Rewiring biopharma R&D with AI: from linear gates to learning loops

By McKinsey & Company · 2026.

This McKinsey article, written by the global leaders of its Life Sciences practice, Adam Sabow and Reinout Goedvolk, proposes using AI to rethink the research and development (R&D) model in the biopharmaceutical industry.

The core idea is to replace today's workflow, described as sequential and fragmented and organized around linear 'gates' that follow one after another, with a model built on connected, AI-powered decision loops. According to McKinsey, this new approach would reduce the uncertainty inherent in drug development, compress project timelines and ultimately speed up the arrival of new medicines on the market.

The email says the proposal involves organizing R&D around five key decision points. However, the body of the message does not say what those five points are or go into the specific methodology. Readers are referred to the linked article on McKinsey's website for the full discussion.

Under related content ('Also Consider'), the email points to two more McKinsey pieces. One covers how to reimagine life sciences companies with agentic AI ('Reimagining life science enterprises with agentic AI'). The other covers the evolving formula for discovery and development in biopharma R&D ('Biopharma R&D: The evolving formula for discovery and development'). This ties the topic to broader trends in autonomous agents applied to highly regulated sectors such as pharmaceuticals.

More broadly, McKinsey content of this kind is usually part of a larger series of publications on digital transformation and AI in specific sectors, in this case life sciences. The aim is to position the firm as a strategic thought leader where AI and biopharma meet.