Drug Discovery Papers Meme

One of the key challenges in CNS projects is achieving sufficient unbound brain exposure to engage the target. To predict CNS exposure, scientists employ metrics like CNS MPO scores from Pfizer and Merck, Bayesian models, and methods for balancing physicochemical properties. However, these in silico metrics often fail to correlate well with experimental data. Schrödinger's team has discovered the energy of solvation (E-sol) metric, which accurately predicts Kp,uu and has been validated with CNS-penetrant DLK inhibitors. Explore more in this detailed Drug Hunter article.

Drug Hunter has sifted through news articles, press releases, financial disclosures, SEC filings and more to bring you a roundup of 2023's biggest mergers and acquisitions (M&A) in the drug discovery world. In this 4-part series we will give you an open-access overview of the M&A landscape, and then for Drug Hunter members in the coming weeks, we will be providing in-depth coverage and analysis of the small molecule-focused (parts 2 & 3) and biologics-based deals (part 4). This premium content includes background on the targets, chemical/biological matter and clinical data driving these deals.

The team reviews hundreds of compounds from thousands of papers, press releases, and other sources each month to select candidates for Molecules of the Month. Here we have compiled a table of >70 additional molecules that were of interest in January 2024 along with highlights from some of our favorites, including molecules targeting SOS1, NLRP3, SMARCA2, and more.

During Drug Hunter’s Flash Talks, experts talk in-depth about hot topics in drug discovery. These experts also share insights beyond the subjects of their presentations, such as how they got inspired to become a drug hunter, what their favorite molecule is, what excites them most in drug discovery today, and what advice they wish they could give their younger selves. Here is a quick look at some of these insightful nuggets from Flash Talks hosted between January and August 2024.

Imagine having access to an almost infinite amount of chemical space that could include the next blockbuster medicine waiting to be discovered. The challenge for medicinal chemists is balancing the exploration of this vast space in early drug discovery with the need for focused exploration in later stages. This article explores the genesis of a new AI-powered drug design tool, AIDDISON™ from MilliporeSigma, and how this platform can benefit discovery teams around the world.