Introducing the Foundations in Medical Affairs Certificate Program, an essential component of the MAPS eCademy Learning Journey, specifically designed to elevate your understanding of critical concepts and practices in Medical Affairs. With courses tailored to a wide range of fields, Ecademy fosters skill development and professional growth in a collaborative digital environment.
This webinar discusses considerations for the appropriate structure, resources, and timing to get Medical Affairs involved early enough in the process to optimize clinical development plans informed by medical customer insights.
This webinar will focus on the role of Medical Affairs to lead patient engagement in clinical development.
This article provides an overview of the new MedTech European regulatory environment and opportunities for the Medical Affairs function to evolve and bring value to the respective organizations.
This podcast series discusses the basics of EUMDR, what this means more globally (FDA, CFDA) and finally – how we can view this as the golden opportunity to elevate the science of our products and communicate a compelling medical value proposition.
Part 2 of this series will discuss statistical analysis in clinical trials including null/alternative hypotheses; statistical assumptions (type I error, significance level, type II error, statistical power); hypothesis testing; Statistics used in RCTs, including type of outcome measures, analysis of time-to-event variables (plotting and interpretation of Kaplan-Meier curves).
Early Access includes a variety of programs by which pharmaceutical companies make investigational therapies available to patients with life-threatening diseases. These patients have either exhausted available treatments or have no approved options. This presentation will review the processes and procedures to consider in the implementation of an Early Access Program and explore the opportunities and challenges posed therein.
Part 1 of this series will: define terminologies in statistics; explain different types of data (quantitative vs. qualitative); describe different ways in presenting summary data (such as proportions, means, medians, range and standard deviation); explain 95% confidence intervals; discuss bivariate analyses and appropriate statistical testing for quantitative and qualitative variables