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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Barbolosi, Dominique Ciccolini, Joseph Lacarelle, Bruno Barlési, Fabrice André, Nicolas |
| Description | Country affiliation: France Author Affiliation: Barbolosi D ( SMARTc Unit, Aix Marseille Université, INSERM, CRO2 UMR_S 911, Marseille 13005, France.); Ciccolini J ( SMARTc Unit, Aix Marseille Université, INSERM, CRO2 UMR_S 911, Marseille 13005, France.); Lacarelle B ( SMARTc Unit, Aix Marseille Université, INSERM, CRO2 UMR_S 911, Marseille 13005, France.); Barlési F ( SMARTc Unit, Aix Marseille Université, INSERM, CRO2 UMR_S 911, Marseille 13005, France.); André N ( Multidisciplinary Oncology Unit, Nord University Hospital of Marseille, Assistance Publique - Hôpitaux de Marseille (AP-HM), Marseille 13000, France.) |
| Abstract | Computational oncology is a generic term that encompasses any form of computer-based modelling relating to tumour biology and cancer therapy. Mathematical modelling can be used to probe the pharmacokinetics and pharmacodynamics relationships of the available anticancer agents in order to improve treatment. As a result of the ever-growing numbers of druggable molecular targets and possible drug combinations, obtaining an optimal toxicity-efficacy balance is an increasingly complex task. Consequently, standard empirical approaches to optimizing drug dosing and scheduling in patients are now of limited utility; mathematical modelling can substantially advance this practice through improved rationalization of therapeutic strategies. The implementation of mathematical modelling tools is an emerging trend, but remains largely insufficient to meet clinical needs; at the bedside, anticancer drugs continue to be prescribed and administered according to standard schedules. To shift the therapeutic paradigm towards personalized care, precision medicine in oncology requires powerful new resources for both researchers and clinicians. Mathematical modelling is an attractive approach that could help to refine treatment modalities at all phases of research and development, and in routine patient care. Reviewing preclinical and clinical examples, we highlight the current achievements and limitations with regard to computational modelling of drug regimens, and discuss the potential future implementation of this strategy to achieve precision medicine in oncology. |
| File Format | HTM / HTML |
| ISSN | 17594774 |
| Issue Number | 4 |
| Volume Number | 13 |
| e-ISSN | 17594782 |
| Journal | Nature Reviews Clinical Oncology |
| Language | English |
| Publisher | Nature Publishing Group |
| Publisher Date | 2016-04-01 |
| Publisher Place | Great Britain (UK) |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Discipline Oncology Antineoplastic Agents Pharmacology Therapeutic Use Medical Informatics Methods Models, Theoretical Neoplasms Drug Therapy Individualized Medicine Antineoplastic Combined Chemotherapy Protocols Adverse Effects Drug Monitoring Humans Journal Article Research Support, Non-u.s. Gov't Review |
| Content Type | Text |
| Resource Type | Article |
| Subject | Oncology |
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