10 Most Read Journal Articles of 2023

Authors: Nevarez J

In our industry, new research is constantly evolving our most current knowledge—and it’s critical to stay up-to-date with the latest advancements and best practices. As we look ahead to 2024, take time to catch up on what you missed in 2023 and read what your industry peers were doing and learning about this year. 

We’ve gathered this year’s 10 most-read journal articles from our resource center. Happy reading and happy new year! 


Integrating Forward and Reverse Translation in PBPK Modeling to Predict Food Effect on Oral Absorption of Weakly Basic Drugs 

GastroPlus® has been commonly used to predict how food might affect the oral absorption of drugs.  

The two examples presented in this paper show how middle-out modeling approaches can be used to predict the magnitude and direction of food effects provided the model is verified on fasted state PK data. 


Acalabrutinib Maleate Tablets: The Physiologically Based Biopharmaceutics Model behind the Drug Product Dissolution Specification 

GastroPlus can also be used to understand how drugs dissolve and behave in the body. 

In this paper, find out how a combination of exposure prediction and the use of a PK–PD model allowed researchers to demonstrated that the proposed drug product dissolution specification was acceptable.  


Mechanistic Modeling of Ophthalmic, Nasal, Injectable, and Implant Generic Drug Products: A Workshop Summary Report 

This article summarizes the presentations and panel discussion from a public workshop that provided research updates and information on the current state of the use of PBPK modeling approaches to support generic product development for ophthalmic, injectable, nasal, and implant drug products. 


Investigating bile acid-mediated cholestatic drug-induced liver injury using a mechanistic model of multidrug resistance protein 3 (MDR3) inhibition 

This publication outlines how DILIsym® was extended to represent key features of the bile duct, cholangiocyte functionality, bile acid and phospholipid disposition, and cholestatic hepatotoxicity. It further explains how it can be used to predict drug-induced bile duct injury in humans and DILI liability for compounds with previously studied interactions with bile acid transport. 


pK50─A Rigorous Indicator of Individual Functional Group Acidity/Basicity in Multiprotic Compounds  

In this publication, researchers propose using pK50 (instead of pKa measured by standard titration experiments) for assessing the acidity or basicity of organic functional groups in multiprotic compounds.  


Leveraging Physiologically Based Modelling to Provide Insights on the Absorption of Paliperidone Extended-Release Formulation under Fed and Fasting Conditions  

Paliperidone was approved in 2006 by the FDA as an extended release tablet for the treatment of schizophrenia. However, food can have a range of effects on gastrointestinal physiology that can affect solubility, the dissolution rate, absorption and the pharmacokinetics.  

This paper outlines how researchers applied physiologically based absorption modeling (PBAM) to gain insights on paliperidone ER absorption under fed and fasting conditions. 



Assessing Liver Effects of Cannabidiol and Valproate Alone and in Combination Using Quantitative Systems Toxicology 

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox-Gastaut syndrome and tuberous sclerosis complex, elevated levels of serum alanine aminotransferase (ALT) were observed in some patients. The incidence of elevated ALT levels was greater with patients who were also receiving treatment with valproate (VPA) before beginning treatment with CBD. 


Virtual Docking, design and in silico ADMET profiling of novel Rho-associated protein kinases-1 (ROCK1) inhibitors 

Overexpression of Rho-associated protein kinases has been associated with multiple diseases, including tumors, but none of the ROCK inhibitors are currently used for cancer treatment—even though some have been shown to have anti-tumor potential. 

Researchers set out to develop novel ROCK1 inhibitors using the structure-based method, molecular docking, and prediction of pharmacokinetic properties using ADMET Predictor®. This paper outlines their work and results. 


Quantitative Systems Toxicology identifies independent mechanisms for hepatotoxicity and bilirubin elevations due to AKR1C3 Inhibitor BAY1128688 

This article outlines how BAY1128688, a selective inhibitor of AKR1C3 that was terminated due to drug-induced liver injury, was used to refine DILIsym predictions and provide insight into mechanisms behind hepatotoxicity and bilirubin elevations. 


AIDD, an interactive AI-driven drug design system that uses molecular evolution and mechanistic pharmacokinetic simulation to optimize multiple property objectives simultaneously  

Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico designed molecules advancing to the clinic have demonstrated the contribution of this field to medicine.  

The findings in this publication demonstrate that AIDD generates molecules with good combinations of desirable predicted properties, in many cases better than those of analogs that its activity models are trained on. 


We’re proud to be a part of the science and research that drives the future of the pharmaceutical and biotechnology industries.  

If you’re curious about any of our software platforms mentioned in the articles above, let us know.