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 rethinking the research and development (R&D) model in the biopharmaceutical industry through AI.

The central idea is to replace the current workflow —described as sequential and fragmented, organized around linear 'gates' that follow one after another— with a model based on connected decision loops powered by AI. According to McKinsey, this new approach would reduce the uncertainty inherent in the drug development process, compress project timelines and, ultimately, accelerate the arrival of new medicines on the market.

The email indicates that the proposal consists of organizing R&D around five key decision points, although the body of the message does not specify what those five points are, nor does it delve into the concrete methodology; for the full discussion it refers readers to the article linked on McKinsey's site.

As related content ('Also Consider'), the email points to two additional McKinsey pieces: one on reimagining life science enterprises with agentic AI ('Reimagining life science enterprises with agentic AI'), and another on the evolving formula for discovery and development in biopharma R&D ('Biopharma R&D: The evolving formula for discovery and development'). This connects the topic with broader trends in autonomous agents applied to highly regulated sectors such as pharmaceuticals.

In general, this type of McKinsey content tends to form part of a broader series of publications on digital transformation and AI in specific sectors, in this case life sciences, with the aim of positioning the consultancy as a strategic thought leader at the intersection of AI and biopharma.