Multi-label classifier based on histogram of gradients for predicting the anatomical therapeutic chemical class/classes of a given compound

Background: Unused medicines represent a major source of wastage in healthcare systems around the world. Previous studies have suggested the potential cost savings from recycling the waste medicines. However, issues of product safety and integrity often deter healthcare institutions from recycling donated medications. Aim: To evaluate the feasibility of medication recycling and to assess the actual cost savings from recycling waste medicines and whether reusability of waste medicines differed among various drug classes and donor sources. Design and setting: Donated medications from hospitals, private medical clinics and patients were collected and assessed using a medication recycling protocol in a hospice care setting from November 2013 through January 2014. Costs were calculated using a reference pricing list from a public hospital. Results: A total of 244 donations, amounting to 20,759 dosage units, were collected during the study period. Most donations (90.8%) were reusable, providing a total of S$5266 in cost savings. Less than 2 h daily was spent by a single pharmacy technician on the sorting and distributing processes. Medications donated by health facilities were thrice more likely to be reusable than those by patients (odds ratio = 3.614, 95% confidence interval = 3.127, 4.176). Medications belonging to Anatomical Therapeutic Chemical class G (0.0%), H (8.2%) and L (30.0%) were the least reusable. Conclusion: Most donated medications were reusable. The current protocol can be further streamlined to focus on the more reusable donor sources and drug classes and validated in other settings. Overall, we opine that it is feasible to practise medication recycling on a larger scale to reduce medication wastage.

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Potentially harmful excipients in neonatal medicines: a pan-European observational study

Archives of Disease in Childhood ◽

10.1136/archdischild-2014-307793 ◽

2015 ◽

Vol 100 (7) ◽

pp. 694-699 ◽

Cited By ~ 36

Author(s):

Georgi Nellis ◽

Tuuli Metsvaht ◽

Heili Varendi ◽

Karolin Toompere ◽

Jana Lass ◽

...

Keyword(s):

Propylene Glycol ◽

Anatomical Therapeutic Chemical ◽

Demographic Data ◽

Active Pharmaceutical Ingredient ◽

Geographical Region ◽

Polysorbate 80 ◽

Free Products ◽

Saccharin Sodium ◽

Anatomical Therapeutic Chemical Class ◽

Harmful Excipients

ObjectivesWe aimed to describe administration of eight potentially harmful excipients of interest (EOI)—parabens, polysorbate 80, propylene glycol, benzoates, saccharin sodium, sorbitol, ethanol and benzalkonium chloride—to hospitalised neonates in Europe and to identify risk factors for exposure.MethodsAll medicines administered to neonates during 1 day with individual prescription and demographic data were registered in a web-based point prevalence study. Excipients were identified from the Summaries of Product Characteristics. Determinants of EOI administration (geographical region, gestational age (GA), active pharmaceutical ingredient, unit level and hospital teaching status) were identified using multivariable logistical regression analysis.ResultsOverall 89 neonatal units from 21 countries participated. Altogether 2095 prescriptions for 530 products administered to 726 neonates were recorded. EOI were found in 638 (31%) prescriptions and were administered to 456 (63%) neonates through a relatively small number of products (n=142; 27%). Parabens, found in 71 (13%) products administered to 313 (43%) neonates, were used most frequently. EOI administration varied by geographical region, GA and route of administration. Geographical region remained a significant determinant of the use of parabens, polysorbate 80, propylene glycol and saccharin sodium after adjustment for the potential covariates including anatomical therapeutic chemical class of the active ingredient.ConclusionsEuropean neonates receive a number of potentially harmful pharmaceutical excipients. Regional differences in EOI administration suggest that EOI-free products are available and provide the potential for substitution to avoid side effects of some excipients.

