Cryogenic electron microscopy (cryo-EM) is a characterization technique of great importance to pharmaceutical and biotech R&D teams. It flash freezes biomolecules that enables near-atomic resolution. Using advanced software tools, highly detailed 3-D representations of complex large molecules can be examined without the need to grow pure crystals.
To learn more about how lab managers can make good decisions about cryo-EM technology, we talked with two experts from Thermo Fisher Scientific—Melanie Adams- Cioaba, senior director and general manager, pharma, and Pablo Castro Hartmann, global manager, scientific operations.
Q: Where does cryo-EM deliver the most value in today’s drug discovery pipelines? How should pharma labs decide which programs are best suited for it versus other structural biology approaches?
A: Cryo-EM delivers the most value when and where teams need structural insights, which is predominantly in the earliest stages of discovery. In practice, pharmaceutical companies are using cryo-EM techniques to fundamentally understand the biology of drug targets to assess how early therapeutic molecules may go on to impact the disease in question. Historically, pharma companies have applied cryo-EM techniques to support small-molecule drug discovery, but there has been a dramatic expansion into biotherapeutics, which includes antibodies and vaccines, and the rational design and engineering of cell and gene therapies in recent years.
This expansion of the types of targets and molecules that scientists are tackling is incredibly exciting and offers a significant opportunity for structural biology to add value. Cryo-EM can handle challenging sample types, which means it’s well positioned to not only expand into new modalities but also migrate downstream into development and preclinical applications.
Q: How does cryo-EM help pharmaceutical R&D labs stay competitive in the drug discovery and development landscape?
A: It helps pharma R&D labs tackle the most challenging and often, most interesting, drug targets. This enables the development of novel, innovative therapies, which isn’t a space where everyone plays. Companies that stick with more traditional methods of discovery are going to be limited in what they can do when it comes to types of diseases they can address, targets they can investigate, and drugs that they can design.
There are additional competitive advantages for organizations that bring cryo-EM in-house. With in-house technology, companies also gain the ability to build a repository of data that can be used and shared across workflows from protein production to drug design.
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Q: What are the most important upfront considerations for pharma labs evaluating cryo-EM adoption?
A: There are several things pharma labs should consider ahead of cryo-EM adoption. First and foremost, labs will need clarity on where cryo-EM can materially change decision-making. The strongest return on investment (ROI) is when cryo-EM can compress the cycle time from structure to design to test on druggable targets that might otherwise stall. This is especially true for membrane proteins, large protein complexes, and targets with multiple conformational states that have historically challenged drug development pipelines. It becomes a practical question for leadership: will routine access to high-resolution cryo-EM data improve confidence earlier in discovery and development and, thus, reduce late-stage pivots or redundancies?
From there, lab leaders should evaluate their operating model and consider workflow integration. Pragmatically, this means that the in-house adoption versus external access decision should come down to volume. Labs need to quantify the amount of work that needs to be supported by cryo-EM workflows. Importantly, labs should also define time and delivery expectations upfront by asking how quickly the team can generate structures and translate them into usable outputs for internal stakeholders. Cryo-EM delivers the most value when it fits into the program’s cadence.
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Finally, there are practical realities of space, facility permanence, and cost to consider. It can take time to build out and fully utilize the investment, which becomes a cost consideration. However, cryo-EM is becoming more accessible with microscopes that have smaller footprints and shorter installation times, plus a growing network of centers that provide flexible, external access to cryo-EM. This can help support earlier investment in this technology while teams build demand, capability, and the operating model that makes cryo-EM a durable part of the pipeline.
Q: How has cryo-EM changed the speed and confidence of structure-based drug design?
A: Cryo-EM has made high-resolution structural insights available for targets that have historically slowed programs down or been intractable. When structure-based methods are at the core of discovery, cycle times and associated costs of getting molecules from concept to clinic can drop meaningfully. In fact, structure-based drugs have more than twice the rate of clinical success and a 50 percent cost and time savings from target selection to investigational new drug (IND) filing when compared to traditional drug discovery methods.
Confidence has increased just as dramatically because cryo-EM enables teams to see precisely how molecules bind—often at near-atomic detail—and to visualize multiple functional states rather than a single static snapshot. In short, cryo-EM has helped shift structural biology from an occasional, confirmatory step into a reliable tool for working with complex.
Q: What organizational or workflow changes have you seen enable successful cryo-EM adoption in pharma labs?
A: Successful adoption tends to come down to upstream and downstream integration. In fact, the secret to running programs at scale and seeing maximum success is proximity between the structural biology platforms and tightly aligned project teams. When pharma labs can treat the protein as a dynamic entity and intentionally iterate how it’s produced, handled, and stabilized in discovery, it can dramatically improve throughput and reliability of downstream structure generation. This synergy enables labs to apply data in context regardless of where they are in the workflow. Structure becomes a decision tool inside a program, rather than a standalone deliverable.
Q: What capabilities should organizations prioritize building internally, and where does it make sense to rely on external expertise?
A: Organizations should prioritize building end-to-end operational capability where cryo-EM is a high-dependency part of the portfolio, such as in large pharma companies and high-throughput biotechs running hundreds of structures per year across multiple programs. In these instances, onsite expertise, standardized protocols, and well-prepared samples are essential.
A hybrid model often works well in practice. Companies can keep their core program internal while using external labs, research organizations, or consortia selectively for surge capacity and specialized workflows. For small biotechs, this externalization can be very beneficial, especially if they only need a handful of structures per year.
Q: How do you see cryo-EM evolving as demand continues to rise to bring more reliable drugs to market faster?
A: As demand rises, cryo-EM is evolving in tandem with more automation, higher throughput, better resolution, and greater user-friendliness across the full workflow. Technology providers have a clear vision to make cryo-EM more accessible, and that includes reducing the number of highly manual, specialized steps that have historically created bottlenecks. It’s a meaningful evolution that unlocks “structure on demand,” where teams can see, with confidence, what a protein looks like as close to real time as possible.
Finally, cryo-EM is increasingly expected to fit into a broader AI-powered drug discovery ecosystem, where rapid structural feedback strengthens iterative design cycles across both small molecules and biotherapeutics. By lowering technical friction and expanding access to high-resolution insight into complex, dynamic targets, cryo-EM helps teams reduce uncertainty earlier—so promising programs can move forward faster and more efficiently, ultimately supporting the industry’s push to bring more reliable drugs to patients sooner.
