Team:Penn/ProjectOverview

Medicine is a challenge of optimization. When treating a disease, doctors and physicians want to maximize the on-target, beneficial effects of a therapy while minimizing the off target or side effects. There are two main optimization parameters that doctors face use when applying current medical therapies: specificity and dosage control.

Current therapies are usually able to target spatially (in a particular region of the body) or cellularly (targeting to a specific cell type). However, these types of targeting still lead to high nonspecific effects and are limited in their approach. For example, radiation therapy is able to spatially target and kill tumor cells, but this only works when the cancer is highly localized and when the tumor area is well defined. Chemotherapy and monoclonal antibody therapies are able to target by cell type, but they target even healthy cells that are of that type. This is why patients undergoing chemotherapy exhibit horrible side effects: the treatment targets and kills all rapidly dividing cells, including hair and skin cells.

Precise dosage control is difficult in current medical therapies. Relying on passive diffusion makes dose precision hard to determine – of the dose injected into the body, how much of it actually reaches it’s target? Innovation in pharmacology therefore focuses on increasing the therapeutic window -- the range of drug dose that is considered both effective and safe – so that doses may be increased if necessary. Besides being expensive in both cost and time, this shotgun approach towards therapeutics is inefficient. Essentially, it becomes a race – can you kill the disease before the treatment kills you?