Are Drugs Becoming More Lipophilic Over Time?

In the aftermath of the thalidomide tragedy, the FDA advised excluding females in the childbearing age from early-stage clinical trials. However, this policy resulted in the prolonged underrepresentation of women in clinical research, limiting knowledge about how drugs affect genders differently. Recent policy changes, including the NIH's emphasis on considering sex as a biological variable, aim to reduce these disparities by promoting more diverse clinical trial participation. This article explores the current landscape of endometriosis therapies and how it relates to women’s healthcare.

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 part 3 of this 4-part series, we bring you the top-ranked small molecule-focused deals by value. Covering a range of targets and modalities, this article gives Drug Hunter members in-depth background and analysis of the hottest science opening checkbooks in 2023.

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.

There has been substantial interest in the development of screening methods capable of surveying a wider sample of chemical space and larger numbers of compounds. Over the past two decades, DEL technology has evolved into a broadly utilized and validated platform in drug discovery, yielding diverse hits for a wide range of biologically relevant targets. Read the full review for a historical and technical overview of DEL technology, including how libraries are prepared and screened, a comparison to other HTS methods, and examples of successful applications in drug discovery.

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.