Why High Performers Often Struggle Most During Transformation
Past success remains an asset, but it does not automatically guarantee future relevance.
In pharmaceutical R&D, scientific priorities evolve, new technologies reshape how research is conducted, and AI is changing the capabilities organisations may need. For experienced professionals, the challenge is not simply to acquire new skills, but to recognise how their existing expertise, judgement and experience might need to be applied differently.
At Arete Pharma Coach, I help pharmaceutical professionals connect industry change with individual action, understanding where R&D is heading, identifying where their experience can create future value, and deciding what to do next.
The Enabling Layer: Why Data, Platforms, and Governance Matter More Than Tools
Pharma R&D faces challenges not due to a lack of science, AI, or data, but because it lacks decision-grade systems. Despite significant investments in AI and multimodal platforms, high portfolio attrition persists because one of the bottleneck is the enabling layer. The structural architecture determining whether a scientific signal translates into successful capital allocation. When this layer is overlooked, AI redistributes uncertainty instead of reducing it, necessitating a focus on designing Evidence Continuity and Escalation Integrity to build truly decision-ready systems.