Discover how automation technologies are transforming pharmaceutical research, accelerating drug discovery, and revolutionizing medical science through robotics and artificial intelligence.
Picture a laboratory where experiments run 24 hours a day, seven days a week, with robotic arms precisely handling microscopic samples and artificial intelligence analyzing results in real-time. This isn't science fiction—it's the new reality of pharmaceutical research.
Automating repetitive laboratory tasks with enhanced accuracy and reduced contamination risks4
| Category | 2023/2025 Value | 2034/2035 Projection | CAGR | Notes |
|---|---|---|---|---|
| Lab Automation Market | - | $4,936 million (by 2035) | 7.3% (2025-2035) | Driven by technological advancements1 |
| AI in Pharma Market | $1.94 billion (2025) | $16.49 billion | 27% (2025-2034) | Includes all AI applications2 |
| AI in Drug Discovery | $1.5 billion | ~$13 billion (by 2032) | - | Specific to discovery applications2 |
While robotics alone has transformed laboratory workflows, the true revolution begins when these automated systems are enhanced with artificial intelligence. AI acts as the brain that directs robotic hands, creating an integrated system that's far more powerful than the sum of its parts.
AI algorithms scan scientific literature and patient data to identify new proteins implicated in diseases7
AI explores chemical space to generate top hits from billions of potential molecules7
AI cuts patient recruitment times and designs better trials using real-world data2
A collaboration between BD and Hamilton Company demonstrates how automation transforms genomic research through standardized library preparation processes.
Precisely handle microscopic volumes of liquids, such as the Hamilton Microlab NGS STAR platform3
Manipulate samples, containers, and instruments like Yaskawa Motoman systems for specimen processing8
Interpret complex data and identify patterns, such as Relay Therapeutics' platform for understanding protein motion7
Work safely alongside human researchers in shared workspaces, like HC Series cobots8
"Automated labs are built on the principles of digitisation and automation, combining these elements to enhance efficiency, repeatability and reliability. Automated labs use advanced systems, such as robotics, AI-driven decision-making and data processing tools, to streamline experimental procedures and data collection"
Systems that understand and explain reasoning behind tasks9
Systems that design and execute experiments autonomously
Making technology accessible to smaller institutions
Laboratory robotics and AI are not replacing scientists—they're augmenting human capabilities. These technologies handle repetitive tasks, freeing researchers to focus on creative problem-solving and strategic decision-making.
"These tools have expedited the process of drug discovery operations significantly. They allow us to explore chemical spaces that we could not explore earlier"