Using Modeling and Simulation to Combat Tuberculosis: A Global Health Priority

Speaker(s): Klaus Romero
Date: June 22, 2017
Time: 11 am ET
Duration: 1 hour

Tuberculosis (TB) is a deadly disease, a principal cause of death by infectious disease, and the leading cause of mortality for HIV+ patients. Most available TB drugs are more than 40 years old, have significant side effects and drug interactions, and require a long treatment period. Furthermore, these drugs are becoming less effective as TB strains grow increasingly drug resistant. New tools are desperately needed to help TB drug developers combat this deadly disease.

The Critical Path to TB Drug Regimens (CPTR) Initiative, in partnership with Certara, developed a TB-specific set of lung and granuloma models, together with a library of drug and metabolite files. These models and library files are implemented in Certara’s Simcyp Simulator physiologically-based pharmacokinetic (PBPK) platform, which helps optimize the design of clinical studies for multiple indications and has been widely adopted by industry and regulators.

Attend this webinar with C-Path’s Dr. Klaus Romero to learn how they integrated these components into the latest version of the Simcyp Simulator to establish a robust resource that will help development teams and regulators evaluate the safety and efficacy of novel anti-TB drug regimens.

About Our Speaker

Dr. Klaus Romero is a clinical pharmacologist and epidemiologist by training, with 12 years of experience in clinical research. He is a fellow of the American College of Clinical Pharmacology, a founding member of the International Society of Pharmacometrics, as well as a member of the American Society for Clinical Pharmacology and Therapeutics and the International Society for Pharmacoepidemiology. He has conducted research on endemic channels for non-steroidal anti-inflammatory drug-related gastropathy, antibiotic-related dysglycemia, drug-induced QT prolongation, pharmacoepidemiology, and patient education. Dr. Romero has been with C-Path since January 1, 2008, where he has led clinical pharmacology, pharmacoepidemiology, and modeling and simulation projects for the Coalition Against Major Diseases, the Polycystic Kidney Disease Outcomes Consortium, and the Critical Path to TB Drug Regimens Consortium, achieving major milestones such as the first regulatory endorsement by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) of a clinical trial simulation tool for mild and moderate Alzheimer’s Disease. He is fluent in English, Spanish, German, and Portuguese, and has published in the areas of clinical pharmacology, pharmacometrics, cardiovascular drug safety, and pharmacoepidemiology.


Using Model Reduction to Bridge the QSP-Pharmacometrics Divide

Speaker(s): Tom Snowden
Date: July 26, 2017
Time: 11 am EDT
Duration: 1 hour

One of the biggest challenges – and, hence, the biggest opportunity for quantitative systems pharmacology (QSP) – is drug attrition in Phase 2 clinical trials. Investigational medicines are usually tested for the first time in patients in Phase 2 clinical trials. This is the point when many drug programs fail. In fact, approximately 80 percent of new drugs that move into Phase 2 fail. The major reason for this failure is that the drug doesn’t show efficacy or is not safe.

QSP is a relatively new discipline with enormous potential to improve pharma R&D productivity. It provides a framework for constructing mechanistic, mathematical models of drug action in silico. This integrative discipline incorporates pharmacometric, pharmacokinetic/pharmacodynamic (PK/PD), and physiologically-based PK (PBPK) approaches with systems biology models of biological and biochemical processes. Such models can inform the mechanisms of drug efficacy and safety, as well as confirm the ‘drugability’ of proposed targets.

Describing biological systems at this level of detail invokes the issue of model complexity. QSP models are generally too large to be validated or fit in a traditional sense and they can become intractable to standard methods of analysis or even to the modeler’s own intuition. Model reduction can alleviate these issues of complexity by eliminating portions of a system that have minimal effect upon the outputs or time-scales of interest. Such approaches yield simplified models that still provide accurate predictions. By shrinking a model’s parameter space, increasing computational speed and reducing the number of modeled state-variables, reduction techniques can help bridge the gap between pre-clinical and clinical QSP applications.

In this webinar, Dr. Tom Snowden will demonstrate:

  • Why reduction methods are a potent and necessary tool in the modeler’s arsenal;
  • How reduction methods can be applied to QSP models; and,
  • How model reduction can be used to extract scientific and business insights from complex models.

About Our Speaker

Tom Snowden received his PhD in applied mathematics and quantitative systems pharmacology from the University of Reading in 2015. He was then awarded and completed an EPSRC doctoral prize fellowship at the university, continuing his research at the interface of mathematics and pharmacology. In October 2016, Tom joined Certara QSP as a research scientist working on a range of QSP consultancy projects.

Learn More