How genomics is becoming a routine tool across research and healthcare

A decade ago, genomics was still regarded by many as an emerging technology with enormous potential but significant practical limitations. Today, that picture looks very different. Sequencing has become a routine part of workflows across research, healthcare, agriculture, and biotechnology, helping scientists answer increasingly complex questions about disease, biological function, and genetic diversity. For Leandro Neves, Senior Global Director of R&D Genomics at LGC, one of the most significant changes has been the shift in how people view genomics itself.

Rather than being seen as a specialist capability that sits at the edges of research programs, genomics is now becoming an expected part of the toolkit. Researchers and organizations are no longer questioning whether genomic information can provide value; instead, they are looking at how to integrate it more effectively into their workflows and decision-making processes. The focus has moved from proving the technology works to maximizing its impact.

"Sequencing is really becoming a mainstream technology," says Neves. "It's being adopted more and more, and people are taking for granted, in a good way, that genomics is there to support their programs."

Genomics expands beyond DNA

That growing adoption of sequencing technologies is being accompanied by an expansion in the scope of genomic analysis. Modern researchers are not looking at DNA sequence data in isolation. Increasingly, genomic information is being combined with transcriptomic, proteomic, and other biological data sets to build a more complete picture of biological systems.

"We are seeing some trends around incorporating large datasets," says Neves. "Whether that's analyzing DNA, the transcriptome, the proteome, or other datasets, they're collectively contributing to what we call genomic analysis."

This integrated approach is helping researchers better understand disease mechanisms, identify therapeutic targets, and uncover biological patterns that would be difficult to detect using a single data type alone.

Cost and accessibility for genomics remain key barriers

While genomics has undoubtedly become more accessible than it was in the past, significant challenges remain. Cost continues to be a major consideration, particularly for laboratories operating outside well-established genomic hubs. Although sequencing prices have fallen dramatically over the years, access to high-throughput instruments and the infrastructure needed to support them is still unevenly distributed. As a result, many organizations continue to rely on centralized facilities that can achieve the economies of scale required to make genomic analysis cost-effective.

"As much as prices have reduced, they're still reasonably expensive," he says. "It can be difficult to have decentralized genomic centers, so analysis often needs to be consolidated in hubs."

Neves believes that improving access will be a critical next step for the industry, particularly in regions where economic barriers continue to limit adoption. The long-term goal is not simply to make sequencing faster or more powerful, but to make it available to more laboratories, researchers, and communities around the world.

"Working more on democratizing genomics, especially where costs are still a major criterion, needs to be thought about for broader adoption," he explains.

How standardization in genomics is driving reliability

As genomics moves beyond research settings and into more industrialized and regulated environments, laboratories are also placing greater emphasis on consistency, reproducibility, and quality. This has driven major advances in sample preparation, assay development, and workflow automation. Library preparation workflows that once required extensive manual handling and optimization are now faster, more streamlined, and capable of delivering increasingly consistent results.

According to Neves, these improvements are helping genomics transition from a research-driven discipline into an operational technology that laboratories can depend on every day. Automation is playing a particularly important role, reducing variability between users and helping laboratories process larger numbers of samples while maintaining confidence in their results.

"The key is standardization," he says. "Processes are becoming more controlled and automated. It's becoming more of an industrial application of genomics rather than what used to be a research exercise where every lab would tweak things a little differently."

Using AI to uncover hidden patterns in genomic data

The growing maturity of genomics is also reflected in the evolution of bioinformatics and data analysis. Sequencing technologies are generating vast amounts of information, creating both opportunities and challenges for researchers. While established bioinformatics pipelines have become highly effective at answering many of the core questions researchers face, there is increasing interest in using data science and artificial intelligence to uncover insights that might otherwise remain hidden.

"Bioinformatics is pretty consolidated today," he says. "We have strong tools and pipelines that the community uses to answer major questions."

Neves sees artificial intelligence (AI) as a natural next step in the industry's analytical evolution. Rather than replacing existing bioinformatics approaches, these tools are helping researchers explore increasingly complex data sets and identify patterns that traditional methods may struggle to detect. Although the field is still developing, AI is already becoming an important area of exploration across the genomics community.

"We're trying to go a layer deeper," he says. "To find patterns that current tools or algorithms were not sophisticated enough to identify and answer questions that were previously hidden in the data."

Why standards and controls matter in clinical genomics

As genomic technologies become more deeply embedded within clinical and regulated environments, ensuring the accuracy and reliability of results becomes increasingly important. In healthcare settings, genomic data can influence patient management decisions, making quality assurance, standards, and controls essential components of the workflow. Robust reference materials and controls allow laboratories to validate assays, monitor performance over time, and understand the limitations of their methods.

This is an area where LGC, through its SeraCare brand, plays a key role by providing standards and controls used throughout the genomics workflow. For Neves, the importance of these tools will only continue to grow as genomic testing becomes more widespread.

"It's crucial that we have control over the process and understand the limits of the technology," he explains. "You can only do that when you have standards and controls to calibrate your tests and make sure they continue working to the specifications you've designed."

What will the sequencing laboratory of the future look like?

Looking ahead, Neves believes that future sequencing laboratories will be defined by three interconnected themes: automation, integration, and control. Advances in miniaturization are expected to reduce reagent consumption and sample requirements, enabling laboratories to operate more efficiently while accelerating turnaround times. At the same time, laboratories will increasingly connect instruments, sample preparation systems, data analysis platforms, and laboratory information management systems into seamless end-to-end workflows.

"Integration is really the keyword," he says.

The goal is to create environments where samples move efficiently from collection through analysis and interpretation, supported by automated processes that minimize human error and maximize reproducibility. This level of integration will be particularly important as genomic technologies continue to expand into applications such as cancer research and minimal residual disease monitoring, where speed, reliability, and scalability are essential.

A future powered by broader adoption and genomics integration

Ultimately, however, what excites Neves most is not a specific technology or breakthrough, but the broader impact genomics is having across multiple sectors. From supporting crop improvement and animal breeding programs to advancing rare disease research and drug discovery, genomics is increasingly being used to address real-world challenges that affect both industry and society.

"We're able to use these tools for more questions, more problems, and more people," he says. "Whether that's through better medicine, better food production, or understanding the natural diversity that exists in our world."

To support this future, LGC has recently brought together its clinical diagnostics and genomics teams, reflecting a broader industry trend toward integrated solutions that span the entire workflow. By combining expertise across these areas, the company aims to help customers navigate an increasingly complex genomics landscape while continuing to develop technologies that make genomic analysis more accessible, reliable, and impactful.

As genomics becomes ever more embedded in routine laboratory practice, the conversation is no longer about whether sequencing will transform science and healthcare; it already has. The challenge now is ensuring that the benefits of these technologies can be delivered consistently, at scale, and to the widest possible community of researchers, clinicians, and innovators.

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