AI Medical Compendium Topic

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Chemistry, Pharmaceutical

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From traditional to data-driven medicinal chemistry: A case study.

Drug discovery today
Artificial intelligence (AI) and data science are beginning to impact drug discovery. It usually takes considerable time and efforts until new scientific concepts or technologies make a transition from conceptual stages to practical applicability and...

IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method.

Journal of chemical information and modeling
The prediction and optimization of pharmacokinetic properties are essential in lead optimization. Traditional strategies mainly depend on the empirical chemical rules from medicinal chemists. However, with the rising amount of data, it is getting mor...

Bench to bedside: The ambitious goal of transducing medicinal chemistry from the lab to the clinic.

Bioorganic & medicinal chemistry letters
This paper deals with a critical examination on the possibility of quantitatively predicting the in vivo activity of new chemical entities (NCEs) by making use of in silico and in vitro data including three-dimensional structure of drug-target comple...

Real-time coating thickness measurement and defect recognition of film coated tablets with machine vision and deep learning.

International journal of pharmaceutics
This paper presents a system, where images acquired with a digital camera are coupled with image analysis and deep learning to identify and categorize film coating defects and to measure the film coating thickness of tablets. There were 5 different c...

Continuous Manufacturing and Molecular Modeling of Pharmaceutical Amorphous Solid Dispersions.

AAPS PharmSciTech
Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires...

Application of an AI image analysis and classification approach to characterise dissolution and precipitation events in the flow through apparatus.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Imaging and artificial intelligence (AI) approaches have been used with increasing frequency in pharmaceutical industry in recent years. Characterisation of processes such as drug dissolution and precipitation is vital in quality control testing and ...

Deep learning image analysis models pretrained on daily objects are useful for the preliminary characterization of particulate pharmaceutical samples.

Biotechnology and bioengineering
Visible and subvisible particles are a quality attribute in sterile pharmaceutical samples. A common method for characterizing and quantifying pharmaceutical samples containing particulates is imaging many individual particles using high-throughput i...

In-line particle size measurement during granule fluidization using convolutional neural network-aided process imaging.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This paper presents a machine learning-based image analysis method to monitor the particle size distribution of fluidized granules. The key components of the direct imaging system are a rigid fiber-optic endoscope, a light source and a high-speed cam...

Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning.

Journal of chemical information and modeling
Lead optimization supported by artificial intelligence (AI)-based generative models has become increasingly important in drug design. Success factors are reagent availability, novelty, and the optimization of multiple properties. Directed fragment-re...