Optimizing environmental sustainability in pharmaceutical 3D printing through machine learning DOI Creative Commons
Hanxiang Li,

Manal E. Alkahtani,

Abdul W. Basit

и другие.

International Journal of Pharmaceutics, Год журнала: 2023, Номер 648, С. 123561 - 123561

Опубликована: Окт. 30, 2023

3D Printing (3DP) of pharmaceuticals could drastically transform the manufacturing medicines and facilitate widespread availability personalised healthcare. However, with increasing awareness environmental damage manufacturing, 3DP must be eco-friendly, especially when it comes to carbon emissions. This study investigated effects pharmaceutical 3DP. Using Design Experiments (DoE) Machine Learning (ML), we looked at energy use in Fused Deposition Modeling (FDM). From 136 experimental runs across four common dosage forms, identified several key parameters that contributed consumption, consequently CO

Язык: Английский

Optical biosensors - Illuminating the path to personalized drug dosing DOI
Jun Jie Ong, Thomas D. Pollard, Álvaro Goyanes

и другие.

Biosensors and Bioelectronics, Год журнала: 2021, Номер 188, С. 113331 - 113331

Опубликована: Май 13, 2021

Язык: Английский

Процитировано

48

Influence of probiotic bacteria on gut microbiota composition and gut wall function in an in-vitro model in patients with Parkinson's disease DOI Creative Commons

Jonas Ghyselinck,

Lynn Verstrepen,

Frédéric Moens

и другие.

International Journal of Pharmaceutics X, Год журнала: 2021, Номер 3, С. 100087 - 100087

Опубликована: Июль 2, 2021

We report here the potential role of a 4-strain probiotic suspension for use with patients Parkinson's disease (PD). Stool samples from group three diagnosed PD were used to create microbiotas in an

Язык: Английский

Процитировано

48

The intestinal and biliary microbiome in autoimmune liver disease—current evidence and concepts DOI Creative Commons
Timur Liwinski, Melina Heinemann, Christoph Schramm

и другие.

Seminars in Immunopathology, Год журнала: 2022, Номер 44(4), С. 485 - 507

Опубликована: Май 10, 2022

Autoimmune liver diseases are a group of immune-mediated with three distinct entities, including autoimmune hepatitis, primary biliary cholangitis, and sclerosing cholangitis. The interplay genetic environmental factors leads to the breakdown self-tolerance, resulting in hyper-responsiveness, auto-aggressive immune activation. Emerging evidence links alterations commensal microbiome configuration aberrant system activation by microbial signals, mainly via gut-liver axis. Thus, is new frontier deepen pathogenetic understanding, uncover biomarkers, inspire innovative treatments. Herein, we review current on role from both clinical basic research. We highlight recent achievements also bottlenecks limitations. Moreover, give an outlook future developments potential for applications.

Язык: Английский

Процитировано

36

Microbiome as an immune regulator in health, disease, and therapeutics DOI Creative Commons
Valeria M. Juarez,

Alyssa N. Montalbine,

Ankur Singh

и другие.

Advanced Drug Delivery Reviews, Год журнала: 2022, Номер 188, С. 114400 - 114400

Опубликована: Июнь 16, 2022

Язык: Английский

Процитировано

32

Gut microbiome immaturity and childhood acute lymphoblastic leukaemia DOI Open Access
Ioannis Peppas, Anthony M. Ford, Caroline L. Furness

и другие.

Nature reviews. Cancer, Год журнала: 2023, Номер 23(8), С. 565 - 576

Опубликована: Июнь 6, 2023

Язык: Английский

Процитировано

22

Recent advances in gut microbiota-associated natural products: structures, bioactivities, and mechanisms DOI
Huanqin Dai, Junjie Han, Tao Wang

и другие.

