Recent projects

Goals:

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1. Identify genetic biomarkers associated with rheumatoid arthritis.

2. Study the genetic pathways and inflammatory processes involved in the disease.

3. Analyze the individual response to different therapies and medications.

4. Develop personalized approaches to the treatment and management of rheumatoid arthritis.

 

Outstanding results:

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• Identification of genetic variants associated with an increased risk of developing rheumatoid arthritis.

• Characterization of genetic profiles and gene expression that differentiate between subtypes of the disease and help to understand their heterogeneity.

• Discovery of new inflammatory pathways and potential therapeutic targets for the treatment of rheumatoid arthritis.

• Validation of the clinical utility of genetic biomarkers in predicting the response to available treatments.

 

Collaborations:

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• Virgen de la Macarena University Hospital

• Pfizer 

• Healthcare and patients with Rheumatoid Arthritis.

Cancer is a complex and heterogeneous disease that requires personalized treatment approaches. In collaboration with different institutions, Pharmacogenomics research projects have been carried out to analyze the genetic polymorphisms associated with the response to chemotherapy drugs, with the aim of improving the efficacy and reducing the adverse effects of cancer treatments.

 

Goals:

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1. Identify genetic polymorphisms that influence the response to drugs used in chemotherapy.

2. Study the molecular mechanisms underlying the variability in the response to cancer treatments.

3. Develop predictive models based on genomic analysis to improve the selection of more effective and personalized therapies.

4. Contribute to the development of precision medicine strategies in cancer treatment.

 

Outstanding results:

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• Identification of genetic variants associated with a favorable or unfavorable response to certain drugs used in chemotherapy.

• Establishment of correlations between genetic profiles and the efficacy of different anticancer therapies.

• Discovery of genetic biomarkers that allow a more precise selection of patients who will benefit from certain treatments.

• Development of algorithms and genomic analysis tools to predict the response to drugs and optimize the choice of treatment.

• Participation in clinical trials and collaboration with oncologists and genetic specialists to apply the findings in clinical practice and improve patient outcomes.

 

Collaborations:

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• Research Centers 

• Oncology Institutions.

• Patients undergoing chemotherapy 

• Pharmacists and specialists in clinical oncology.