An overview of the safety pharmacology society strategic plan

Safety Pharmacology studies are conducted to characterize the confidence by which biologically active new chemical entities (NCE) may be anticipated as safe. Non-clinical safety pharmacology studies aim to detect and characterize potentially undesirable pharmacodynamic activities using an array of in silico, in vitro and in vivo animal models. While a broad spectrum of methodological innovation and advancement of the science occurs within the Safety Pharmacology Society, the society also focuses on partnerships with health authorities and technology providers and facilitates interaction with organizations of common interest such as pharmacology, physiology, neuroscience, cardiology and toxicology. Education remains a primary emphasis for the society through content derived from regional and annual meetings, webinars and publication of its works it seeks to inform the general scientific and regulatory community. In considering the future of safety pharmacology the society has developed a strategy to successfully navigate forward and not be mired in stagnation of the discipline. Strategy can be defined in numerous ways but generally involves establishing and setting goals, determining what actions are needed to achieve those goals, and mobilizing resources within the society to accomplish the actions. The discipline remains in rapid evolution and its coverage is certain to expand to provide better guidance for more systems in the next few years. This overview from the Safety Pharmacology Society will outline the strategic plan from 2016 to 2018 and beyond and provide insight into the future of the discipline which builds upon a previous strategic plan established in 2009

The relationship between patient data and pooled clinical management decisions

A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. Ina previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P <0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics with the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.G. L. Ludbrook, E. J. O'loughlin, C. Grant, T B. Corcora