When you spend hours at the bench or under a microscope, the smallest details in your tools make the biggest difference. The weight of your forceps, the glare from a light, the feel of a pair of scissors after repetitive use. Everything adds up. Choosing the right material isn’t just a matter of preference. It directly affects comfort, accuracy, and long‑term success in the lab.

You've calibrated your pressure settings perfectly, your timing is precise, yet you're still watching expensive reagents leak into the bath solution during microinjection. Sound familiar? This frustrating scenario plays out in labs worldwide, often leading researchers to question their pump settings or injection protocols. But after years of troubleshooting with scientists using WPI's next generation microinjection systems, one critical factor emerges repeatedly: tip geometry.

When it comes to gene modification and transfection research, success often depends on the smallest details. One of the most critical factors in microinjection-based techniques is the geometry of the pipette tip.

Meet the EVOM™ Auto from World Precision Instruments, the breakthrough that’s revolutionizing drug discovery. When it comes to drug discovery, reliable data on barrier function and cell integrity is essential. Transepithelial Electrical Resistance (TEER) measurements have long been the gold standard for assessing barrier function and cell integrity, critical data for your research, but traditional TEER workflows are often slow, error‑prone, and labor‑intensive.

A new study by Altis Biosystems (Durham, NC) using the EVOM™ Auto is undergoing a peer review prior to publication. It addresses the challenge of predicting gastrointestinal toxicities (GITs) in drug development, which are common adverse events in clinical trials. ​ Traditional animal models fail to accurately replicate human GI physiology, leading to late detection of GITs. ​ Researchers Colleen Pike and James Levi (with their team) developed a high-throughput assay, a 2D human intestinal stem cell-derived model, which assesses cell proliferation, cell abundance, and barrier function to predict clinical diarrhea risk.