Data visualization during the early stages of drug discovery

Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

New product screening in fast moving consumer goods

Theory suggests that the dimensions that are incorporated in the new product screening decision will differ according to the stage of the development process. The outcome of the application of different screening dimensions would be quicker, realistic and more reliable screening decisions. This research project builds on existing new product development and screening literature by investigating new product screening in international fast moving consumer goods companies. It further builds on the existing literature by measuring decision-making relating to projects in 'real time', as managers' responses refer to projects they are currently working on. The introduction of branded consumer products allows us to evolve scales used in new product research by further developing variables relating to branding, promotion and retailer power. The project uncovers multiple dimensions of new product screening and evaluation within this branded product sector. These dimensions are found to differ in their ability to discriminate between two groups of accepted and rejected projects at each of four stages of the new product development process. This investigation provides the intelligence with which managers can determine the likelihood of project acceptance and rejection at different stages of the development process. It highlights the need for managers to apply stage-specific dimensions in the new product screening decision and advocates the redefinition of new product screening from both an academic and managerial perspective. The screening decision should not be viewed as a single, early decision in a product development process, but as a series of stage specific decisions regarding future project potential.

Post-communist recessions re-examined

We apply simple econometric methods to evaluate the factors that determined the length and depth of the post-Communist recessions. Early implementation of the stabilisation and liberalisation programmes made the recessions weaker. Wars had strong negative impact. Initial trade dependence made recessions more serious. The results are discussed with reference to the existing explanations of the 'transitional recessions', in particular Calvo and Coricelli (1992, 1993), Blanchard and Kremer (1997) and Blanchard (1997).

Grading and disease management in national screening for diabetic retinopathy in England and Wales

Aims - A National Screening Programme for diabetic eye disease in the UK is in development. We propose a grading and early disease management protocol to detect sight-threatening diabetic retinopathy and any retinopathy, which will allow precise quality assurance at all steps while minimizing false-positive referral to the hospital eye service. Methods - Expert panel structured discussions between 2000 and 2002 with review of existing evidence and grading classifications. Proposals - Principles of the protocol include: separate grading of retinopathy and maculopathy, minimum number of steps, compatible with central monitoring, expandable for established more complex systems and for research, no lesion counting, no ‘questionable’ lesions, attempt to detect focal exudative, diffuse and ischaemic maculopathy and fast track referral from primary or secondary graders. Sight-threatening diabetic retinopathy is defined as: preproliferative retinopathy or worse, sight-threatening maculopathy and/or the presence of photocoagulation. In the centrally reported minimum data set retinopathy is graded into four levels: none (R0), background (R1), preproliferative (R2), proliferative (R3). Maculopathy and photocoagulation are graded as absent (M0, P0) or present (M1, P1). Discussion - The protocol developed by the Diabetic Retinopathy Grading and Disease Management Working Party represents a new consensus upon which national guidelines can be based leading to the introduction of quality-assured screening for people with diabetes.