Example of Journal of Pharmaceutical and Biomedical Analysis format
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Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format
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Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format Example of Journal of Pharmaceutical and Biomedical Analysis format
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open access Open Access

Journal of Pharmaceutical and Biomedical Analysis — Template for authors

Publisher: Elsevier
Categories Rank Trend in last 3 yrs
Pharmaceutical Science #33 of 166 down down by 6 ranks
Analytical Chemistry #27 of 122 down down by 3 ranks
Spectroscopy #19 of 74 down down by 7 ranks
Clinical Biochemistry #29 of 113 up up by 3 ranks
Drug Discovery #38 of 145 down down by 5 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 2626 Published Papers | 15387 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 06/06/2020
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FAQ

Related Journals

open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 8.3
SJR: 0.786
SNIP: 1.529
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recommended Recommended

American Chemical Society

Quality:  
High
CiteRatio: 6.5
SJR: 0.976
SNIP: 1.593
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Wiley

Quality:  
High
CiteRatio: 6.0
SJR: 1.065
SNIP: 1.136
open access Open Access

American Chemical Society

Quality:  
High
CiteRatio: 8.1
SJR: 1.13
SNIP: 1.113

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

3.209

8% from 2018

Impact factor for Journal of Pharmaceutical and Biomedical Analysis from 2016 - 2019
Year Value
2019 3.209
2018 2.983
2017 2.831
2016 3.255
graph view Graph view
table view Table view

5.9

7% from 2019

CiteRatio for Journal of Pharmaceutical and Biomedical Analysis from 2016 - 2020
Year Value
2020 5.9
2019 5.5
2018 5.1
2017 5.5
2016 5.4
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 8% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 7% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.777

2% from 2019

SJR for Journal of Pharmaceutical and Biomedical Analysis from 2016 - 2020
Year Value
2020 0.777
2019 0.795
2018 0.786
2017 0.919
2016 0.92
graph view Graph view
table view Table view

1.246

6% from 2019

SNIP for Journal of Pharmaceutical and Biomedical Analysis from 2016 - 2020
Year Value
2020 1.246
2019 1.171
2018 1.185
2017 1.234
2016 1.361
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 2% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 6% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Pharmaceutical and Biomedical Analysis

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Elsevier

Journal of Pharmaceutical and Biomedical Analysis

This journal is an international medium directed towards the needs of academic, clinical, government and industrial analysis by publishing original research reports and critical reviews on pharmaceutical andbiomedical analysis. It covers the interdisciplinary aspects of analys...... Read More

Pharmaceutical Science

Spectroscopy

Clinical Biochemistry

Analytical Chemistry

Drug Discovery

Pharmacology, Toxicology and Pharmaceutics

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Last updated on
06 Jun 2020
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ISSN
0731-7085
i
Impact Factor
High - 1.521
i
Acceptance Rate
26%
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
i
Bibliography Name
elsarticle-num
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Citation Type
Numbered
[25]
i
Bibliography Example
G. E. Blonder, M. Tinkham, T. M. Klapwijk, Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion, Phys. Rev. B 25 (7) (1982) 4515–4532. URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

Journal Article DOI: 10.1016/S0731-7085(96)02024-9
Stability of curcumin in buffer solutions and characterization of its degradation products
Ying-Jan Wang1, Min-Hsiung Pan1, Ann-Lii Cheng1, Liang-In Lin1, Yuan Soon Ho1, Chang-Yao Hsieh1, Jen-Kun Lin1

Abstract:

The degradation kinetics of curcumin under various pH conditions and the stability of curcumin in physiological matrices were investigated. When curcumin was incubated in 0.1 M phosphate buffer and serum-free medium, pH 7.2 at 37 degrees C, about 90% decomposed within 30 min. A series of pH conditions ranging from 3 to 10 wer... The degradation kinetics of curcumin under various pH conditions and the stability of curcumin in physiological matrices were investigated. When curcumin was incubated in 0.1 M phosphate buffer and serum-free medium, pH 7.2 at 37 degrees C, about 90% decomposed within 30 min. A series of pH conditions ranging from 3 to 10 were tested and the result showed that decomposition was pH-dependent and occurred faster at neutral-basic conditions. It is more stable in cell culture medium containing 10% fetal calf serum and in human blood; less than 20% of curcumin decomposed within 1 h, and after incubation for 8 h, about 50% of curcumin is still remained. Trans-6-(4'-hydroxy-3'-methoxyphenyl)-2,4-dioxo-5-hexenal was predicted as major degradation product and vanillin, ferulic acid, feruloyl methane were identified as minor degradation products. The amount of vanillin increased with incubation time. read more read less

