Active Machine learning for formulation of precision probiotics DOI Creative Commons
Laura E. McCoubrey,

Nidhi Seegobin,

Moe Elbadawi

et al.

International Journal of Pharmaceutics, Journal Year: 2022, Volume and Issue: 616, P. 121568 - 121568

Published: Feb. 9, 2022

It is becoming clear that the human gut microbiome critical to health and well-being, with increasing evidence demonstrating dysbiosis can promote disease. Increasingly, precision probiotics are being investigated as investigational drug products for restoration of healthy balance. To reach distal alive where density microbiota highest, oral should be protected from harsh conditions during transit through stomach small intestines. At present, few probiotic formulations designed this delivery strategy in mind. This study employs an emerging machine learning (ML) technique, known active ML, predict how excipients at pharmaceutically relevant concentrations affect intestinal proliferation a common probiotic, Lactobacillus paracasei. Starting labelled dataset just 6 bacteria-excipient interactions, ML was able effects further 111 using uncertainty sampling. The average certainty final model 67.70% experimental validation demonstrated 3/4 excipient-probiotic interactions could correctly predicted. used enable superior maximise vivo marks first use science.

Language: Английский

Connected healthcare: Improving patient care using digital health technologies DOI
Atheer Awad, Sarah J. Trenfield, Thomas D. Pollard

et al.

Advanced Drug Delivery Reviews, Journal Year: 2021, Volume and Issue: 178, P. 113958 - 113958

Published: Sept. 1, 2021

Language: Английский

Citations

262
Impact of gastrointestinal tract variability on oral drug absorption and pharmacokinetics: An UNGAP review DOI Creative Commons
Zahari Vinarov, Mohammad Abdallah, José A. G. Agúndez

et al.

European Journal of Pharmaceutical Sciences, Journal Year: 2021, Volume and Issue: 162, P. 105812 - 105812

Published: March 20, 2021

The absorption of oral drugs is frequently plagued by significant variability with potentially serious therapeutic consequences. source can be traced back to interindividual in physiology, differences special populations (age- and disease-dependent), drug formulation properties, or food-drug interactions. Clinical evidence for the impact some these factors on pharmacokinetic mounting: e.g. gastric pH emptying time, small intestinal fluid pediatrics elderly, surgical changes gastrointestinal anatomy. However, link colonic (transit composition, microbiome), sex (male vs. female) gut-related diseases (chronic constipation, anorexia cachexia) has not been firmly established yet. At same a way decrease provided pharmaceutical industry: clinical suggests that approaches employed during development exposure. This review outlines main drivers exposure potential overcome them, while highlighting existing knowledge gaps guiding future studies this area.

Language: Английский

Citations

227
Machine learning and deep learning applications in microbiome research DOI Creative Commons
Ricardo Hernández Medina, Svetlana Kutuzova, K Nielsen

et al.

ISME Communications, Journal Year: 2022, Volume and Issue: 2(1)

Published: Oct. 6, 2022

Abstract The many microbial communities around us form interactive and dynamic ecosystems called microbiomes. Though concealed from the naked eye, microbiomes govern influence macroscopic systems including human health, plant resilience, biogeochemical cycling. Such feats have attracted interest scientific community, which has recently turned to machine learning deep methods interrogate microbiome elucidate relationships between its composition function. Here, we provide an overview of how latest studies harness inductive prowess artificial intelligence methods. We start by highlighting that data – being compositional, sparse, high-dimensional necessitates special treatment. then introduce traditional novel discuss their strengths applications. Finally, outlook pipelines, focusing on bottlenecks considerations address them.

Language: Английский

Citations

153
Harnessing artificial intelligence for the next generation of 3D printed medicines DOI
Moe Elbadawi, Laura E. McCoubrey,

Francesca K. H. Gavins

et al.

Advanced Drug Delivery Reviews, Journal Year: 2021, Volume and Issue: 175, P. 113805 - 113805

Published: May 18, 2021

Language: Английский

Citations

130
Colonic drug delivery: Formulating the next generation of colon-targeted therapeutics DOI Creative Commons
Laura E. McCoubrey,

Alessia Favaron,

Atheer Awad

et al.

