AIMC Topic: Excipients

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A quantitative size stability metrics for long-acting suspensions and its prediction with machine learning.

International journal of pharmaceutics
Defining suspension stability can be extremely complex, but beyond critical during the formulation development of nano- and microsuspensions intended for long-acting injectables. As of now, the current practice is based on the trial-and-error approac...

From Liquid SNEDDS to Solid SNEDDS: A Comprehensive Review of Their Development and Pharmaceutical Applications.

The AAPS journal
The liquid and solid formulations of self-nano-emulsifying drug delivery systems (SNEDDS) have garnered significant attention in the pharmaceutical field for their ability to enhance the solubility and absorption of hydrophobic drugs. While both liqu...

Bayesian Optimization for Efficient Multiobjective Formulation Development of Biologics.

Molecular pharmaceutics
Biologics, including emerging engineered formats, can often exhibit poor developability profiles, complicating their translation into successful therapeutics. While formulation design can substantially mitigate some developability issues, it represen...

Enhanced ribbon quality in roller compaction process by mitigating splitting through a machine-learning framework.

International journal of pharmaceutics
Ribbon splitting, a phenomenon that can occur during the roller compaction operation used in dry granulation processes, can lead to compromised granule uniformity, poor tabletability, and ultimately, off-specification tablet production. Despite its i...

Factors Influencing the Dispersibility of Glycopyrronium Bromide and Indacaterol Maleate - Combined In Vitro and In Silico Study.

AAPS PharmSciTech
The development of dry powder inhalers (DPIs) for pulmonary drug delivery is complex, requiring optimization of variable factors to ensure effective lung deposition. This study investigates the factors influencing the dispersibility of glycopyrronium...

Advancing Direct Tablet Compression with AI: A multi-task framework for quality control, batch acceptance, and causal analysis.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Pharmaceutical manufacturing has surged in drug development with the rise of Pharma 4.0, leveraging artificial intelligence (AI) to improve efficiency, optimize resource use, and reduce production times. Direct Tablet Compression (DTC), a key manufac...

Recent advances in dry powder inhalation formulations prepared by co-spray drying technology: a comprehensive review.

International journal of pharmaceutics
Co-spray drying technology represents an increasingly important approach in preparing dry powder inhalation (DPI) formulations. Compared to conventional spray drying, co-spray drying typically yields particles characterized by improved aerosol perfor...

Predicting Powder Blend Flowability from Individual Constituent Properties Using Machine Learning.

Pharmaceutical research
PURPOSE: Predicting powder blend flowability is necessary for pharmaceutical manufacturing but challenging and resource-intensive. The purpose was to develop machine learning (ML) models to help predict flowability across multiple flow categories, id...

Machine Learning-Based Prediction of Drug Solubility in Lipidic Environments: The Sol_ME Tool for Optimizing Lipid-Based Formulations with a Preliminary Apalutamide Case Study.

AAPS PharmSciTech
Lipid-based formulations are essential for enhancing drug solubility and bioavailability, yet selecting optimal lipid excipients for specific drugs remains challenging. This study introduces Sol_ME, a machine learning-based model designed to predict ...