Smoking is bad for you. And in other breaking news, so is too much fried food, drinking to excess and putting your hopes and dreams on a depleted Green Bay Packers secondary to make one stop in preventing a last-minute touchdown drive and avoid losing by one point!
However, that doesn’t mean researchers at Wyss Institute for Biologically Inspired Engineering at Harvard University are giving up on finding ways to combat the largest risk factor associated with cigarettes – chronic obstructive pulmonary disease, or COPD – which, by the way, is the third leading cause of death in humans worldwide.
The biggest challenge in studying COPD is that exposure to cigarettes effects living tissue much differently than lab-grown substitutes. And animal studies bring up numerous moral and study quality concerns.
So, fresh off their creation of a simulated heart on a computer chip, which was covered here on IEN.com last week, Harvard researchers have combined organ-on-a-chip technology with legacy Gatling gun mechanics to create a chain-smoking robot that provides more direct insight on the effects of cigarette smoke on living human tissue.
The robot’s turret holds 10-12 cigarettes, an automated car cigarette lighter and a microrespirator that simulates a human puffing on a smoke. The frequency, intensity and intervals can be customized, observed and recorded based on what happens as the smoke passes through the chip airway, which is lined with human bronchiolar cell tissues taken from either healthy individuals or COPD patients.
Additional cell culture medium is continually supplied so the process can be studied for up to four weeks.
The use of microengineered cell cultures like this lung on a chip are having a revolutionary impact on medical research, as they allow for specific organs to be tested without exposing people or animals to harmful side effects.
Researchers feel these types of studies will provide greater insight on how to decipher which cell types, cellular functions and genes contribute to diseases. In turn, this could translate to identifying biomarkers, drug targets and more personalized approaches to diseases like COPD.