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Short Communication: A Note of Caution to Users of ECOSAR

Water Quality Research Journal ◽

10.2166/wqrj.1999.006 ◽

1999 ◽

Vol 34 (1) ◽

pp. 179-182 ◽

Cited By ~ 25

Author(s):

Klaus L.E. Kaiser ◽

John C. Dearden ◽

Werner Klein ◽

T. Wayne Schultz

Keyword(s):

Environmental Protection Agency ◽

Partition Coefficients ◽

Short Communication ◽

Computer Software ◽

Aquatic Organisms ◽

Protection Agency ◽

Personal Computer Software ◽

Linear Correlations ◽

Class Representative ◽

Chemical Class

Abstract ECOSAR (1998), a personal computer software program available from the U.S. Environmental Protection Agency (EPA) and affiliated vendors, is used to estimate the toxicity of chemicals to aquatic organisms, particularly fish, daphnid and algae species. It relies on approximately 150 equations, each for a chemical class of substances (Clements et al. 1996), which are linear correlations (SARs) of measured toxicity values of class-representative compounds with their octanol/water partition coefficients, with the latter taken from a database or computed by a companion program.

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Convolutional Neural Networks for ATC Classification

Current Pharmaceutical Design ◽

10.2174/1381612824666181112113438 ◽

2019 ◽

Vol 24 (34) ◽

pp. 4007-4012 ◽

Cited By ~ 5

Author(s):

Alessandra Lumini ◽

Loris Nanni

Keyword(s):

Classification System ◽

Feature Vector ◽

Chemical Interaction ◽

Anatomical Therapeutic Chemical ◽

World Health ◽

Therapeutic Effects ◽

True Rate ◽

Unknown Compound ◽

The Absolute ◽

Learned Features

Background: Anatomical Therapeutic Chemical (ATC) classification of unknown compound has raised high significance for both drug development and basic research. The ATC system is a multi-label classification system proposed by the World Health Organization (WHO), which categorizes drugs into classes according to their therapeutic effects and characteristics. This system comprises five levels and includes several classes in each level; the first level includes 14 main overlapping classes. The ATC classification system simultaneously considers anatomical distribution, therapeutic effects, and chemical characteristics, the prediction for an unknown compound of its ATC classes is an essential problem, since such a prediction could be used to deduce not only a compound’s possible active ingredients but also its therapeutic, pharmacological, and chemical properties. Nevertheless, the problem of automatic prediction is very challenging due to the high variability of the samples and the presence of overlapping among classes, resulting in multiple predictions and making machine learning extremely difficult. Methods: In this paper, we propose a multi-label classifier system based on deep learned features to infer the ATC classification. The system is based on a 2D representation of the samples: first a 1D feature vector is obtained extracting information about a compound’s chemical-chemical interaction and its structural and fingerprint similarities to other compounds belonging to the different ATC classes, then the original 1D feature vector is reshaped to obtain a 2D matrix representation of the compound. Finally, a convolutional neural network (CNN) is trained and used as a feature extractor. Two general purpose classifiers designed for multi-label classification are trained using the deep learned features and resulting scores are fused by the average rule. Results: Experimental evaluation based on rigorous cross-validation demonstrates the superior prediction quality of this method compared to other state-of-the-art approaches developed for this problem. Conclusion: Extensive experiments demonstrate that the new predictor, based on CNN, outperforms other existing predictors in the literature in almost all the five metrics used to examine the performance for multi-label systems, particularly in the “absolute true” rate and the “absolute false” rate, the two most significant indexes. Matlab code will be available at https://github.com/LorisNanni.

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4H-1,3-Benzothiazin-4-one a Promising Class Against MDR/XDR-TB

Current Topics in Medicinal Chemistry ◽

10.2174/1568026619666190305130809 ◽

2019 ◽

Vol 19 (8) ◽

pp. 567-578 ◽

Cited By ~ 1

Author(s):

Marcus Vinicius Nora de Souza ◽

Thais Cristina Mendonça Nogueira

Keyword(s):

Treatment Time ◽

Public Health Problem ◽

New Drugs ◽

Global Public Health ◽

Synthesis Mechanism ◽

Highly Active ◽

Latent Disease ◽

Resistant Strains ◽

Chemical Class ◽

Global Public Health Problem

Nowadays, tuberculosis (TB) is an important global public health problem, being responsible for millions of TB-related deaths worldwide. Due to the increased number of cases and resistance of Mycobacterium tuberculosis to all drugs used for the treatment of this disease, we desperately need new drugs and strategies that could reduce treatment time with fewer side effects, reduced cost and highly active drugs against resistant strains and latent disease. Considering that, 4H-1,3-benzothiazin-4-one is a promising class of antimycobacterial agents in special against TB-resistant strains being the aim of this review the discussion of different aspects of this chemical class such as synthesis, mechanism of action, medicinal chemistry and combination with other drugs.

