| Title |
General Framework for the Quantitative Prediction of CYP3A4-Mediated Oral Drug Interactions Based on the AUC Increase by Coadministration of Standard Drugs
|
|---|---|
| Published in |
Clinical Pharmacokinetics, September 2012
|
| DOI | 10.2165/00003088-200746080-00005 |
| Pubmed ID | |
| Authors |
Yoshiyuki Ohno, Akihiro Hisaka, Hiroshi Suzuki |
| Abstract |
Cytochrome P450 (CYP) 3A4 is the most prevalent metabolising enzyme in the human liver and is also a target for various drug interactions of significant clinical concern. Even though there are numerous reports regarding drug interactions involving CYP3A4, it is far from easy to estimate all potential interactions, since too many drugs are metabolised by CYP3A4. For this reason, a comprehensive framework for the prediction of CYP3A4-mediated drug interactions would be of considerable clinical importance. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 25% |
| Unknown | 6 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 1% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Russia | 1 | 1% |
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 86 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 28% |
| Other | 10 | 11% |
| Student > Ph. D. Student | 10 | 11% |
| Student > Master | 7 | 8% |
| Student > Bachelor | 7 | 8% |
| Other | 19 | 21% |
| Unknown | 13 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 36 | 39% |
| Pharmacology, Toxicology and Pharmaceutical Science | 14 | 15% |
| Agricultural and Biological Sciences | 10 | 11% |
| Chemistry | 7 | 8% |
| Nursing and Health Professions | 1 | 1% |
| Other | 8 | 9% |
| Unknown | 16 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 April 2024.
All research outputs
#3,560,742
of 25,371,288 outputs
Outputs from Clinical Pharmacokinetics
#189
of 1,602 outputs
Outputs of similar age
#25,614
of 191,398 outputs
Outputs of similar age from Clinical Pharmacokinetics
#75
of 587 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,602 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 191,398 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 587 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.