Benefits of Model-based Drug Development: A Rigorous,Planned Case Study

Model-based drug development (MBDD) is useful to make better quantitative decisions within drug development. However, rigorous evaluation of the benefits has been scarce in the literature. In this study, we take a completed development program, retrospectively repeat it in a virtual setting using MBDD methodologies, and compare it to the traditional drug development process. The conclusion is that the use of MBDD could have facilitated more efficient use of resources.     

Adoptive and Nonadoptive Mother–Child Behavioral Interaction: A Comparative Study at 4 Years of Age

Comparable samples of low-risk adopted and non-adopted children and mothers were observed during three tasks at age 4 years. Quality of mother–child interactions, child level of functioning in four domains, and maternal parenting satisfaction and social support were assessed. Adopted children were as competent as non-adopted children on measures of developmental functioning. Both groups of mothers expressed high satisfaction and support as parents. However, ratings of child, maternal, and dyadic behavior when interacting were all lower for adoptive dyads than for non-adoptive dyads, and adoptive dyads with boys accounted for the maternal and dyadic group differences.     

A candidate-set-free algorithm for generating D-optimal split-plot designs

Summary.  We introduce a new method for generating optimal split-plot designs. These designs are optimal in the sense that they are efficient for estimating the fixed effects of the statistical model that is appropriate given the split-plot design structure. One advantage of the method is that it does not require the prior specification of a candidate set. This makes the production of split-plot designs computationally feasible in situations where the candidate set is too large to be tractable. The method allows for flexible choice of the sample size and supports inclusion of both continuous and categorical factors. The model can be any linear regression model and may include arbitrary polynomial terms in the continuous factors and interaction terms of any order. We demonstrate the usefulness of this flexibility with a 100-run polypropylene experiment involving 11 factors where we found a design that is substantially more efficient than designs that are produced by using other approaches.     

Human dimensions of forest management: an empirical study of stakeholder perspectives

Although much has been written on the human dimensions of forest management, there has been little empirical investigation of how forest stakeholders themselves conceptualize this domain. We used a conceptual content cognitive mapping (3CM) task along with a short survey to explore the perspectives of 23 forest stakeholders in the Pacific Northwest on the human factors relevant to appropriate forest management. Study participants were chosen from three groups: employees of the U.S. Forest Service at the Mount Baker-Snoqualmie Forest, employees of a large timber company, and area environmentalists. Three distinct human dimensions emerged: Traditional intangible benefits (aesthetic concerns, recreation and cultural resources), Values and expectations (considering multiple values, maintaining public expectations, considering social acceptability and maintaining public confidence in forestry), and Process issues indecision making (public involvement, communication across boundaries, collaboration and taking an interdisciplinary approach). In this article, we discuss these three dimensions, the differences found among the stakeholder groups in the importance they placed on each of these dimensions, and the benefits of the 3CM method in this context.     

Locating genes involved in human diseases

The increasing amount of information that is becoming available about the structure and composition of the DNA constituting the human chromosomes has provided new opportunities to locate genes that affect susceptibilities to a range of diseases. The accurate location of these genes is important in genetic counselling and in understanding the effects of genes that may result in disease. Various methods of analysing the data when DNA information is available at a single marker locus for an affected child and his or her parents are reviewed and applied to data on insulin-dependent diabetes mellitus . The importance of distinguishing between the association of alleles at a marker locus and at a disease locus resulting from chromosomal linkage from that resulting from other causes is emphasized.     

Estimating numbers of infectious units from serial dilution assays

Summary.  The paper concerns the design and analysis of serial dilution assays to estimate the infectivity of a sample of tissue when it is assumed that the sample contains a finite number of indivisible infectious units such that a subsample will be infectious if it contains one or more of these units. The aim of the study is to estimate the number of infectious units in the original sample. The standard approach to the analysis of data from such a study is based on the assumption of independence of aliquots both at the same dilution level and at different dilution levels, so that the numbers of infectious units in the aliquots follow independent Poisson distributions. An alternative approach is based on calculation of the expected value of the total number of samples tested that are not infectious. We derive the likelihood for the data on the basis of the discrete number of infectious units, enabling calculation of the maximum likelihood estimate and likelihood-based confidence intervals. We use the exact probabilities that are obtained to compare the maximum likelihood estimate with those given by the other methods in terms of bias and standard error and to compare the coverage of the confidence intervals. We show that the methods have very similar properties and conclude that for practical use the method that is based on the Poisson assumption is to be recommended, since it can be implemented by using standard statistical software. Finally we consider the design of serial dilution assays, concluding that it is important that neither the dilution factor nor the number of samples that remain untested should be too large.