drug discovery

AI Identifies the Target. Someone Still Has to Validate It.

Posted on by Elise Johnson

Did you see the movie where Spider-Man files his taxes? Or the one where Wonder Woman sits on hold with her insurance company while her pasta water boils over? Or where Captain America finds blight on his tomato plants and drives to the county extension office where he spends fifty minutes with a seventy-four-year-old master gardener named Marlys then leaves with a handwritten note covering his soil composition, his watering schedule, and what Marlys calls “the mulching situation”?

No. Because the ordinary day-to-day doesn’t stand a chance next to the saving of the world.

We spend most of our lives in the ordinary. Not because we’re failing to reach the extraordinary, but because the ordinary is what holds everything together while we get there. It’s not the backdrop but the foundation. It’s what the story depends on, whether or not it gets any credit.

Drug Discovery Has a Storytelling Problem

Drug discovery runs almost entirely on ordinary days, punctuated by the moments that make the news: a new target gets identified, a compound shows promise, a trial produces results. Those moments get the headlines, press releases and keynote slots. What doesn’t get the same attention is the years of work behind those moments: the assays, the failed experiments, the redesigns, the slow accumulation of evidence that either holds up or doesn’t. That work has always been the majority of drug discovery.

Some of the most important work in drug discovery ends in a result nobody publishes, but a dead end isn’t a failure of the program. It’s the program working. The researcher who rules something out has learned something true. That knowledge travels forward even when it doesn’t make the headline because it can redirect the next hypothesis, narrow the next experiment or just quietly move things along. That work moves research forward without anyone announcing it.

The Shiniest Thing in the Room

Artificial intelligence is drug discovery’s latest extraordinary announcement, and the fanfare is legitimate. Most of the druggable proteome has never been touched. Of approximately 4,500 human proteins considered druggable, all approved drugs to date work through only 716 distinct targets. Drug hunters knew there was more biology to address but lacked a way to find and prioritize candidates at scale. AI is changing that. By scanning genetic evidence, biological networks and scientific literature at a scale no human team can match, AI is surfacing targets that were previously out of reach and ranking them by the strength of the evidence behind them.

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Another Crack in the RAS Code: The Measurement Story Behind Daraxonrasib

Posted on by Elise Johnson

In late May 2026, a clinical trial result landed in the New England Journal of Medicine and immediately rewrote what oncologists believed was possible for patients with metastatic pancreatic cancer. Before the paper was published, people in the field were already calling it “transformative.” The data, when it came, agreed. In a disease where most second-line treatments offer months at best, a drug called daraxonrasib nearly doubled how long patients lived compared to those who received chemotherapy.¹

RAS proteins, which regulate cell growth and are mutated in more than a third of all human cancers,² had spent forty years resisting every attempt to drug them. The protein’s surface offered no obvious foothold for a small molecule. Once the word “undruggable” attached itself to the RAS protein family, most of the field moved on to more cooperative targets.

Some researchers stayed. And Promega stayed committed to the question that never goes away: does this new compound work inside a living cell? When the next chapter of the RAS story arrived, the tools were ready. Daraxonrasib is one culmination of a much longer story, one that matters for every researcher pursuing a target the field has written off.

The First Answer

To understand what daraxonrasib represents, it helps to see how an earlier chapter of the RAS story faced the same fundamental measurement challenge.

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Screening Disease-Relevant Biology: How the Endo-GeneScreen Platform Uses Endogenous Protein Detection to Drive Drug Discovery 

Posted on by Amy Landreman

Drug discovery has long grappled with a fundamental tension in high-throughput screening: the more biologically relevant your model, the harder it is to scale. Phenotypic assays in primary disease-relevant cells offer rich biological context, but capturing meaningful, target-specific readouts from these complex systems at screening scale has remained a significant challenge.  In contrast, simpler, more scalable systems are easier to deploy but sacrifice the biological fidelity that makes hits meaningful. A recent study by Samowitz et al. in Nature Communications describes an interesting approach to resolve this tension, the Endo-GeneScreen (EGS) platform. A high-throughput screening system designed to enable scalable detection of endogenous protein levels within disease-modeling cellular contexts. 

A Well-Chosen Proof of Concept 

The authors selected Syngap1 as their proof-of-concept target to develop and demonstrate this approach. De novo mutations in this gene that lead to haploinsufficiency are among the most common genetic causes of sporadic neurodevelopmental disorders, including intellectual disability, autism, and epilepsy. Small molecules that boost SynGAP protein levels back toward wildtype would address the root cause of these disorders rather than managing downstream symptoms. Importantly, Syngap1 function is closely tied to cortical excitatory neurons. Well-validated in vitro and in vivo models for these neurons already exist, creating an integrated system for both discovering new compounds and validating them in the same biological context. That continuity is an important step toward improving the translational relevance of lead molecules coming out of the screen. 

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Your Media Choice Might Be Designing Your T-Cell Fate

Posted on by Simon Moe

Why Metabolism Matters in T-Cell Expansion

Adoptive T-cell therapies rely on generating metabolically fit, functional cells during ex vivo expansion—but this process often pushes T cells toward highly glycolytic, terminally differentiated states that limit their persistence and therapeutic potential. These metabolic programs begin shifting within hours of activation, therefore understanding early metabolic remodeling is essential for designing culture conditions that support durable, cytotoxic, and memory-enriched T-cell populations.

Researchers at Promega set out to address this challenge by systematically mapping how media composition and activation strength shape T-cell metabolism during the first 72 hours after stimulation. Using a suite of bioluminescent assays, they profiled intracellular energy cofactors, redox balance, and extracellular metabolites across several conditions. This approach revealed distinct, media-driven metabolic states that not only emerged early but also predicted downstream expansion, proliferation, and cytotoxic function.

