Causes of competitive analysis failure: Understanding and responding to problems at the individual level.

It ought to be a fairly safe assumption that a CI analyst would want to perform the analysis task and execute their responsibilities successfully over time. Such competencies should come with added experience on the job, as should the ability to reduce the risk of failure by diagnosing potential pitfalls. This paper presents a) a unique four-level hierarchical model of analysis failure, b) ten key continua of competitive analysis skills which we believe an analyst has to master before they can consider themselves to be truly competent in their work, c) a discussion on the paucity of high quality teaching of these skills, and d) presents eight guiding principles which a firm should consider in an attempt to improve individual performance and reduce the potential for analysis failure. Our purpose in identifying the possibility and causes of analytical failure is that we believe much can be learned by managers and practitioners from studying failures. This learning can ultimately contribute towards creating a more successful analysis function which can only be beneficial to all concerned

Applications of neuroimaging to disease-modification trials in Alzheimer's disease.

Critical to development of new therapies for Alzheimer's disease (AD) is the ability to detect clinical or pathological change over time. Clinical outcome measures typically used in therapeutic trials have unfortunately proven to be relatively variable and somewhat insensitive to change in this slowly progressive disease. For this reason, development of surrogate biomarkers that identify significant disease-associated brain changes are necessary to expedite treatment development in AD. Since AD pathology is present in the brain many years prior to clinical manifestation, ideally we want to develop biomarkers of disease that identify abnormal brain structure or function even prior to cognitive decline. Magnetic resonance imaging, fluorodeoxyglucose positron emission tomography, new amyloid imaging techniques, and spinal fluid markers of AD all have great potential to provide surrogate endpoint measures for AD pathology. The Alzheimer's disease neuroimaging initiative (ADNI) was developed for the distinct purpose of evaluating surrogate biomarkers for drug development in AD. Recent evidence from ADNI demonstrates that imaging may provide more sensitive, and earlier, measures of disease progression than traditional clinical measures for powering clinical drug trials in Alzheimer's disease. This review discusses recently presented data from the ADNI dataset, and the importance of imaging in the future of drug development in AD