Building a shared team identity with GenAI: a Case Study in breaking down silos across a rare disease marketing team Generative AI can produce an image in seconds. Producing one that genuinely represents a person, earns their recognition and serves a purpose takes considerably longer. This case study describes how a global pharmaceutical company worked …
Not every content decision works as planned. What separates a good campaign from a great one is the willingness to read the data, adjust the approach, and carry those lessons forward. This case study documents how a global pharmaceutical company worked with SciencePOD to design, deliver and evaluate a twelve-month multichannel content campaign aimed at …
The challenge of HCP engagement Pharma teams increasingly recognise the value of digital HCP engagement. However, the practical challenge lies within its execution: producing content at pace whilst meeting medical and legal review requirements. The MLR process is consistently cited as the primary barrier to creating agile content. The pharma company hosted a relatively small …
Challenge To raise awareness of malnutrition in key patient groups. The pharma company needed to target time-pressed HCPs and patient groups while navigating strict regulatory constraints. Although the pharmaceutical company’s objective was clear, they needed an experienced partner to bring their campaign to life, a partner capable of visualising, mapping out, and orchestrating the necessary …
A panel with some of the most actionable advice that Pharma customer engagement managers could have right now. AI won’t do the whole job
Interview with Vivek Mukhatyar, Generative AI Medical Engagement Lead, Pfizer
Interview with Alexandros Athanasiou, Head of Marketing, Innovation and Excellence with Takeda Pharmaceuticals
Loucif Ouyahia, Global Head of Digital Healthcare, Jazz Pharmaceuticals | Managing expectations and countering ‘ChatGPT syndrome’
The Power of polyintelligence: A synergistic symphony of human and artificial intelligence
New tech combining forensic linguistics and machine learning yields surprising insights into what does and doesn’t work in HCP communication