Research Interest

Modeling and Analysis of Transdermal Drug-Delivery Systems

A major challenge in the pharmaceutical industry is that current drug-delivery methods, such as tablets, injections and sprays, are inefficient in administering long-term consistent drug release to a target site. Certain drugs lose effectiveness over a period of time. As a result, multiple injections are necessary to maintain the therapeutic level required.

The scientific objective of our group is to introduce new mathematical formulations that ensure accurate, cost-effective polymer-based delivery of drugs to their target sites. Drug-release profiles can be varied by controlling several factors; such as: drug loading, polymer compositions and membrane thickness. Although optimal experimental designs (e.g. sequential simplex delivery method or response surface experiments) are helpful tools in the development of drug-delivery devices, they are costly and provide only limited predictive capabilities.

Our research proposes an alternative method based on a hybrid data-driven/first-principle modeling approach. By using mathematical models to predict drug-release and data-driven estimation techniques to predict the diffusion coefficient, a precise, efficacious polymer-based drug-delivery system can be designed to meet specific end-user requirements. The predictive capability of the methodology will allow for a performance assessment of drug-delivery devices without conducting numerous experiments, thus saving time and money.

Numerical and Experimental Approaches to Protein Separation and Purification

The biggest problem in biopharmaceutical and industrial protein production at commercial scale is the time and cost associated with separation and purification. The world market for biopharmaceuticals is about $30 billion and growing at a rate of 20-25% annually. Approximately 80% of these products are proteins that require extensive attention to isolation and purification methods before going to market. Six-month (or longer) delays for the introduction of a new drug to the market can cause significant revenue losses while the expenses keep mounting.

We are developing novel approaches, which rely on the symbiotic combination of rational and empirical strategies, to improve the efficiency, yield and time-to-market of biopharmaceutical drugs. Our group is devising means to eliminate the need for extensive measurements and data correlations in the determination of protein-polymer, polymer-polymer, and ion-polymer interaction parameters.

These approaches promise to dramatically reduce production costs of biopharmaceutical proteins and increase profit margings, as major production costs involve separation and purification steps.

Modeling and Control of Distributed Parameter Systems

Distributed parameter systems, such as chemical vapor depositions, nanostructred coatings processing and transdermal drug delivery are usually represented by Partial Differential Equations (PDEs). The control of these systems poses both theoretical and practical challenges.

Our work provides a good starting point for designing controllers for these processes.


Current Graduate Students

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