Their work demonstrates how integrating metabolic profiling into in vitro expansion workflows can provide a more informed framework for optimizing T-cell manufacturing strategies.

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CRISPR/Cas9 Endogenous Tagging in Drug Discovery

Posted on by Teresa Simon

Limitations of Traditional Protein Study Methods 

Studying proteins in their native biological context has long been a major challenge in molecular biology. Traditional methods, although widely used, often distort the actual cellular environment and limit functional interpretation. Techniques like antibody-based detection or plasmid-driven overexpression can introduce artifacts and do not allow real-time analysis in living cells. 

In this context, the need for tools that enable the observation of proteins as they naturally occur, under physiological conditions, and within live cells is becoming increasingly evident in molecular biology. 

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Accelerating Drug Discovery at Grove Biopharma with MyGlo® and ProNect®

Posted on by Promega

At Grove Biopharma, the R&D team is advancing a rational design approach to drug discovery. Their Bionic Biologics™ Platform assembles custom-engineered peptides to target intracellular protein-protein interactions into stable, potent, cell permeable therapeutics. By combining the precision of biologics with the efficiency of synthesizing small molecules, Grove accelerates lead generation and optimization.

Grove’s technology enables targeting key proteins involved in cancer and neurodegenerative diseases for which effective therapeutics have historically been difficult to develop. Their candidate molecules focus on important targets such as the Androgen Receptor splice variant, SHOC2 within the RAS/RAF pathway, the MYC-regulator WDR5, a Tau isoform relevant to Alzheimer’s Disease, and the Keap1-Nrf2 interaction associated with neurodegeneration. These programs have made significant progress and now represent some of the most advanced agents in their pipeline.

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CRISPR/Cas9 Knock-In Tagging: Simplifying the Study of Endogenous Biology

Posted on by Ken Doyle

Understanding the expression, function and dynamics of proteins in their native environment is a fundamental goal that’s common to diverse aspects of molecular and cell biology. To study a protein, it must first be labeled—either directly or indirectly—with a “tag” that allows specific and sensitive detection.

Using a labeled antibody to the protein of interest is a common method to study native proteins. However, antibody-based assays, such as ELISAs and Western blots, are not suitable for use in live cells. These techniques are also limited by throughput and sensitivity. Further, suitable antibodies may not be available for the target protein of interest.

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Targeted Protein Degradation: How Chemoproteomics and Induced Proximity Are Shaping Drug Discovery

Posted on by Amy Landreman

Earlier this fall, more than 90 researchers from academia and industry gathered at the Promega Madison campus for the 4th TPD & Induced Proximity Symposium. The event focused on the rapidly advancing field of targeted protein degradation (TPD) and the broader concept of induced proximity—therapeutic strategies that bring two or more proteins into proximity to trigger a specific biological effect. 

This 4th year reflected of the symposium a maturing and diversifying field with chemoproteomics and proteomescale mapping redefining what it means to be “druggable,” while AI and high throughput biology are connecting molecular design to cellular function. Yet the mission remains unchanged—using molecular approaches that leverage the cellular machinery to make progress against targets once deemed “undruggable.” 

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Cellular Selectivity Profiling: Unveiling Novel Interactions and More Accurate Compound Specificity

Posted on by Promega

This blog was written by guest contributor Tian Yang, Associate Product Manager, Promega, in collaboration with Kristin Huwiler, Manager, Small Molecule Drug Discovery, Promega.

Determining the selectivity of a compound is critical during chemical probe or drug development. In the case of chemical probes, having a clearly defined mechanism of action and specific on-target activity are needed for a chemical probe to be useful in delineating the function of a biological target of interest in cells. Similarly, optimizing a drug candidate for on-target potency and reducing off-target interactions is important in the drug development process (1,2). A thorough understanding of the selectivity profile of a drug can facilitate drug repurposing, by enabling approved therapeutics to be applied to new indications (3). Interestingly, small molecule drugs do not necessarily require the same selectivity as a chemical probe, since some drugs may benefit from polypharmacology to achieve their desired clinical outcome.

Selectivity profiling panels based on biochemical methods have commonly been used to assess compound specificity for established target classes in drug discovery and chemical probe development. Biochemical assays are target-specific and often quantitative, enabling direct measurements of compound affinities for targets of interest and facilitate comparison of compound engagement to a panel of targets. As an example, several providers offer kinase selectivity profiling services using different assay formats and kinase panels comprised of 100 to 400 kinases (4). However, just as biochemical target engagement does not always translate to cellular activity, selectivity profiles based on biochemical platforms may not reflect compound selectivity in live cells (5).

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From Tracers to Kinetic Selectivity: Highlights from the Target Engagement in Chemical Biology Symposium

Posted on by Anna Bennett

In April 2024, Promega hosted the “Target Engagement in Chemical Biology Symposium” at the Kornberg Center, a research and development hub on Promega’s campus in Madison, Wisconsin. The goal of the symposium was to gather interdisciplinary researchers interested in the field of small molecule target engagement to foster collaboration through knowledge sharing and innovation. The symposium featured a 1.5-day agenda packed with 23 speakers, 4 workshops, poster sessions and social events. Over 130 attendees gathered to participate in the multifaceted event, with participants from different geographic regions and in different research sectors from academia to government to industry.  

People gather in a large atrium with scientific posters and table displays.
Attendees gather for the poster session in Kornberg Atrium. Photo by Anna Bennett (Promega Corporation)

The symposium highlighted the collective commitment to overcoming the challenges in drug discovery by developing more targeted and efficacious treatments, driven by a shared determination to create innovative solutions that address unmet medical needs. While we cannot share all the exciting research presented at the symposium, we are thrilled to highlight a few talks that exemplify the novel work and collaborative spirit of this research community.  

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