Tips and Tools

Sequence to Substance: Making the mRNA Therapeutic

Posted on by Shannon Sindermann

mRNA-based therapeutics are being explored across a range of applications, including vaccines, protein replacement and immunotherapies (2).

Before any formulation decisions enter the picture, teams need confidence in the RNA itself: that it is the right sequence, right properties and the right purity to behave predictably downstream. That is where it helps to separate drug substance from drug product. The drug substance is the active ingredient intended to deliver a pharmacological effect, while drug product is the finished dosage form that contains that ingredient (6).

This post focuses on what happens upstream, making the mRNA drug substance before formulation. In practical terms, that upstream work spans choosing an mRNA construct, producing it by IVT, and then purifying and analyzing the product so it has the desired quality attributes (5).

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The Breakthrough Was There All Along

Posted on by Elise Johnson

If you’ve ever played The New York Times game Connections, you know the feeling. You’re staring at a grid of words, knowing the solution is there, but unable to see how the pieces fit together. All you can do is work with the words in front of you. There are no extra clues, no new information coming. The only option is to shuffle, to look at the same information in a different arrangement until patterns begin to appear.

Nothing about the problem changes. Then something about how you see it does.

In 2014, a third-year medical student named David Fajgenbaum checked himself into the emergency room mid-exam. He felt off. By the time anyone understood why, he was in the ICU with multiple organ failure from a disease so rare it wasn’t taught in medical school: Castleman disease. The only approved drug didn’t work. A priest came to his bedside and read him his last rites. He was 25.

Fajgenbaum survived that relapse, and four more after it. As he recounted in a recent episode of NPR’s Radiolab, he understood that chemotherapy was keeping him alive without curing him, and that waiting for a new drug to be developed (a process that typically takes 10 to 15 years and billions of dollars) wasn’t an option he had. So he did something unusual. He started asking his doctors to save his blood samples, and he ran experiments on himself.

What he found was that a specific signaling pathway in his immune system, mTOR, was in overdrive. When he searched the existing pharmacological literature for something that could block it, he found an answer that had been sitting in pharmacies for 25 years. Sirolimus, a drug approved in 1999 to prevent organ transplant rejection, had never been used for Castleman disease. The biology of his disease hadn’t changed. The drug had always existed. The connection simply hadn’t been made.

He took it. It worked. He has been in remission for over a decade.

The detail worth holding onto isn’t the drug or the disease. It’s the instinct. Fajgenbaum didn’t wait for new knowledge to arrive. He looked differently at what already existed.

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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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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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Insights from 3D Liver Models: Rethinking Fatty Liver Disease with Hormone Correction

Posted on by Simon Moe

Liver disease is a global health challenge, affecting millions each year. The liver has a remarkable ability to regenerate; however, chronic damage arising from obesity, alcohol, or metabolic dysfunction can lead to irreversible failure. At the University of Edinburgh’s Centre for Regenerative Medicine, Professor David Hay’s lab is developing innovative ways to study liver function and disease using a lab-grown mini-organ. In this blog, we highlight how Dr. Hay’s lab is redefining liver disease research through 3D models that reveal how hormones influence metabolic health.

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Exploring How NEAT1 Shapes Granulosa Cell Function

Posted on by Shannon Sindermann
Granulosa Cells

Granulosa cells (GCs), which surround and support developing oocytes, play a critical role in estrogen production, follicle maturation and overall ovarian health (3). Their ability to regulate hormone production and cell survival makes them a central focus in studies of ovarian biology.

A recent study investigated how the long non-coding RNA (lncRNA) NEAT1 regulates GC function and mapped a pathway that links NEAT1 expression to cell proliferation, apoptosis and hormone production (1).

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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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Unlocking the Power of Live-Cell Kinetics in Degrader Development

Posted on by Kelly Grooms

In targeted protein degradation (TPD), timing is everything. Understanding not just whether a degrader works—but how fast, how thoroughly and how sustainably—can dramatically influence early discovery decisions. Dr. Kristin Riching (Promega) dove into the real-time world of degradation kinetics in the webinar: Degradation in Motion: How Live-Cell Kinetics Drive Degrader Optimization, sharing how dynamic data provides a clearer view of degrader performance than traditional endpoint assays.

Whether you’re exploring your first PROTAC or optimizing a molecular glue series, the expertise offered in Dr. Riching’s presentation gives you actionable insights that will help you connect kinetic data to better therapeutic design.

3D visualization of a protein structure within a live-cell environment, highlighting the interaction site relevant to targeted protein degradation, set against a dark cellular background to emphasize kinetic dynamics.
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How The OceanOmics Centre is Using the Maxwell RSC to Scale eDNA Biodiversity Monitoring

Posted on by Promega

This blog is written by guest blogger Ben Rushton, Application Specialist/Territory Manager at Promega Australia.

When you’re monitoring marine biodiversity at scale, every drop of seawater tells a story. At Minderoo OceanOmics Centre at the University of Western Australia, scientists are uncovering that story through environmental DNA (eDNA)—and automation is helping them listen more clearly.

Laura Missen, a Scientific Officer at OceanOmics Centre, shares how automating their DNA extraction workflow with the Maxwell® RSC 48 system has transformed how they gather and interpret data from marine ecosystems.

(Image credit: Giacomo d’Orlando / Ronin_Lab)
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Exploring the Relationship Between IC50 and Kd in Pharmacology

Posted on by Promega

This guest blog post is written by Tian Yang, Associate Product Manager at Promega.

In the realm of chemical probe development and drug discovery, understanding the interactions between drugs/compounds and their targets is crucial. Two frequently used metrics to characterize these interactions are IC50 and Kd, which guide researchers in evaluating the potential of compounds in effecting changes in target function. IC50 offers insights into a compound’s potency by quantifying its ability to inhibit a specific biological activity. Kd provides a measure of the affinity between a ligand and its receptor, reflecting how tightly a compound binds to its target (1). Together, these parameters are instrumental in the early stages of drug development, helping to identify promising candidates by assessing a compounds’s binding characteristics and its observed efficacy.

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