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Pharmaceutical Preparations

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Improving on in-silico prediction of oral drug bioavailability.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Although significant development has been made in high-throughput screening of oral drug absorption and oral bioavailability, prediction continues to play an important role in prediction of oral bioavailability and assisting in the pro...

Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

European journal of drug metabolism and pharmacokinetics
BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) categorizes drugs into four classes on the basis of their solubility and metabolism. This framework allows for the study of the pharmacokinetics of transpor...

Machine Learning: A New Approach for Dose Individualization.

Clinical pharmacology and therapeutics
The application of machine learning (ML) has shown promising results in precision medicine due to its exceptional performance in dealing with complex multidimensional data. However, using ML for individualized dosing of medicines is still in its earl...

Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors.

Methods (San Diego, Calif.)
Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but i...

In silico co-crystal design: Assessment of the latest advances.

Drug discovery today
Pharmaceutical co-crystals represent a growing class of crystal forms in the context of pharmaceutical science. They are attractive to pharmaceutical scientists because they significantly expand the number of crystal forms that exist for an active ph...

Acid-resistant enzymes: the acquisition strategies and applications.

Applied microbiology and biotechnology
Enzymes have promising applications in chemicals, food, pharmaceuticals, and other variety products because of their high efficiency, specificity, and environmentally friendly properties. However, due to the complexity of raw materials, pH, temperatu...

Quantum Machine Learning Predicting ADME-Tox Properties in Drug Discovery.

Journal of chemical information and modeling
In the drug discovery paradigm, the evaluation of absorption, distribution, metabolism, and excretion (ADME) and toxicity properties of new chemical entities is one of the most critical issues, which is a time-consuming process, immensely expensive, ...

FDA Modernization Act 2.0: An insight from nondeveloping country.

Drug development research
Animal testing is required in drug development research and is crucial for assessing the efficacy and safety of medications before they are commercialized. However, the newly furnished Food and Drug Administration Modernization Act 2.0 has given new ...

New drugs and stock market: a machine learning framework for predicting pharma market reaction to clinical trial announcements.

Scientific reports
Pharmaceutical companies operate in a strictly regulated and highly risky environment in which a single slip can lead to serious financial implications. Accordingly, the announcements of clinical trial results tend to determine the future course of e...

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds.

Expert opinion on drug discovery
INTRODUCTION: Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recen...