Incomplete understanding of the pathophysiology of neurodegenerative chronic diseases (eg, Alzheimer’s) has hindered the development of effective drug treatments. In particular, considering the impact of aging is important when analyzing clinical data derived from a geriatric population.
Physiological modeling and simulation including brain physiology (and/or pharmacology) have typically assumed that the brain has a constant volume. However, several studies have shown that the volume of the brain varies with age. It increases in volume during development with a peak around age 20 and then shows a slow and steady decrease over time. Quantifying the changes in brain volume with age is important for estimating the concentration of biomarkers in the brain, eg, amyloid beta, cholesterol, etc.
Quantitative systems pharmacology (QSP) models combine computational modeling and experimental data to examine the relationships between a drug, the biological system, and the disease process. This emerging discipline integrates quantitative drug data with knowledge of its mechanism of action. QSP may also be able to take advantage of the enormous amounts of information we now have access to, including genomics and proteomic data.
QSP models predict how drugs modify cellular networks in space and time and how they impact and are impacted by human pathophysiology. Additionally, QSP facilitates evaluating complex, heterogeneous diseases such as cancer, immunological, metabolic, and CNS diseases that will probably require combination therapies to fully control them.
In this webinar, Dr. Cesar Pichardo will explain how he:
- Leveraged QSP to assess the impact of brain volume changes on estimating biomarker concentrations
- Compared the results of a model with variable brain volume with a model using constant brain volume
- Evaluated the effect of variability in brain volume changes in a given population on estimates of biomarker concentrations
Attend this webinar to learn why many major pharma organizations are investing in QSP for its potential to improve pharma R&D productivity.
About Our Speaker
Cesar Pichardo is currently a Principal Scientist at Certara, creating quantitative systems pharmacology (QSP) models and solutions for drug discovery. He earned his first degree in Chemical Engineering (MEng) and a MSc in Systems Engineering (Control Theory) from Simon Bolivar University (Venezuela) and got his PhD in Applied Mathematics from Ecole Centrale de Lille (France). He has spent the last 15 years developing biological, physiological and medical models for lifestyle interventions, drug development, mortality risk, and actuarial science.
He has worked as a senior researcher in both academia (eg, University College London, University of Sheffield, INSA de Lyon) and industry (Pfizer, XenologiQ).