---
id: "concept-self-driving-labs"
type: "concept"
source_timestamps: ["§ 2. Integrate emerging technologies into the drug-development process."]
tags: ["artificial-intelligence", "robotics", "automation"]
related: ["concept-human-in-the-loop-research", "entity-purdue-care", "action-integrate-sdls", "entity-mount-sinai-ai", "claim-human-in-the-loop-essential"]
definition: "Robotic systems integrated with AI that autonomously and continuously conduct scientific experiments, capturing real-time data to accelerate drug development."
sources: ["tail2"]
sourceVaultSlug: "hbr-seg-tail2"
originDay: 2
articleStem: "hbr-tail-131-medical-drug-discovery"
sourceUrl: "https://hbr.org/2026/04/u-s-medical-centers-need-a-new-model-for-drug-discovery-and-development"
sourceTitle: "U.S. Medical Centers Need a New Model for Drug Discovery and Development"
---
# Self-Driving Labs (SDLs)

A **self-driving lab (SDL)** combines **artificial intelligence with robotic automation** to autonomously run a **continuous (24/7) series of AI-selected experiments**. By automating manual workflows, SDLs **capture real-time data with significantly reduced error rates**, giving AMCs a platform to **increase research productivity and reduce operational costs**.

Crucially, SDLs are **not entirely autonomous**: they require **human oversight** for complex problem-solving and quality control — see [[concept-human-in-the-loop-research]] and [[claim-human-in-the-loop-essential]]. Deploying SDLs is the action item [[action-integrate-sdls]] and constitutes Pillar 2 of the [[framework-amc-innovation-acceleration]].

Named AMC examples: Purdue's [[entity-purdue-care]] (an SDL initiative pairing AI with robotic automation) and Mount Sinai's [[entity-mount-sinai-ai]] (generative AI + medicinal chemistry).

**Enrichment context:** current academic literature frames AI as most effective when combined with high-quality experimental systems and human oversight, rather than as a fully autonomous replacement for scientists.