Natural Product Reports, Год журнала: 2023, Номер 40(6), С. 1078 - 1093

Опубликована: Янв. 1, 2023

Covering: 2014 to June 2022The gut microbiota has attracted increasing attention from researchers due its critical role in regulating human physiology and pathophysiology. Natural products (NPs) produced or transformed by microbes are key signalling mediators for a variety of physiological functions. On the other hand, NPs ethnomedicines have also been found generate health benefits through modulation microbiota. In this highlight, we review most recent studies related microbiota-derived bioactive that regulate pathological processes via microbiota-associated mechanisms. We outline strategies discovery methodologies how elucidate crosstalk between

Язык: Английский

Процитировано

20

Orally Administered Drugs and Their Complicated Relationship with Our Gastrointestinal Tract DOI Creative Commons

Stavros Bashiardes,

Christina Christodoulou

Microorganisms, Год журнала: 2024, Номер 12(2), С. 242 - 242

Опубликована: Янв. 24, 2024

Orally administered compounds represent the great majority of all pharmaceutical produced for human use and are most popular among patients since they practical easy to self-administer. Following ingestion, orally drugs begin a “perilous” journey down gastrointestinal tract their bioavailability is modulated by numerous factors. The (GI) anatomy can modulate drug accounts interpatient response heterogeneity. Furthermore, host genetics contributor modulation. Importantly, component GI that has been gaining notoriety with regard treatment interactions gut microbiota, which shares two-way interaction in be influenced able influence drugs. Overall, patient-friendly option. However, during tract, there factors patient-specific manner.

Язык: Английский

Процитировано

8

A new era in healthcare: The integration of artificial intelligence and microbial DOI Creative Commons
Da-Liang Huo, Xiaogang Wang

Medicine in Novel Technology and Devices, Год журнала: 2024, Номер 23, С. 100319 - 100319

Опубликована: Июль 2, 2024

The convergence of artificial intelligence (AI) and microbial therapeutics offers promising avenues for novel discoveries therapeutic interventions. With the exponential growth omics datasets rapid advancements in AI technology, next generation is increasingly prevalent microbiology research. In research, instrumental classification functional annotation microorganisms. Machine learning algorithms facilitate efficient accurate categorization taxa, enabling identification traits metabolic pathways within communities. Additionally, AI-driven protein design strategies hold promise engineering enzymes with enhanced catalytic activities stabilities. By predicting structures, functions, interactions, enable rational proteins tailored specific applications. systems are already present clinical laboratories form expert rules used by some automated susceptibility testing systems. future, technologists will rely more heavily on initial screening, allowing them to focus diagnostic challenges complex technical interpretations. approaches immense advancing our understanding ecosystems, accelerating drug discovery processes, fostering development groundbreaking This review aims summarize common their applications synthetic biology. We provide a comprehensive evaluation AI's utility discussing both its advantages challenges. Finally, we explore future research directions bottlenecks faced field.

Язык: Английский

Процитировано

7

Prebiotics Beyond the Gut: Omics Insights, Artificial Intelligence, and Clinical Trials in Organ-Specific Applications DOI
I.S.I. Al-Adham, Ahmed S.A. Ali Agha, Faisal Al‐Akayleh

и другие.

Probiotics and Antimicrobial Proteins, Год журнала: 2025, Номер unknown

Опубликована: Янв. 29, 2025

Язык: Английский

Процитировано

1

Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria DOI Creative Commons
Laura E. McCoubrey, Moe Elbadawi, Mine Orlu

и другие.

Pharmaceutics, Год журнала: 2021, Номер 13(7), С. 1026 - 1026

Опубликована: Июль 6, 2021

The human gut microbiome, composed of trillions microorganisms, plays an essential role in health. Many factors shape microbiome composition over the life span, including changes to diet, lifestyle, and medication use. Though not routinely tested during drug development, drugs can exert profound effects on potentially altering its functions promoting disease. This study develops a machine learning (ML) model predict whether will impair growth 40 bacterial strains. Trained 18,600 drug-bacteria interactions, 13 distinct ML models are built compared, tree-based, ensemble, artificial neural network techniques. Following hyperparameter tuning multi-metric evaluation, lead is selected: tuned extra trees algorithm with performances AUROC: 0.857 (±0.014), recall: 0.587 (±0.063), precision: 0.800 (±0.053), f1: 0.666 (±0.042). be used by pharmaceutical industry development could even adapted for use clinical settings.

Язык: Английский

Процитировано

38