Lab automation strong despite global challenges

The world of drug discovery definitely kept us on our toes last year. Uncertainty in the market, not helped by the challenges created by changes in US drug pricing and tariffs, led to spending dips and nervousness throughout the sector.  

SLAS2026 is a key point in the drug discovery calendar, showcasing the best of global lab automation technology and concepts under one roof. Whatever else may be taking place in the wider pharmaceutical, biopharmaceutical and biotech sectors, we know that the technology designed to service those markets continues to advance.
 

Strong growth predicted

According to Mordor Intelligence: “The lab automation market in the drug discovery sector is estimated to grow from $5.90 billion in 2026 to reach $7.27 billion by 2031.” It adds that “the growth path reflects the steady integration of artificial intelligence into laboratory workflows, the mainstream adoption of acoustic liquid handling, and increasing investments that alleviate talent shortages across pharmaceutical research hubs.” 

While AI often hits the headlines, lab automation does of course, include a variety of technologies such as high throughput screening, robotics, AI, machine learning and automated liquid handling. The latter, according to Mordor Intelligence, has: “become a key component of modern screening lines. This development is driven by compound library developers increasingly relying on high-throughput screening to achieve faster cycle times. Pharmaceutical companies continue to represent the largest segment, accounting for the highest demand, while contract research organisations are becoming increasingly significant, reflecting a growing trend toward outsourcing and services focused on automation.”  

From new technology to collaborations, plus the ever-present interest in AI, the lab automation sector is vibrant and exciting. 

Genomics and AI

Certain areas of drug discovery have also shown a keen interest in lab automation. Genomics is one example  – AI in particular.  Particularly noteworthy is a new AI tool by Genomics England  –Savana – which uses long-read sequencing data to find specific changes within a person’s DNA linked to cancer. The tool can quickly and accurately analyse genetic information from patient samples to help diagnose cancer and inform treatment approaches. AlphaGenome is an AI tool for genomics developed by Google DeepMind to decipher the “dark matter” of DNA, focusing on non-coding regions and their impact on gene expression and regulation. And DRAGEN is an AI-powered platform by Nvidia and Illumina, which uses genomics and AI technologies to analyse and interpret multiomic data in drug discovery, clinical research, and human health.

Product launches

New offerings to the market continue such as Merck’s AAW Automated Assay Workstation which automates routine laboratory experiments that were previously performed manually – the idea being that it reduces hands-on time and ensures consistency in results across diverse experimental settings. Of course, this is the attraction to users. 

“Our customers are increasingly seeking tools that improve efficiency and deliver reliable and reproducible results,” said Anand Nambiar, Head of Science & Lab Solutions for the Life Science business sector of Merck. “By automating routine tasks, researchers can focus on solving complex scientific challenges and accelerate discovery.”

Collaboration

Interesting partnerships have included Insilico Medicine, a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, which announced a research collaboration with Eli Lilly where the two parties will combine Insilico’s Pharma.AI platforms with Lilly’s development and disease expertise to jointly discover and advance innovative therapies.

The aim is to use Insilico’s platform and deep drug discovery expertise to generate, design, and optimise candidate compounds against targets. 

Alex Zhavoronkov, PhD, Founder and Co-CEO of Insilico Medicine said: “This expanded collaboration further recognises Insilico’s AI-driven drug discovery capabilities while strengthening our longstanding partnership. By joining forces, we are accelerating the development of transformative therapies to address urgent patient needs worldwide.” 

Again, at the time of writing is the news out of the JP Morgan Healthcare Conference that NVIDIA has expanded its drug discovery platform and partnered with Lilly. NVIDIA has announced a major expansion of NVIDIA BioNeMo, its open development platform for AI-driven biology and drug discovery. 

“Biology and drug discovery are reaching their transformer moments,” says Kimberly Powell, Vice President of Healthcare at NVIDIA. “BioNeMo turns experimental data into usable intelligence for AI, so every experiment informs the next. This creates a continuous learning cycle that speeds up discovery and helps researchers build new frontier models to tackle some of biology’s toughest challenges.” 

Further developments also saw the company announcing a new collaboration with Lilly to launch a co-innovation lab focused on tackling some of the most enduring challenges in drug discovery. The companies will also explore opportunities to apply accelerated computing and advanced AI across Lilly’s business, from manufacturing to commercial operations. The new initiative intends to harness investments in next-generation NVIDIA architectures, including Vera Rubin — representing a total investment of up to $1 billion over five years. 

“We see this as a catalyst for the capabilities that will define the next era of drug discovery,” said Diogo Rau, Executive Vice President and Chief Information and Digital Officer at Lilly. “By working with NVIDIA, we’re uniting massive compute, specialised talent and the ability to shape data at immense scale.” 

In another deal announced at the conference, NVIDIA revealed it will partner with Thermo Fisher to make scientific instruments intelligent and laboratories increasingly autonomous. By integrating NVIDIA’s full-stack AI computing with Thermo Fisher’s instrumentation, the collaboration aims to transform scientific research labs into scalable, automated data factories. 

Despite global volatility in the markets, the advancement of technology for the drug discovery and development sector is strong.

By Lu Rahman in Lab automation: How technology can accelerate drug discovery – Read the eBook here

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