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Machine Learning
Development of a potential anti-cancer pulmonary nanosystem consisted of chitosan-doped LeciPlex…
A novel self-assembled lecithin-based cationic nanocarrier (LeciPlex) doped with chitosan was prepared to improve Resveratrol solubility and anticancer efficacy. Using on a machine learning method based on regression analysis, LP5 (composed of lecithin, Peceol® and chitosan) was selected as the…
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Machine Learning and Machine Vision Accelerate 3D Printed Orodispersible Film Development
Orodispersible films (ODFs) are an attractive delivery system for a myriad of clinical applications and possess both large economical and clinical rewards. However, the manufacturing of ODFs does not adhere to contemporary paradigms of personalised, on-demand medicine, nor sustainable manufacturing.…
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Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm
Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development…
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Machine learning predicts the effect of food on orally administered medicines
Food-mediated changes to drug absorption, termed the food effect, are hard to predict and can have significant implications for the safety and efficacy of oral drug products in patients. Mimicking the prandial states of the human gastrointestinal tract in preclinical studies is challenging, poorly…
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Machine Learning Predicts Drug Metabolism and Bioaccumulation by Intestinal Microbiota
Over 150 drugs are currently recognised as being susceptible to metabolism or bioaccumulation (together described as depletion) by gastrointestinal microorganisms; however, the true number is likely higher. Microbial drug depletion is often variable between and within individuals, depending on their…
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Use of machine learning in prediction of granule particle size distribution and tablet tensile…
In the manufacturing of pharmaceutical Oral Solid Dosage (OSD) forms, Particle Size Distribution (PSD) and Tensile Strength (TS) are common in-process tests that are controlled in order to achieve the quality targets of the end-product. The Quality by Design (QbD) concept elaborates process…
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Design of Biopharmaceutical Formulations Accelerated by Machine Learning
In addition to activity, successful biological drugs must exhibit a series of suitable developability properties, which depend on both protein sequence and buffer composition. In the context of this high-dimensional optimization problem, advanced algorithms from the domain of machine learning are…
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Machine learning predicts 3D printing performance of over 900 drug delivery systems
Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimization. Artificial intelligence (AI) is a technology…
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Artificial Neural Networks to Predict the Apparent Degree of Supersaturation in Supersaturated…
In response to the increasing application of machine learning (ML) across many facets of pharmaceutical development, this pilot study investigated if ML, using artificial neural networks (ANNs), could predict the apparent degree of supersaturation (aDS) from two supersaturated LBFs (sLBFs). Accuracy…
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Recent Development in Pharmaceutical 3D Printing: A Bird’s Eye Perspective
Pharmaceutical product development is constantly witnessing advancements in the creation of novel delivery methods in order to enhance medication therapeutic effectiveness. Furthermore, 3D printing (3DP) has been utilized to produce medication delivery systems and biomedical equipment, resulting in…
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