AIMC Topic: Chemistry, Pharmaceutical

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A multitask modelling framework for tablet manufacturability and quality attributes in direct compression using knowledge-guided neural networks.

International journal of pharmaceutics
Assessing the feasibility of a manufacturing route for a given formulation and process is a key initial step in drug product development. Additionally, the final product must meet a series of critical quality attributes to be considered suitable to m...

A mechanistic framework for predicting tablet disintegration: Integrating the Representative Capillary Evolution Model (RCEM) and the Dynamic Void Fraction Evolution Model (DVFEM).

International journal of pharmaceutics
The disintegration behaviour of pharmaceutical tablets is a critical quality attribute influencing drug release, yet predicting it from formulation and processing parameters remains challenging due to complex underlying mechanisms. This work presents...

Advances in Pharmaceutical Cocrystals and Nano-Cocrystals: Strategies for Enhancing Solubility and Translating to Clinical Use.

AAPS PharmSciTech
Poor oral bioavailability in most modern pharmaceuticals is primarily caused by poor aqueous solubility. Most NCEs (New Chemical Entities) and nearly 40% of drugs on the market fall into either Biopharmaceutical Classification System (BCS) class II o...

Breaking barriers: Medicinal chemistry strategies and advanced in-silico approaches for overcoming the BBB and enhancing CNS penetration.

European journal of medicinal chemistry
Delivering small molecules to the brain and central nervous system (CNS) is greatly hindered by the restrictive blood-brain barrier (BBB), which selectively permits essential molecules while excluding toxic molecules. This selective permeability feat...

Machine learning-based prediction of aerodynamic performance in arformoterol-lactose dry powder inhaler formulations using surface roughness features.

International journal of pharmaceutics
Dry powder inhalers (DPIs) are widely used for pulmonary drug delivery, and their aerodynamic performance is highly dependent on particle surface morphology. This paper presents a machine learning-based framework to quantitatively predict DPI aerodyn...

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...

Molecular dynamics simulations of proteins: an in-depth review of computational strategies, structural insights, and their role in medicinal chemistry and drug development.

Biological cybernetics
Molecular dynamics (MD) simulations have emerged as a powerful and extensively employed tool in biomedical research, offering insights into intricate biomolecular processes such as structural flexibility and molecular interactions, and playing a pivo...

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...