Simulations Plus Announces Extensions of U.S. FDA and NIEHS Research Collaborations

Simulations Plus Announces Extensions of U.S. FDA and NIEHS Research Collaborations

Keywords: FDA, food and chemical safety assessmets, in silico, model-informed drug development, New Approach Methodologies (NAMs), U.S. Food and Drug Administration (FDA), U.S. National Institute of Environmental Health Sciences (NIEHS)

Extended projects support ongoing research into computational approaches and new approach methodologies for food and chemical safety assessment

Building Confidence in Physiologically BasedPharmacokinetic Modeling of CYP3A InductionMediated by Rifampin: An Industry Perspective

Building Confidence in Physiologically BasedPharmacokinetic Modeling of CYP3A InductionMediated by Rifampin: An Industry Perspective

Authors: Reddy MB, Cabalu T, De Zwart L, Ramsden D, Dowty M, Taskar KS, Badée J, Bolleddula J, Boulu L, Fu Q, Kotsuma M, Leblanc AF, Lewis G, Liang G, Parrott N, Pilla Reddy V, Prakash C, Shah K, Umehara K, Mukherjee D, Rehmel J, Hariparsad N
Publication: Clinical Pharmacology & Therapeutics
Keywords: CYP3A, DDI simulations, gastroplus, PBPK modeling, physiologically based pharmacokinetic modeling, rifampin
Software: GastroPlus®

Physiologically- based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug–druginteractions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made withsufficient confidence.

High-Throughput Physiologically Based Pharmacokinetic Model for Rodent Pharmacokinetics Prediction Using Machine Learning-Predicted Inputs and a Large In Vivo Pharmacokinetics Data Set

High-Throughput Physiologically Based Pharmacokinetic Model for Rodent Pharmacokinetics Prediction Using Machine Learning-Predicted Inputs and a Large In Vivo Pharmacokinetics Data Set

Authors: Bassani D, Andrews-Morger A, Zhang J, Docci L, Cecere G, Pähler A, Belubbi T, Laye P, Shih I, Parrott NJ
Publication: Mol Pharm
Keywords: compound optimization, drug discovery, gastroplus, high-throughput PBPK (HT-PBPK), machine learning (ML), PK prediction
Software: GastroPlus®

Accurate prediction of the pharmacokinetic (PK) properties of small-molecule drug candidates is a critical aspect of pharmaceutical research.

Design, Synthesis, and Pharmacological Evaluation of Metabolically Stable Apelin Receptor Antagonists with Improved In Vivo Exposure and Efficacy in Ovarian Cancer

Design, Synthesis, and Pharmacological Evaluation of Metabolically Stable Apelin Receptor Antagonists with Improved In Vivo Exposure and Efficacy in Ovarian Cancer

Authors: Elsheikh MS, Bist G, Kim S, Huang RY, Ruszaj D, Angevine D, Duminuco A, You Y, Woo S
Publication: J Med Chem
Keywords: a, admet predictor, Apelin Receptor Antagonists, in vivo exposure, ovarian cancer
Software: ADMET Predictor®

The apelin receptor (APJ) has emerged as a potential novel therapeutic target in cancer due to its role in regulating cell proliferation, angiogenesis, and metastasis.