---
id: "action-integrate-sdls"
type: "action-item"
source_timestamps: ["§ 2. Integrate emerging technologies into the drug-development process."]
tags: ["automation", "infrastructure"]
related: ["concept-self-driving-labs", "entity-purdue-care", "entity-mount-sinai-ai", "concept-human-in-the-loop-research"]
action: "Deploy AI-driven robotic automation (SDLs) to run continuous experimental workflows."
outcome: "Increased research productivity, reduced error rates, and lower operational costs."
speakers: ["Anaeze C. Offodile II", "Kushal T. Kadakia", "Yashodhara Dash", "Whitney Snider", "Joseph C. Wu", "Selwyn M. Vickers"]
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"
---
# Integrate Self-Driving Labs (SDLs)

**Action:** Invest in and deploy **Self-Driving Labs (SDLs)** — [[concept-self-driving-labs]] — that combine AI algorithms with robotic automation to run **continuous, 24/7 experimental workflows**, reducing reliance on manual processes and lowering error rates.

**Mechanism / examples:** Purdue's [[entity-purdue-care]] and Mount Sinai's [[entity-mount-sinai-ai]] (Pillar 2 of [[framework-amc-innovation-acceleration]]). Retain **human oversight** per [[concept-human-in-the-loop-research]].

**Outcome:** increased research productivity, reduced error rates, and lower operational costs.