Topics:

Liposomal Curcumin (62%)62% related to the paper, Buffer solution (52%)52% related to the paper, Curcumin (51%)51% related to the paper, Ferulic acid (50%)50% related to the paper, Vanillin (50%)50% related to the paper
1,302 Citations
Journal Article DOI: 10.1016/J.JPBA.2006.04.002
Phenolics in cereals, fruits and vegetables: Occurrence, extraction and analysis
Marian Naczk1, Fereidoon Shahidi2

Abstract:

Consumption of plant foods, particularly fruits, vegetables and cereal grains is encouraged because they render beneficial health effects. Phenolics and polyphenolics are among the most desirable food bioactives because of their antioxidant activity, brought about by a number of pathways, or due to other mechanisms. The analy... Consumption of plant foods, particularly fruits, vegetables and cereal grains is encouraged because they render beneficial health effects. Phenolics and polyphenolics are among the most desirable food bioactives because of their antioxidant activity, brought about by a number of pathways, or due to other mechanisms. The analysis of phenolics and polyphenolics requires their extraction possible purification and structure elucidation. This overview provides a cursory account of the source, extraction and analysis of phenolics in fruits, vegetables and cereals. read more read less
1,130 Citations
Journal Article DOI: 10.1016/J.JPBA.2007.03.023
A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies.
Yves Roggo1, Pascal Chalus1, Lene Maurer1, Carmen Lema-Martinez1, Aurélie Edmond1, Nadine Jent1

Abstract:

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical ... Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories.This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications. read more read less
966 Citations
Journal Article DOI: 10.1016/S0731-7085(99)00272-1
Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research
Snezana Agatonovic-Kustrin1, R. Beresford1

Abstract:

Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from h... Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine and incorporate both literature-based and experimental data to solve problems. The various applications of ANNs can be summarised into classification or pattern recognition, prediction and modeling. Supervised 'associating networks can be applied in pharmaceutical fields as an alternative to conventional response surface methodology. Unsupervised feature-extracting networks represent an alternative to principal component analysis. Non-adaptive unsupervised networks are able to reconstruct their patterns when presented with noisy samples and can be used for image recognition. The potential applications of ANN methodology in the pharmaceutical sciences range from interpretation of analytical data, drug and dosage form design through biopharmacy to clinical pharmacy. read more read less

Topics:

Time delay neural network (65%)65% related to the paper, Learning rule (63%)63% related to the paper, Types of artificial neural networks (62%)62% related to the paper, Nervous system network models (62%)62% related to the paper, Physical neural network (62%)62% related to the paper
812 Citations
Journal Article DOI: 10.1016/S0731-7085(02)00047-X
Development of validated stability-indicating assay methods--critical review.

Abstract:

This write-up provides a review on the development of validated stability-indicating assay methods (SIAMs) for drug substances and products. The shortcomings of reported methods with respect to regulatory requirements are highlighted. A systematic approach for the development of stability-indicating methods is discussed. Crit... This write-up provides a review on the development of validated stability-indicating assay methods (SIAMs) for drug substances and products. The shortcomings of reported methods with respect to regulatory requirements are highlighted. A systematic approach for the development of stability-indicating methods is discussed. Critical issues related to development of SIAMs, such as separation of all degradation products, establishment of mass balance, stress testing of formulations, development of SIAMs for combination products, etc. are also addressed. The applicability of pharmacopoeial methods for the analysis of stability samples is discussed. The requirements of SIAMs for stability study of biotechnological substances and products are also touched upon. read more read less
641 Citations
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Frequently asked questions

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3. Can I cite my article in multiple styles in Journal of Pharmaceutical and Biomedical Analysis?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Pharmaceutical and Biomedical Analysis citation style.

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12. Is Journal of Pharmaceutical and Biomedical Analysis's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Pharmaceutical and Biomedical Analysis?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Pharmaceutical and Biomedical Analysis. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Pharmaceutical and Biomedical Analysis?

The 5 most common citation types in order of usage for Journal of Pharmaceutical and Biomedical Analysis are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Pharmaceutical and Biomedical Analysis?

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16. Can I download Journal of Pharmaceutical and Biomedical Analysis in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Pharmaceutical and Biomedical Analysis Endnote style according to Elsevier guidelines.

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