Journal of Controlled Release, Journal Year: 2022, Volume and Issue: 353, P. 1107 - 1126

Published: Dec. 25, 2022

Colonic drug delivery can facilitate access to unique therapeutic targets and has the potential enhance bioavailability whilst reducing off-target effects. Delivering drugs colon requires considered formulation development, as both oral rectal dosage forms encounter challenges if colon's distinct physiological environment is not appreciated. As opportunities surrounding colonic multiply, success of novel pharmaceuticals lies in their design. This review provides a modern insight into key parameters determining effective design development colon-targeted medicines. Influential features governing release, dissolution, stability, absorption are first discussed, followed by an overview most reliable strategies. Finally, appropriate vitro, vivo, silico preclinical investigations presented, with goal inspiring strategic new therapeutics.

Language: Английский

Citations

116
Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning DOI Creative Commons
Jingyue Wu, Stephanie S. Singleton, Urnisha Bhuiyan

et al.

Frontiers in Molecular Biosciences, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 19, 2024

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of gut with exceptional resolution. analysis various data, including metatranscriptomics, metagenomics, glycomics, metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, metabolites. This multi-omics approach not only provided insights into diseases but also facilitated identification biomarkers diagnosis, prognosis, treatment. Machine learning algorithms emerged powerful tools extracting meaningful from complex datasets, more recently applied to metagenomics via efficiently identifying signatures, predicting disease states, determining therapeutic targets. Despite these rapid advancements, several challenges remain, such key knowledge gaps, algorithm selection, bioinformatics software parametrization. In this mini-review, our primary focus is while recognizing that other can enhance understanding diversity organisms how they interact host. We aim explore current intersection multi-omics, medicine, machine advancing microbiome. A multidisciplinary promise improving patient outcomes era we unravel intricate interactions between health.

Language: Английский

Citations

24
Disrupting 3D printing of medicines with machine learning DOI
Moe Elbadawi, Laura E. McCoubrey,

Francesca K. H. Gavins

et al.

Trends in Pharmacological Sciences, Journal Year: 2021, Volume and Issue: 42(9), P. 745 - 757

Published: July 5, 2021

Language: Английский

Citations

82
Predicting drug-microbiome interactions with machine learning DOI
Laura E. McCoubrey, Simon Gaisford, Mine Orlu

et al.

Biotechnology Advances, Journal Year: 2021, Volume and Issue: 54, P. 107797 - 107797

Published: July 11, 2021

Language: Английский

Citations

64
Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions DOI Creative Commons
Sean M. Gibbons, Thomas Gurry, Johanna W. Lampe

et al.

Advances in Nutrition, Journal Year: 2022, Volume and Issue: 13(5), P. 1450 - 1461

Published: July 1, 2022

Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some major computational experimental tools being applied critical questions microbiota-mediated personalized nutrition health. First, discuss latest advances in silico modeling microbiota-nutrition-health axis, including application statistical, mechanistic, hybrid artificial intelligence models. Second, address high-throughput vitro techniques assessing interindividual heterogeneity, from ex vivo batch culturing stool continuous anaerobic bioreactors, more sophisticated organ-on-a-chip models integrate both host microbial compartments. Third, explore approaches better understanding personalized, diet, prebiotics, probiotics, nonhuman animal human observational studies, feeding trials crossover We highlight examples existing, consumer-facing precision platforms are currently leveraging microbiota. Furthermore, how integration broader set described piece can generate data necessary support greater diversity strategies. Finally, present vision healthcare future, which leverages design effective, individual-specific

Language: Английский

Citations

49
A Review of State-of-the-Art on Enabling Additive Manufacturing Processes for Precision Medicine DOI
Atheer Awad, Álvaro Goyanes, Abdul W. Basit

et al.

Journal of Manufacturing Science and Engineering, Journal Year: 2022, Volume and Issue: 145(1)

Published: Nov. 8, 2022

Abstract Precision medicine is an emerging healthcare delivery approach that considers variability between patients, such as genetic makeups, in contrast to the current one-size-fits-all designed treat average patient. The White House launched Medicine Initiative 2015, starting endeavor reshape delivery. To translate concept of precision from bench practice, advanced manufacturing will play integral part, including fabrication personalized drugs and drug devices screening platforms. These products are highly customized require robust yet flexible systems. field has rapidly evolved past five years. In this state-of-the-art review, manufactured for be introduced, followed by a brief review processing materials their characteristics. A on different processes applicable those aforementioned provided. status development regulatory submission quality control considerations also discussed. Finally, paper presents future outlook used medicine.

Language: Английский

Citations

39