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return kwic search for different out of >500 occurrences
683276 occurrences (No.7 in the rank) during 5 years in the PubMed. [no cache] 500 found

166) In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules.

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PMID:24134068 DOI:10.1111/bcp.12258

2015 British journal of clinical pharmacology

* Population pharmacokinetic-pharmacodynamic modelling in oncology: a tool for predicting clinical response.

- In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic-pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed.

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(1)21 from	(18)3 amounts	(35)2 compared	(52)2 origins
(2)15 types	(19)3 aspects	(36)2 dietary	(53)2 output
(3)10 between	(20)3 cell	(37)2 diseases	(54)2 pHs
(4)9 doses	(21)3 degrees	(38)2 dosing	(55)2 patterns
(5)7 concentrations	(22)3 effects	(39)2 ethnic	(56)2 perspectives
(6)6 time	(23)3 for	(40)2 flow	(57)2 protocols
(7)5 in	(24)3 health	(41)2 frequencies	(58)2 range
(8)5 levels	(25)3 mechanisms	(42)2 gene	(59)2 regions
(9)4 null	(26)3 parts	(43)2 genes	(60)2 scenarios
(10)4 areas	(27)3 roles	(44)2 genetic	(61)2 sensory
(11)4 combinations	(28)3 species	(45)2 human	(62)2 surface
(12)4 components	(29)3 ways	(46)2 indicators	(63)2 taxa
(13)4 groups	(30)2 abutments	(47)2 internal-cone	(64)2 than
(14)4 methods	(31)2 and	(48)2 laser	(65)2 therapeutic
(15)4 stages	(32)2 approaches	(49)2 masking	(66)2 tissues
(16)4 tilt	(33)2 bleaching	(50)2 materials	(67)2 versions
(17)3 adhesive	(34)2 changes	(51)2 molecular	(68)2 views

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--- WordNet output for different --- =>いろいろな, 違った, 異なった, 様々の, 種々の, 異なる, 変わった Overview of adj different The adj different has 5 senses (first 4 from tagged texts) 1. (88) different -- (unlike in nature or quality or form or degree; "took different approaches to the problem"; "came to a different conclusion"; "different parts of the country"; "on different sides of the issue"; "this meeting was different from the earlier one") 2. (41) different -- (distinctly separate from the first; "that's another (or different) issue altogether") 3. (2) different -- (differing from all others; not ordinary; "advertising that strives continually to be different"; "this new music is certainly different but I don't really like it") 4. (1) unlike, dissimilar, different -- (marked by dissimilarity; "for twins they are very unlike"; "people are profoundly different") 5. different -- (distinct or separate; "each interviewed different members of the community") --- WordNet end ---