Literature DB >> 3072349

Population pharmacokinetics.

T M Ludden1.   

Abstract

The major strength of the population analysis approach is that useful information can be extracted from sparse data using blood samples and pharmacologic monitoring during routine safety and efficacy studies conducted during the development of a drug product. The results of these analyses may lead to integrated pharmacokinetic-pharmacodynamic models that can aid the clinician during the initiation and adjustment of therapeutic regimens. In some cases it may be possible to develop closed-loop control systems that monitor a drug concentration or a response and automatically adjust the drug administration rate. Overall, an increase in the safety and efficiency of drug use can be anticipated.

Mesh:

Year:  1988        PMID: 3072349     DOI: 10.1002/j.1552-4604.1988.tb05714.x

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  11 in total

1.  Population Pharmacokinetics of Diazoxide in Children with Hyperinsulinemic Hypoglycemia.

Authors:  Rika Kizu; Kazuko Nishimura; Reiko Sato; Kenjiro Kosaki; Toshiaki Tanaka; Yusuke Tanigawara; Tomonobu Hasegawa
Journal:  Horm Res Paediatr       Date:  2017-07-14       Impact factor: 2.852

Review 2.  Clinical pharmacology = disease progression + drug action.

Authors:  Nick Holford
Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

3.  Characterization of AUCs from sparsely sampled populations in toxicology studies.

Authors:  S M Pai; S H Fettner; G Hajian; M N Cayen; V K Batra
Journal:  Pharm Res       Date:  1996-09       Impact factor: 4.200

4.  Prediction of diltiazem plasma concentration curves from limited measurements using compliance data.

Authors:  A Rubio; C Cox; M Weintraub
Journal:  Clin Pharmacokinet       Date:  1992-03       Impact factor: 6.447

5.  Pharmacokinetics of teriparatide (rhPTH[1-34]) and calcium pharmacodynamics in postmenopausal women with osteoporosis.

Authors:  Julie Satterwhite; Michael Heathman; Paul D Miller; Fernando Marín; Emmett V Glass; Harald Dobnig
Journal:  Calcif Tissue Int       Date:  2010-10-16       Impact factor: 4.333

Review 6.  Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective.

Authors:  E Samara; R Granneman
Journal:  Clin Pharmacokinet       Date:  1997-04       Impact factor: 6.447

7.  Comparison of population pharmacokinetic models for gentamicin in spinal cord-injured and able-bodied patients.

Authors:  T M Gilman; S R Brunnemann; J L Segal
Journal:  Antimicrob Agents Chemother       Date:  1993-01       Impact factor: 5.191

8.  Mitoxantrone, etoposide, and cytarabine with or without valspodar in patients with relapsed or refractory acute myeloid leukemia and high-risk myelodysplastic syndrome: a phase III trial (E2995).

Authors:  Peter L Greenberg; Sandra J Lee; Ranjana Advani; Martin S Tallman; Branimir I Sikic; Louis Letendre; Kathleen Dugan; Bert Lum; David L Chin; Gordon Dewald; Elisabeth Paietta; John M Bennett; Jacob M Rowe
Journal:  J Clin Oncol       Date:  2004-03-15       Impact factor: 44.544

9.  Pharmacokinetic/Pharmacodynamic Modeling of the PDE4 Inhibitor TAK-648 in Type 2 Diabetes: Early Translational Approaches for Human Dose Prediction.

Authors:  N Plock; S Vollert; M Mayer; G Hanauer; G Lahu
Journal:  Clin Transl Sci       Date:  2017-01-15       Impact factor: 4.689

10.  A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters.

Authors:  Xiuqing Zhu; Wencan Huang; Haoyang Lu; Zhanzhang Wang; Xiaojia Ni; Jinqing Hu; Shuhua Deng; Yaqian Tan; Lu Li; Ming Zhang; Chang Qiu; Yayan Luo; Hongzhen Chen; Shanqing Huang; Tao Xiao; Dewei Shang; Yuguan Wen
Journal:  Sci Rep       Date:  2021-03-10       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.