Ryad Ghanam

Optimal Treatment Combination while Controlling for Patient Safety

Ryad Ghanam

VCUarts Qatar

raghanam@vcu.edu

Edward L. Boone

Physicians are often confronted with treating diseases, using a simultaneous administration of several medicines to obtain the desired outcome.  However, many of these medicines have adverse side effects that must be managed by the physician to ensure the safety of the patient, as well as promote treatment compliance to the treatment regime. An example of this is hypertension (affecting more than 30% of the Qatari population) that is often treated with a combination of an angiotensin converting enzyme inhibitor (ACEI) and a calcium channel blocker (CCB). Currently, physicians have no rigorous systematic data-based approach to determine an optimal combination of medicines; instead, they often use a recursive approach of adjusting the dosages of each of the medicines until a satisfactory combination is achieved. No statistical methodology exists that allows for researchers or physicians to estimate the optimal combination of medicines to treat the disease, while controlling for adverse effects. In this presentation, we will show a new statistical methodology to address this problem in both the linear and non-linear cases. The linear case is where the treatments may only have an additive effect and the non-linear case allows for interaction, antagonistic as well as synergistic effects. This Bayesian methodology will utilize Markov chain Monte Carlo (MCMC) techniques to fit toxicology and treatment models to clinical data, which will result in a large number of samples from the posterior distribution of model parameters. These posterior samples will be used to form instances of mathematical programs to be solved using techniques, such as linear programming and non-linear programming, resulting in a distribution of optimal treatment combinations. Several methodologies will be explored to interrogate the posterior distribution of the optimal treatment combinations to obtain a combination that can be administered to a patient.

BIOGRAPHY

Dr. Ghanam is a full professor of mathematics at Virginia Commonwealth University in Qatar. Dr. Ghanam’s area of expertise is using the theory of Lie algebras to solve partial differential equations, especially equations that have applications in mathematical modeling. Dr. Ghanam has published more than 60 peer-reviewed journal articles and supervised and co-supervised many Ph.D. students in the VCU Richmond campus. Over the past few years, Dr Ghanam has been focusing on the applications of statistics in mathematical modeling. Dr. Ghanam published many articles related to mathematical modeling of Covid-19 in Qatar. Dr. Ghanam and Dr. Boone established the Mathematical Data Science Lab at VCUarts Qatar. Dr. Ghanam has presented his work in very prestigious conferences locally and internationally Dr. Boone, is full professor of statistics at the Department of Statistical Sciences and Operations Research. Dr. Boone has extensive experience in statistical analysis as well as statistical methodology development that includes many different fields including Neuroscience, Psychology, Forensic Science, Genetics, Environmental Science, Computer Vision, Exercise Science, etc. In addition, I have a wide perspective on possible techniques that can be used to draw inferences from the data beyond those typically used. Dr. Boone is also expert in Bayesian statistical methods with applications in the environment, health care and national security.