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

By McKinsey & Company · 2026.

This McKinsey article, authored 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, AI-powered decision loops. According to McKinsey, this new approach would reduce the uncertainty inherent in the drug development process, compress project timelines and, ultimately, speed up the arrival of new medicines on the market.

The email states 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 or go into the specific methodology; for the full discussion, it refers readers to the linked article on McKinsey's website.

As related content ('Also Consider'), the email points to two additional McKinsey pieces: one on reimagining life sciences companies 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 ties the topic to broader trends of autonomous agents applied to highly regulated sectors such as pharmaceuticals.

Overall, this kind of McKinsey content typically forms part of a broader series of publications on digital transformation and AI in specific sectors, in this case life sciences, aimed at positioning the consultancy as a strategic thought leader at the intersection of AI and biopharma.