Research Focus Areas

My research spans clinical pharmacology, epidemiology, and hematological oncology with a focus on improving patient outcomes through data-driven approaches.

Current Research Projects

Pharmacogenetics Implementation in Clinical Practice 

<div class="project-status">Status: <span class="badge badge-primary">Active</span></div>
<div class="project-timeline">2021 - Present</div>
<p>This project focuses on translating pharmacogenetic findings into clinical practice to enable personalized medication dosing. We are developing implementation strategies, clinical decision support tools, and educational resources for healthcare providers to effectively utilize genetic information in prescribing decisions.</p>
<h4>Key Objectives:</h4>
<ul>
  <li>Evaluate the clinical utility of pharmacogenetic testing in selected drug-gene pairs</li>
  <li>Develop and validate clinical decision support algorithms</li>
  <li>Assess healthcare provider adoption and patient outcomes</li>
</ul>

PreVentACall Randomized Clinical Trial 

<div class="project-status">Status: <span class="badge badge-primary">Active</span></div>
<div class="project-timeline">2022 - Present</div>
<p>The PreVentACall trial combines infection risk prediction with disease progression models to improve outcomes for patients with chronic lymphocytic leukemia (CLL). This innovative approach uses machine learning algorithms to identify high-risk patients and implement targeted interventions.</p>
<h4>Key Objectives:</h4>
<ul>
  <li>Validate a combined risk prediction model for infection and disease progression</li>
  <li>Evaluate the effectiveness of targeted preventive measures in high-risk patients</li>
  <li>Assess the impact on quality of life and healthcare resource utilization</li>
</ul>

National Hospital Medication Register Assessment 

<div class="project-status">Status: <span class="badge badge-success">Completed</span></div>
<div class="project-timeline">2021 - 2022</div>
<p>This project evaluated the Danish National Hospital Medication Register using immunotherapy as a case study. The aim was to assess data quality, completeness, and utility for research purposes, providing insights for future register-based studies.</p>
<h4>Key Findings:</h4>
<ul>
  <li>Identified patterns of data quality and completeness across different hospitals</li>
  <li>Developed validation algorithms to enhance data reliability</li>
  <li>Created recommendations for researchers using medication register data</li>
</ul>

Research Methods & Expertise

<h4><i class="fa fa-bar-chart"></i> Statistical Analysis</h4>
<ul>
  <li>Survival analysis</li>
  <li>Generalized additive models</li>
  <li>Time series analysis</li>
  <li>Propensity score methods</li>
</ul>
<h4><i class="fa fa-code"></i> Data Science</h4>
<ul>
  <li>R programming (data.table, heaven)</li>
  <li>Machine learning algorithms</li>
  <li>Predictive modeling</li>
  <li>Data visualization</li>
</ul>
<h4><i class="fa fa-database"></i> Data Sources</h4>
<ul>
  <li>Danish national health registers</li>
  <li>Clinical databases</li>
  <li>Electronic health records</li>
  <li>Biobank samples</li>
</ul>
<h4><i class="fa fa-flask"></i> Clinical Research</h4>
<ul>
  <li>Randomized controlled trials</li>
  <li>Cohort studies</li>
  <li>Case-control studies</li>
  <li>Pharmacokinetic studies</li>
</ul>

Research Impact

My research on infection risk in CLL patients has identified patterns of increased susceptibility to specific pathogens and has led to improved risk stratification models. These findings have influenced clinical practice guidelines and inspired multiple follow-up studies.

The machine learning models developed for predicting disease progression have demonstrated improved accuracy compared to traditional methods, potentially allowing for more personalized treatment approaches and better resource allocation.

Collaborations

I collaborate with researchers and clinicians across multiple institutions, including:

If you’re interested in potential research collaborations, please contact me.