Literature DB >> 26781205

Enabling personalized cancer medicine decisions: The challenging pharmacological approach of PBPK models for nanomedicine and pharmacogenomics (Review).

Ioannis S Vizirianakis1, George A Mystridis1, Konstantinos Avgoustakis2, Dimitrios G Fatouros3, Marios Spanakis4.   

Abstract

The existing tumor heterogeneity and the complexity of cancer cell biology critically demand powerful translational tools with which to support interdisciplinary efforts aiming to advance personalized cancer medicine decisions in drug development and clinical practice. The development of physiologically based pharmacokinetic (PBPK) models to predict the effects of drugs in the body facilitates the clinical translation of genomic knowledge and the implementation of in vivo pharmacology experience with pharmacogenomics. Such a direction unequivocally empowers our capacity to also make personalized drug dosage scheme decisions for drugs, including molecularly targeted agents and innovative nanoformulations, i.e. in establishing pharmacotyping in prescription. In this way, the applicability of PBPK models to guide individualized cancer therapeutic decisions of broad clinical utility in nanomedicine in real-time and in a cost-affordable manner will be discussed. The latter will be presented by emphasizing the need for combined efforts within the scientific borderlines of genomics with nanotechnology to ensure major benefits and productivity for nanomedicine and personalized medicine interventions.

Entities:  

Mesh:

Year:  2016        PMID: 26781205     DOI: 10.3892/or.2016.4575

Source DB:  PubMed          Journal:  Oncol Rep        ISSN: 1021-335X            Impact factor:   3.906


  8 in total

Review 1.  Dynamical systems approaches to personalized medicine.

Authors:  Jacob D Davis; Carla M Kumbale; Qiang Zhang; Eberhard O Voit
Journal:  Curr Opin Biotechnol       Date:  2019-04-09       Impact factor: 9.740

Review 2.  Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine.

Authors:  Clara Hartmanshenn; Megerle Scherholz; Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-09-19       Impact factor: 2.745

3.  Pharmacological Development of Target-Specific Delocalized Lipophilic Cation-Functionalized Carboranes for Cancer Therapy.

Authors:  Eirini D Tseligka; Aikaterini Rova; Elsa P Amanatiadou; Gianpiero Calabrese; John Tsibouklis; Dimitrios G Fatouros; Ioannis S Vizirianakis
Journal:  Pharm Res       Date:  2016-04-26       Impact factor: 4.200

4.  Constraint-based perturbation analysis with cluster Newton method: a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model.

Authors:  Shun Asami; Daisuke Kiga; Akihiko Konagaya
Journal:  BMC Syst Biol       Date:  2017-12-21

Review 5.  Nursing Personnel in the Era of Personalized Healthcare in Clinical Practice.

Authors:  Marios Spanakis; Athina E Patelarou; Evridiki Patelarou
Journal:  J Pers Med       Date:  2020-06-29

Review 6.  The Role of in silico Research in Developing Nanoparticle-Based Therapeutics.

Authors:  Migara Kavishka Jayasinghe; Chang Yu Lee; Trinh T T Tran; Rachel Tan; Sarah Min Chew; Brendon Zhi Jie Yeo; Wen Xiu Loh; Marco Pirisinu; Minh T N Le
Journal:  Front Digit Health       Date:  2022-03-16

Review 7.  Developing New Treatments for COVID-19 through Dual-Action Antiviral/Anti-Inflammatory Small Molecules and Physiologically Based Pharmacokinetic Modeling.

Authors:  Panagiotis Zagaliotis; Anthi Petrou; George A Mystridis; Athina Geronikaki; Ioannis S Vizirianakis; Thomas J Walsh
Journal:  Int J Mol Sci       Date:  2022-07-20       Impact factor: 6.208

8.  Physiologically Based Pharmacokinetic Modelling and Simulation to Predict the Plasma Concentration Profile of Doxorubicin.

Authors:  George A Mystridis; Georgios C Batzias; Ioannis S Vizirianakis
Journal:  Pharmaceutics       Date:  2022-02-28       Impact factor: 6.321

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.