Electrochemical biosensors: a nexus for precision medicine

Pollard, Thomas D.; Ong, Jun Jie; Goyanes, Álvaro; Orlu, Mine; Gaisford, Simon; Elbadawi, Moe; Basit, Abdul W.

doi:10.1016/j.drudis.2020.10.021

Cited by 55 publications

(32 citation statements)

References 95 publications

(115 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The potential primary advantages of ML-guided in situ 3DP, like robotic surgery, include higher precision, better safety profiles, and a reduction in invasiveness [235]. In the context of pharmaceutics, in situ printing can be exploited to fabricate intricate drug-eluting devices or sensors for therapeutic drug monitoring inside the body [236,237].…”

Section: Figure 13mentioning

confidence: 99%

“…As pharmaceutical 3DP itself is already a digitalised process, it is perfectly aligned for incorporation into a cyber-physical system. Though once the upfront cost of sensors, robots, and other hardware would prohibit complete digitalisation of the pharmaceutical 3DP pipeline, these elements are consistently becoming cheaper and more accessible [237]. Essentially, ML would provide actionable insight from data, to which 3DP will execute.…”

Section: Internet Of Things For Pharmaceutical 3d Printingmentioning

confidence: 99%

See 1 more Smart Citation

Harnessing artificial intelligence for the next generation of 3D printed medicines

Elbadawi

McCoubrey

Gavins

et al. 2021

Advanced Drug Delivery Reviews

Self Cite

110

View full text Add to dashboard Cite

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

show abstract

Section: Figure 13mentioning

confidence: 99%

Section: Internet Of Things For Pharmaceutical 3d Printingmentioning

confidence: 99%

Harnessing artificial intelligence for the next generation of 3D printed medicines

Elbadawi

McCoubrey

Gavins

et al. 2021

Advanced Drug Delivery Reviews

Self Cite

110

View full text Add to dashboard Cite

show abstract

“…12,141,142 Microbiome-drug metabolism may be assessed using ML combined with biosensors, which can measure subtle alterations in pharmacokinetics in vivo . 143,144 In addition to metabolism, the absorption of drugs across biological barriers may be impacted by perturbations in microbiome composition. For example, dysbiosis of the skin microbiome can affect barrier function, potentially altering the permeation of topical drugs.…”

Section: Prediction Of Microbiome-drug Interactionsmentioning

confidence: 99%

Harnessing machine learning for development of microbiome therapeutics

et al. 2021

Self Cite

View full text Add to dashboard Cite

The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic relationship with human health. Studies elucidating the relationship between an unbalanced microbiome and disease are currently published daily. As such, microbiome big data have become a reality that provide a mine of information for the development of new therapeutics. Machine learning (ML), a branch of artificial intelligence, offers powerful techniques for big data analysis and predictionmaking, that are out of reach of human intellect alone. This review will explore how ML can be applied for the development of microbiome-targeted therapeutics. A background on ML will be given, followed by a guide on where to find reliable microbiome big data. Existing applications and opportunities will be discussed, including the use of ML to discover, design, and characterize microbiome therapeutics. The use of ML to optimize advanced processes, such as 3D printing and in silico prediction of drug-microbiome interactions, will also be highlighted. Finally, barriers to adoption of ML in academic and industrial settings will be examined, concluded by a future outlook for the field.

show abstract

“…Such sensitivity makes optical biosensors suitable for measuring serum concentrations of highly potent drugs that are administered in very small doses, such as levothyroxine (dose ~50-100 μg). Electrochemical biosensors have also been lauded for their apparent sensitivity (Pollard et al, 2021), though a literature-based comparison between the two general types of biosensors would not be fair given the differing parameters employed in each study. Nevertheless, a recent study pitted electrochemical and chemiluminescent biosensors against each other using identical protocols, and found that chemiluminescence-based biosensors generally yielded "slightly lower LOD values and wider dynamic ranges" (Roda et al, 2020).…”

Section: Strengths Of Optical Biosensorsmentioning

confidence: 99%

Optical biosensors - Illuminating the path to personalized drug dosing

Ong

Pollard

Goyanes

et al. 2021

Biosensors and Bioelectronics

Self Cite

View full text Add to dashboard Cite

Optical biosensors are low-cost, sensitive and portable devices that are poised to revolutionize the medical industry. Healthcare monitoring has already been transformed by such devices, with notable recent applications including heart rate monitoring in smartwatches and COVID-19 lateral flow diagnostic test kits. The commercial success and impact of existing optical sensors has galvanized research in expanding its application in numerous disciplines. Drug detection and monitoring seeks to benefit from the fast-approaching wave of optical biosensors, with diverse applications ranging from illicit drug testing, clinical trials, monitoring in advanced drug delivery systems and personalized drug dosing. The latter has the potential to significantly improve patients' lives by minimizing toxicity and maximizing efficacy. To achieve this, the patient's serum drug levels must be frequently measured. Yet, the current method of obtaining such information, namely therapeutic drug monitoring (TDM), is not routinely practiced as it is invasive, expensive, time-consuming and skilled labor-intensive. Certainly, optical sensors possess the capabilities to challenge this convention. This review explores the current state of optical biosensors in personalized dosing with special emphasis on TDM, and provides an appraisal on recent strategies. The strengths and challenges of optical biosensors are critically evaluated, before concluding with perspectives on the future direction of these sensors.

show abstract

Electrochemical biosensors: a nexus for precision medicine

Cited by 55 publications

References 95 publications

Harnessing artificial intelligence for the next generation of 3D printed medicines

Harnessing artificial intelligence for the next generation of 3D printed medicines

Harnessing machine learning for development of microbiome therapeutics

Optical biosensors - Illuminating the path to personalized drug dosing

Contact Info

Product

Resources

About