larvae and pupae of the facultatively myrmecophilous Palaearctic blue butterflyPolyommatus icarus showed no alteration in developmental time when reared in the presence of two species ofLasius ants. Sex differences were observed in larval growth and pupal weight, with males growing larger and faster. Sex-related differences also occurred in the costs and benefits of ant-attendance. Male pupal masses tended to be larger in individuals associated with ants, and their pupal weight loss was not enhanced by ant attendance. This positive developmental effect of myrmecophily is tentatively attributed to a stimulating influence of ants on caterpillar feeding behavior. In contrast, females associated with ants tended to lose more weight during the pupal stage. Hence there is evidence for developmental benefits, rather than costs, of myrmecophily in maleP. icarus immatures, whereas ant attendance appears to be more costly for females during the pupal stage. These findings are discussed in relation to data on other myrmecophilous lycaenid species. It is suggested that maintaining low-level myrmecophily and its related organs is a comparatively inexpensive evolutionary stable strategy among this butterfly group.     

OPTSDNA: Performance evaluation of an efficient distributed bioinformatics system for DNA sequence analysis

Storage of sequence data is a big concern as the amount of data generated is exponential in nature at several locations. Therefore,there is a need to develop techniques to store data using compression algorithm. Here we describe optimal storage algorithm(OPTSDNA) for storing large amount of DNA sequences of varying length. This paper provides performance analysis of optimalstorage algorithm (OPTSDNA) of a distributed bioinformatics computing system for analysis of DNA sequences. OPTSDNAalgorithm is used for storing various sizes of DNA sequences into database. DNA sequences of different lengths were stored byusing this algorithm. These input DNA sequences are varied in size from very small to very large. Storage size is calculated by thisalgorithm. Response time is also calculated in this work. The efficiency and performance of the algorithm is high (in size calculationwith percentage) when compared with other known with sequential approach.