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Thai Traffic Sign Classification and Recognition System Based on Histogram of Gradients, Color Layout Descriptor, and Normalized Correlation Coefficient

2020 - 5th International Conference on Information Technology (InCIT) ◽

10.1109/incit50588.2020.9310778 ◽

2020 ◽

Author(s):

Nattapol Namyang ◽

Suphakant Phimoltares

Keyword(s):

Correlation Coefficient ◽

Recognition System ◽

Traffic Sign ◽

Histogram Of Gradients ◽

Traffic Sign Classification

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Perylene and perinone pigments

Physical Sciences Reviews ◽

10.1515/psr-2020-0190 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Robert Christie ◽

Adrian Abel

Keyword(s):

High Performance ◽

Heat Stability ◽

High Heat ◽

Structural Features ◽

Fastness Properties ◽

Tetracarboxylic Acid ◽

Organic Pigments ◽

Orange Color ◽

Cis Isomer ◽

Chemical Class

Abstract Perylenes and perinones are separate groups of pigments categorized within the carbonyl chemical class. The two pigment groups show similarities, for example, in their chemical structural features and, to an extent, in their technical and application properties as high-performance organic pigments. Perylenes constitute a series of firmly established high-performance pigments, offering red and violet colors, and also extending to black. Synthetically, they are derived from perylene-1,4,5,8-tetracarboxylic acid. The perylenes tend to be quite expensive pigments, but their high levels of fastness properties mean that they are suitable for highly demanding applications. In particular, they offer very high heat stability. Two perinone pigments are used commercially. In their synthesis from naphthalene-1,4,5,8-tetracarboxylic acid, they are formed as mixtures of the two isomers, which can be separated. The trans isomer, CI Pigment Orange 43, is a highly important commercial pigment, especially for plastics, while the cis isomer, CI Pigment Red 194, is bordeaux in color and is of much lesser importance. The perinone, CI Pigment Orange 43, provides a brilliant orange color and has very good fastness properties. Its commercial manufacture involves a challenging multistage procedure and consequently it is one of the most expensive organic pigments on the market.

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Drug Prescription Profiles in Patients with Polypharmacy in Spain: A Large-Scale Pharmacoepidemiologic Study Using Real-World Data

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094754 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4754

Author(s):

Miguel Ángel Hernández-Rodríguez ◽

Ermengol Sempere-Verdú ◽

Caterina Vicens-Caldentey ◽

Francisca González-Rubio ◽

Félix Miguel-García ◽

...

Keyword(s):

Psychotropic Drugs ◽

Large Scale ◽

Anatomical Therapeutic Chemical ◽

Drug Prescription ◽

Age Groups ◽

System Level ◽

Real World Data ◽

Converting Enzyme Inhibitors ◽

Cross Sectional ◽

Β Blockers

We aimed to identify and compare medication profiles in populations with polypharmacy between 2005 and 2015. We conducted a cross-sectional study using information from the Computerized Database for Pharmacoepidemiologic Studies in Primary Care (BIFAP, Spain). We estimated the prevalence of therapeutic subgroups in all individuals 15 years of age and older with polypharmacy (≥5 drugs during ≥6 months) using the Anatomical Therapeutic Chemical classification system level 4, by sex and age group, for both calendar years. The most prescribed drugs were proton-pump inhibitors (PPIs), statins, antiplatelet agents, benzodiazepine derivatives, and angiotensin-converting enzyme inhibitors. The greatest increases between 2005 and 2015 were observed in PPIs, statins, other antidepressants, and β-blockers, while the prevalence of antiepileptics was almost tripled. We observed increases in psychotropic drugs in women and cardiovascular medications in men. By patient´s age groups, there were notable increases in antipsychotics, antidepressants, and antiepileptics (15–44 years); antidepressants, PPIs, and selective β-blockers (45–64 years); selective β-blockers, biguanides, PPIs, and statins (65–79 years); and in statins, selective β-blockers, and PPIs (80 years and older). Our results revealed important increases in the use of specific therapeutic subgroups, like PPIs, statins, and psychotropic drugs, highlighting opportunities to design and implement strategies to analyze such prescriptions’ appropriateness.

