AIMC Topic: Technology, Pharmaceutical

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ML-Driven Pharmaceutical Cocrystal Technology: Advances in Screening, Property Prediction and Applications.

AAPS PharmSciTech
Recently, pharmaceutical cocrystal technology has garnered considerable global attention because of its innovativeness and environmental sustainability. This technology effectively enhances the bioavailability of poorly soluble drugs and optimizes th...

Current state of machine learning implementation in pharmaceutical process modeling for oral solid dosage forms.

International journal of pharmaceutics
Driven by the Food and Drug Administration's Quality-by-Design initiative and the advancements of Industry 4.0, the pharmaceutical industry is transitioning from traditional batch manufacturing to advanced manufacturing. This transition requires resh...

A review of the state-of-the-art: progress in ultrasonic and acoustic techniques for quality assessment in the development and manufacturing of oral solid dosage forms - Part I: theoretical foundations and principles.

International journal of pharmaceutics
Over the past two decades, a diverse array of ultrasonic and acoustic elastic-wave techniques has been developed to non-destructively assess macro- and micro-scale properties of compressed Oral Solid Dosage (OSD) forms. These methods are increasingly...

Machine learning recovers corrupted pharmaceutical 3D printing formulation data.

International journal of pharmaceutics
Pharmaceutical 3D printing is an emerging digital manufacturing technology capable of autonomously producing personalised medicines. However, the same reliance on digital workflows that enables this innovation also introduces new vulnerabilities, mos...

Additive manufacturing of microneedles: a quality by design approach to clinical translation.

International journal of pharmaceutics
Transdermal drug delivery systems (TDDS) offer a painless and non-invasive route of administration but are limited by the skin barrier. Microneedles (MNs) have been shown to overcome this challenge and enable the delivery of small molecules, peptides...

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...

Machine learning real-time control of continuous granulation process.

International journal of pharmaceutics
The transition from traditional batch to continuous pharmaceutical manufacturing puts additional demands on the efficient process development and operation. The comprehensive understanding of complex interdependencies between critical process paramet...

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...

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...

Explainable artificial neural network as a soft sensor to predict the moisture content in a continuous granulation line.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The application of artificial neural networks (ANNs) has the potential to fundamentally change the pharmaceutical industry, making manufacturing more agile, robust, efficient and reliable. Although ANNs' application as data-driven soft sensors has a ...