How Often Do Safety Signals Occur by Chance in First-in-Human Trials?

Clinicians working on first-in-human clinical studies need to be able to judge whether safety signals observed on an investigational drug were more likely to have occurred by chance or to have been caused by the drug. We retrospectively reviewed 84 Novartis studies including 1234 healthy volunteers receiving placebo, to determine the expected incidence of changes in commonly measured laboratory parameters and vital signs, in the absence of any active agent. We calculated the frequency of random incidence of safety signals, focusing on the liver, cardiovascular system, kidney and pancreas. Using the liver enzyme alanine aminotransferase (ALT) as an example, we illustrate how a predictive model can be used to determine the probability of a given subject to experience an elevation of ALT above the upper limit of the normal range under placebo, conditional on the characteristics of this subject and the study

Advances and unmet needs in genetic, basic and clinical science in Alport syndrome::report from the 2015 International Workshop on Alport Syndrome

Alport syndrome (AS) is a genetic disease characterized by haematuric glomerulopathy variably associated with hearing loss and anterior lenticonus. It is caused by mutations in the COL4A3, COL4A4 or COL4A5 genes encoding the α3α4α5(IV) collagen heterotrimer. AS is rare, but it accounts for >1% of patients receiving renal replacement therapy. Angiotensin-converting enzyme inhibition slows, but does not stop, the progression to renal failure; therefore, there is an urgent requirement to expand and intensify research towards discovering new therapeutic targets and new therapies. The 2015 International Workshop on Alport Syndrome targeted unmet needs in basic science, genetics and diagnosis, clinical research and current clinical care. In three intensive days, more than 100 international experts including physicians, geneticists, researchers from academia and industry, and patient representatives from all over the world participated in panel discussions and breakout groups. This report summarizes the most important priority areas including (i) understanding the crucial role of podocyte protection and regeneration, (ii) targeting mutations by new molecular techniques for new animal models and potential gene therapy, (iii) creating optimal interaction between nephrologists and geneticists for early diagnosis, (iv) establishing standards for mutation screening and databases, (v) improving widespread accessibility to current standards of clinical care, (vi) improving collaboration with the pharmaceutical/biotech industry to investigate new therapies, (vii) research in hearing loss as a huge unmet need in Alport patients and (viii) the need to evaluate the risk and benefit of novel (including 'repurposing') therapies on an international basis

Fetal and infant origins of asthma

Previous studies have suggested that asthma, like other common diseases, has at least part of its origin early in life. Low birth weight has been shown to be associated with increased risks of asthma, chronic obstructive airway disease, and impaired lung function in adults, and increased risks of respiratory symptoms in early childhood. The developmental plasticity hypothesis suggests that the associations between low birth weight and diseases in later life are explained by adaptation mechanisms in fetal life and infancy in response to various adverse exposures. Various pathways leading from adverse fetal and infant exposures to growth adaptations and respiratory health outcomes have been studied, including fetal and early infant growth patterns, maternal smoking and diet, children’s diet, respiratory tract infections and acetaminophen use, and genetic susceptibility. Still, the specific adverse exposures in fetal and early postnatal life leading to respiratory disease in adult life are not yet fully understood. Current studies suggest that both environmental and genetic factors in various periods of life, and their epigenetic mechanisms may underlie the complex associations of low birth weight with respiratory disease in later life. New well-designed epidemiological studies are needed to identify the specific underlying mechanisms. This review is focused on specific adverse fetal and infant growth patterns and exposures, genetic susceptibility, possible respiratory adaptations and perspectives for new studies

Economic Evaluation of a Bayesian Model to Predict Late-Phase Success of New Chemical Entities

AbstractObjectiveTo evaluate the economic impact of a Bayesian network model designed to predict clinical success of a new chemical entity (NCE) based on pre-phase III data.MethodsWe trained our Bayesian network model on publicly accessible data on 503 NCEs, stratified by therapeutic class. We evaluated the sensitivity, specificity and accuracy of our model on an independent data set of 18 NCE-indication pairs, using prior probability data for the antineoplastic NCEs within the training set. We performed Monte Carlo simulations to evaluate the economic performance of our model relative to reported pharmaceutical industry performance, taking into account reported capitalized phase costs, cumulative revenues for a postapproval period of 7 years, and the range of possible false negative and true negative rates for terminated NCEs within the pharmaceutical industry.ResultsOur model predicted outcomes on the independent validation set of oncology agents with 78% accuracy (80%sensitivity and 76% specificity). In comparison with the pharmaceutical industry's reported success rates, on average our model significantly reduced capitalized expenditures from $727 million/successful NCE to$444 million/successful NCE (P < 0.001), and significantly improved revenues from $347 million/phase III trial to$507 million/phase III trial (P < 0.001) during the first 7 years post launch. These results indicate that our model identified successful NCEs more efficiently than currently reported pharmaceutical industry performances.ConclusionAccurate prediction of NCE outcomes is computationally feasible, significantly increasing the proportion of successful NCEs, and likely eliminating ineffective and unsafe NCEs