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A chemoinformatic analysis of atoms, scaffolds and functional groups in natural products

Physical Sciences Reviews ◽

10.1515/psr-2019-0096 ◽

2021 ◽

Vol 0 (0) ◽

Cited By ~ 1

Author(s):

Joelle Ngo Hanna ◽

Boris D. Bekono ◽

Luc C. O. Owono ◽

Flavien A. A. Toze ◽

James A. Mbah ◽

...

Keyword(s):

Natural Products ◽

Drug Discovery ◽

Physicochemical Properties ◽

Functional Groups ◽

Atomic Composition ◽

Synthetic Compounds ◽

Chemical Libraries ◽

Synthetic Drugs ◽

Drugs Analysis ◽

Chemical Class

Abstract In the quest to know why natural products (NPs) have often been considered as privileged scaffolds for drug discovery purposes, many investigations into the differences between NPs and synthetic compounds have been carried out. Several attempts to answer this question have led to the investigation of the atomic composition, scaffolds and functional groups (FGs) of NPs, in comparison with synthetic drugs analysis. This chapter briefly describes an atomic enumeration method for chemical libraries that has been applied for the analysis of NP libraries, followed by a description of the main differences between NPs of marine and terrestrial origin in terms of their general physicochemical properties, most common scaffolds and “drug-likeness” properties. The last parts of the work describe an analysis of scaffolds and FGs common in NP libraries, focusing on huge NP databases, e.g. those in the Dictionary of Natural Products (DNP), NPs from cyanobacteria and the largest chemical class of NP – terpenoids.

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Medication Prescribed Within 1 Year Preceding Fall-Related Injuries in Older Adults in Ontario, Canada

Innovation in Aging ◽

10.1093/geroni/igaa057.761 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 236-236

Author(s):

Yu Ming ◽

Aleksandra Zecevic ◽

Richard Booth ◽

Susan Hunter ◽

Andrew Johnson ◽

...

Keyword(s):

Older Adults ◽

Fall Risk ◽

Anatomical Therapeutic Chemical ◽

Group Discussion ◽

Head Injuries ◽

Prescription Medication ◽

Population Based ◽

Age Group ◽

Secondary Health Care ◽

One Year

Abstract Background: The consequences of fall-related injuries are becoming more significant due to ageing societies worldwide. This study aims to provide information on medications prescribed to older adults within one year before they experienced fall-related injury in Ontario, Canada. Methods: A population-based descriptive study of older adults (66 years and older) who experienced fall-related injury was conducted using administrative secondary health care data of Ontario. The percentages of patients prescribed each Anatomical Therapeutic Chemical 4th level medication class and fall-risk increasing drugs one year before their fall-related injuries was summarized. Results: From 2010 to 2014, 288,251 older adults (63.2% females) were admitted to Emergency Department due to fall-related injury, 39.9% were fall-related fractures, 12.6% were head injuries. One year prior to their injury, 48.46% of older adults were prescribed with statins; 35.23% were prescribed with diuretics; 26.84% were prescribed with antidepressants; 25.90% were prescribed with opioids and 16.61% were prescribed with anxiolytics. A higher percentage of females were prescribed with diuretics, antidepressants, and anxiolytics than males. 85 years and older people had higher percentage of prescription of diuretics, antidepressants and antipsychotics than other age group. Discussion: In general, older adults diagnosed with fall-related injuries were prescribed with more opioids, benzodiazepines and antidepressants than other general older adults. There were distinct patterns of prescription medication within each sex and age group (66-74 group, 75-84 group and 85 years and older group). Further association between medications and fall-related injuries need to be established using well-defined cohort studies.

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