Dr. Paul C. Guest, Ph.D, is a scientific researcher/writer with 38 years of experience in the fields of metabolic and neurological disorders. This includes experience in both academia and the pharmaceutical industry with the majority of time spent at the University of Cambridge and Merck Sharp & Dohme in the United Kingdom. He is also affiliated with the University of Campinas in Sao Paulo Brazil and Otto-von-Guericke-University in Magdeburg Germany, still focused on advancing the field of biomarkers for neurological disorders such as schizophrenia, age-related diseases such as diabetes, cancer, cardiovascular disorders, sarcopenia and Alzheimer's disease, and more recently on infectious diseases such as COVID-19. 

1. LC-MS Analysis of Serum and Plasma to Identify Circulating Biomarkers of SARS-CoV-2 Infection

2. Mass Spectrometry Analyses Combined with Machine Learning to Identify Robust Biomarkers for COVID-19 Disease

3. Selective Reaction Monitoring Mass Spectrometry Methods for Establishing a Panel of COVID-19 Biomarkers

4. Chip-Based Assays for Multiplexed Analysis of SARS-CoV-2 Viral Infection

5. Screening of Metabolic Profiles of Serum Metabolites in COVID-19 Patients

6. Proteomic Techniques in Models of SARS-CoV-2 Infection

7. Multiplex Immunoassay Approaches to Study the Cytokine Storm Effect

8. Proteomic Methods for the Study of Organ Failure Associated with Severe COVID-19 Disease Courses

9. Screening of Natural Products for COVID-19 Treatment using Multiplex Biomarker Readouts

10. Multiplex Lateral Flow Antigen and Antibody Tests for Diagnosis and Surveillance of COVID-19 Disease

12. Multiplex Quantitative PCR Approaches for Diagnosis and Tracking of SARS-CoV-2 Variants

13. Lipidomic Analysis of Fatty Acids as Potential New Biomarkers and Targets for Improved Treatment of COVID-19 Disease

14. Multiplex Omic Methods for Screening and Triaging COVID-19 Patients According to Disease Severity

15. Point-of-Care Techniques to Establish Risk of COVID-19 Disease Outcomes

17. The Combined use of Artificial Intelligence and Circulating Molecular Profiles to Identify Prognostic Markers of COVID-19 Disease