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. We identified two main optimization parameters for current medical therapies: specificity and dosage control.

Current therapies generally rely on either spatial targeting (within a physical area) or cellular targeting (to a specific antigen or biomarker). However, these methods still lead to high nonspecific effects and . For example, radiation therapy is able to spatially target and kill tumor cells, but this works only 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.

Spatial Targeting: Surgeons excise a tumor manually, without regard for cellular heterogeneity within and around the tumor area.	Cellular Targeting: Monoclonal antibodies identify antigens on certain cells or viruses. Monoclonal antibodies are often coupled with therapeutic agents. However, if the antigen is present in healthy tissue outside the diseased area, it will be targeted as well.

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 its 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 toward therapeutics is inefficient. Essentially, it becomes a race – will the treatment kill the disease before it kills the patient?