Literature DB >> 20967521

Prediction of exposure-response relationships to support first-in-human study design.

John P Gibbs1.   

Abstract

In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical E (max) models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.

Entities:  

Mesh:

Year:  2010        PMID: 20967521      PMCID: PMC2976982          DOI: 10.1208/s12248-010-9236-7

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  61 in total

1.  General pharmacokinetic model for drugs exhibiting target-mediated drug disposition.

Authors:  D E Mager; W J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-12       Impact factor: 2.745

Review 2.  Immunogenicity of therapeutic monoclonal antibodies.

Authors:  Charles Pendley; Allen Schantz; Carrie Wagner
Journal:  Curr Opin Mol Ther       Date:  2003-04

Review 3.  Diversity of mechanism-based pharmacodynamic models.

Authors:  Donald E Mager; Elzbieta Wyska; William J Jusko
Journal:  Drug Metab Dispos       Date:  2003-05       Impact factor: 3.922

Review 4.  Can the pharmaceutical industry reduce attrition rates?

Authors:  Ismail Kola; John Landis
Journal:  Nat Rev Drug Discov       Date:  2004-08       Impact factor: 84.694

5.  Obstacles and opportunities in translational research.

Authors:  Heidi Hörig; Elizabeth Marincola; Francesco M Marincola
Journal:  Nat Med       Date:  2005-07       Impact factor: 53.440

6.  Efficacy and concentration-response of murine anti-VEGF monoclonal antibody in tumor-bearing mice and extrapolation to humans.

Authors:  J Mordenti; K Thomsen; V Licko; H Chen; Y G Meng; N Ferrara
Journal:  Toxicol Pathol       Date:  1999 Jan-Feb       Impact factor: 1.902

Review 7.  On the prediction of the human response: a recycled mechanistic pharmacokinetic/pharmacodynamic approach.

Authors:  Guy M L Meno-Tetang; Philip J Lowe
Journal:  Basic Clin Pharmacol Toxicol       Date:  2005-03       Impact factor: 4.080

8.  (2R)-4-oxo-4-[3-(trifluoromethyl)-5,6-dihydro[1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-1-(2,4,5-trifluorophenyl)butan-2-amine: a potent, orally active dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes.

Authors:  Dooseop Kim; Liping Wang; Maria Beconi; George J Eiermann; Michael H Fisher; Huaibing He; Gerard J Hickey; Jennifer E Kowalchick; Barbara Leiting; Kathryn Lyons; Frank Marsilio; Margaret E McCann; Reshma A Patel; Aleksandr Petrov; Giovanna Scapin; Sangita B Patel; Ranabir Sinha Roy; Joseph K Wu; Matthew J Wyvratt; Bei B Zhang; Lan Zhu; Nancy A Thornberry; Ann E Weber
Journal:  J Med Chem       Date:  2005-01-13       Impact factor: 7.446

9.  Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents.

Authors:  Monica Simeoni; Paolo Magni; Cristiano Cammia; Giuseppe De Nicolao; Valter Croci; Enrico Pesenti; Massimiliano Germani; Italo Poggesi; Maurizio Rocchetti
Journal:  Cancer Res       Date:  2004-02-01       Impact factor: 12.701

Review 10.  Of mice and men: values and liabilities of the athymic nude mouse model in anticancer drug development.

Authors:  L R Kelland
Journal:  Eur J Cancer       Date:  2004-04       Impact factor: 9.162

View more
  11 in total

1.  Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients.

Authors:  A Thorsted; P Thygesen; H Agersø; T Laursen; M Kreilgaard
Journal:  Br J Pharmacol       Date:  2016-04-21       Impact factor: 8.739

2.  A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.

Authors:  Yadir A Guerrero; Diti Desai; Connor Sullivan; Erick Kindt; Mary E Spilker; Tristan S Maurer; Deepak E Solomon; Derek W Bartlett
Journal:  AAPS J       Date:  2020-03-02       Impact factor: 4.009

Review 3.  Modeling and predicting clinical efficacy for drugs targeting the tumor milieu.

Authors:  Mallika Singh; Napoleone Ferrara
Journal:  Nat Biotechnol       Date:  2012-07-10       Impact factor: 54.908

Review 4.  Antiretroviral pharmacology in mucosal tissues.

Authors:  Corbin G Thompson; Myron S Cohen; Angela D M Kashuba
Journal:  J Acquir Immune Defic Syndr       Date:  2013-07       Impact factor: 3.731

5.  On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.

Authors:  Nahor Haddish-Berhane; Dhaval K Shah; Dangshe Ma; Mauricio Leal; Hans-Peter Gerber; Puja Sapra; Hugh A Barton; Alison M Betts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-08-10       Impact factor: 2.745

6.  A pre-clinical quantitative model predicts the pharmacokinetics/pharmacodynamics of an anti-BDCA2 monoclonal antibody in humans.

Authors:  Konstantinos Biliouris; Ivan Nestorov; Himanshu Naik; David Dai; Guangqing Xiao; Qin Wang; Alex Pellerin; Dania Rabah; Lawrence J Lesko; Mirjam N Trame
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-10-30       Impact factor: 2.745

7.  Prediction of clinical pharmacokinetics of AMG 181, a human anti-α 4 β 7 monoclonal antibody for treating inflammatory bowel diseases.

Authors:  Hong Li; Kathleen Köck; John A Wisler; William A Rees; Peter J Prince; Kai O Reynhardt; Hailing Hsu; Zhigang Yu; Dominic C Borie; David H Salinger; Wei-Jian Pan
Journal:  Pharmacol Res Perspect       Date:  2014-12-09

Review 8.  Immunotherapy and Novel Combinations in Oncology: Current Landscape, Challenges, and Opportunities.

Authors:  K M Morrissey; T M Yuraszeck; C-C Li; Y Zhang; S Kasichayanula
Journal:  Clin Transl Sci       Date:  2016-03-30       Impact factor: 4.689

9.  Population Pharmacokinetics and Pharmacodynamics of GSK961081 (Batefenterol), a Muscarinic Antagonist and β2-Agonist, in Moderate-to-Severe COPD Patients: Substudy of a Randomized Trial.

Authors:  Claire L Ambery; Pascal Wielders; Andrea Ludwig-Sengpiel; Robert Chan; John H Riley
Journal:  Drugs R D       Date:  2015-09

10.  Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations.

Authors:  D R Mould; A-C Walz; T Lave; J P Gibbs; B Frame
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-01-21
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.