Simulations Plus

In systems biology, we often speak of emergence—how complex systems yield behaviors not apparent from their individual parts.

As every researcher in early development knows, there is constant pressure to identify high-quality drug candidates—while also increasing the speed and efficiency of the discovery process.

As AI tools gain traction in drug development, there is growing enthusiasm around their potential to predict drug-induced liver injury (DILI).

Both the U.S. Food and Drug Administration (FDA) (1) and the European Medicines Agency (EMA) (2) have articulated clear regulatory expectations for the implementation and advancement of non-animal methods, known as new approach methodologies (NAMs).

The challenges of developing drug and biological products for rare diseases

As the adage goes, “time is money,” and the drug development pipeline is no exception. Separately, both “time” and “money” are crucial considerations at every stage of drug development

In the complex world of R&D, acronyms like PBPK and PBBM often seem interchangeable—but they're not.

The pharmaceutical industry is on the brink of a transformative shift, with artificial intelligence (AI) increasingly being leveraged across the drug product lifecycle.

This blog post continues our ongoing series on leveraging quantitative systems pharmacology (QSP) to enhance drug development.

When it comes to PK/PD modeling, many researchers stick with the tools they know, even when those tools may not be the most efficient or insightful.

In an industry that’s constantly evolving, staying ahead of the curve is crucial. Every breakthrough, every new piece of research can shape the future—and if you’re not in the loop, you risk falling behind.

Does this sound familiar? You are a pharmacometric modeler facing a tight deadline.

GLP-1 agonists have become a crucial component in the treatment of metabolic disorders like type 2 diabetes and obesity.

Modeling is increasingly important for the speed and success of our drug development programs, but the learning curve to be effective can be high.

Patient trust is critical for ensuring adequate enrollment and retention of clinical trial participants.

Patient safety is paramount in any clinical trial.

You’re the head of medicinal chemistry. Your focus is on developing molecules that balance (often conflicting) objectives to achieve the target compound profile, and it consumes every spare minute.

With a new interface, updated workflows, and advanced features, it may be challenging to know how to get started with GastroPlus(R) X.

New guidance was recently released by the International Council for Harmonisation (ICH) regarding bioequivalence for immediate release solid oral dosage forms.

In the biopharma industry, we often focus on scientific research and research methodologies. However, software design and usability is also vital in translating complex data and technologies into accessible and user-friendly solutions.