The Learning-Adapting-Leveling model: from theory to hypothesis of steps for implementation of basic genome-based evidence in personalized medicine

2013 ◽  
Vol 10 (7) ◽  
pp. 683-701 ◽  
Author(s):  
Jonathan A Lal ◽  
Anil Vaidya ◽  
Iñaki Gutiérrez-Ibarluzea ◽  
Hans-Peter Dauben ◽  
Angela Brand
Keyword(s):  
Personalized Medicine ◽  
Basic Genome

PRDM16 - A Novel Key Player in Personalized Medicine

2015 ◽  
Vol 63 (S 03) ◽  
Author(s):  
A. Arndt ◽  
M. Beerens ◽  
H. Kramer ◽  
S. Klaassen ◽  
C. MacRae
Keyword(s):  
Personalized Medicine

SAP: Personalized Medicine Forum

2016 ◽  
Vol 21 (09) ◽  
pp. 52-52
Keyword(s):  
Personalized Medicine

Die Digitalisierung und das Gesundheitswesen sind Partner, die es in Zukunft gemeinsam noch sehr weit bringen können – das ist die Botschaft des SAP Personalized Medicine Forum, das am 6. und 7. Juli in Bonn stattfand.

Clustering techniques for thyroid nodules malignancy inference in the era of personalized medicine

2020 ◽  
Author(s):  
Andrea Giani ◽  
de Souza Patricia Borges ◽  
Stefania Bartoletti ◽  
Flavio Morselli ◽  
Andrea Conti ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Thyroid Nodules ◽  
Clustering Techniques

Applying personalized medicine to adult severe asthma

2021 ◽  
Vol 42 (1) ◽  
pp. e8-e16 ◽  
Author(s):  
Angelica Tiotiu
Keyword(s):  
Personalized Medicine ◽  
Severe Asthma ◽  
Negative Impact ◽  
Target Therapy ◽  
Asthma Management ◽  
Future Research ◽  
Biologic Therapies ◽  
Eosinophilic Asthma ◽  
Definition Of ◽  
Structured Approach

Background: Severe asthma is a heterogeneous disease that consists of various phenotypes driven by different pathways. Associated with significant morbidity, an important negative impact on the quality of life of patients, and increased health care costs, severe asthma represents a challenge for the clinician. With the introduction of various antibodies that target type 2 inflammation (T2) pathways, severe asthma therapy is gradually moving to a personalized medicine approach. Objective: The purpose of this review was to emphasize the important role of personalized medicine in adult severe asthma management. Methods: An extensive research was conducted in medical literature data bases by applying terms such as “severe asthma” associated with “structured approach,” “comorbidities,” “biomarkers,” “phenotypes/endotypes,” and “biologic therapies.” Results: The management of severe asthma starts with a structured approach to confirm the diagnosis, assess the adherence to medications and identify confounding factors and comorbidities. The definition of phenotypes or endotypes (phenotypes defined by mechanisms and identified through biomarkers) is an important step toward the use of personalized medicine in asthma. Severe allergic and nonallergic eosinophilic asthma are two defined T2 phenotypes for which there are efficacious targeted biologic therapies currently available. Non-T2 phenotype remains to be characterized, and less efficient target therapy exists. Conclusion: Despite important progress in applying personalized medicine to severe asthma, especially in T2 inflammatory phenotypes, future research is needed to find valid biomarkers predictive for the response to available biologic therapies to develop more effective therapies in non-T2 phenotype.

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