In this webinar, we will discuss the historical perspective on value in Medical Affairs, as well as strategies to measure and demonstrate impact in an evolving pharmaceutical environment. Join us to learn more about how data-driven strategies can help you gain a better understanding of your Medical Affairs activities and provide insights into areas of opportunity
In this white paper, Triducive asks: Where is MA now? How are we progressing? Which areas may need the greatest additional effort/support?
This webinar examines, based on the prevailing pre-launch situation, the strategic focus areas for Medical Affairs teams to consider during launch preparation and discuss approaches to achieve excellence across key activities.
The session focuses on results from first hand experiences in Chat GPT and other Large Language Models (LLMs).
Medical congresses are crucial for keeping up with the latest life science industry standards and best practices – but planning is time-consuming and manual. What’s the alternative for better medical congress planning? Get the complete guide to congress planning.
This case study is useful for anyone working to anticipate market access issues and develop plans for launching new drugs in key markets.
This webinar will discuss how with the vast amount of data available today, medical affairs organizations are tasked with continuously enhancing their ability to gather, analyze and derive insights from various data sources.
In this episode, Ariel Katz, co-Founder and CEO of H1, provides a more linear and streamlined vision for how Medical Affairs can impact patient outcomes — and how to measure the results of our actions.
This webinar serves as guidance for how to overcome barriers to access patients compliantly.
This webinar program will focus on the innovative applications of internal performance management platforms such as the Medical Productivity Index (MPI) and external events, namely the 2022 Medical Affairs Innovation Olympics in pharma that illustrate examples of more continuous, real time feedback on performance, new data science analytics driven analysis of performance, more even distribution of accountability, and increased resources to accelerate learning and development.