Growing human tissue for mass-production

BY Charles Pulliam-Moore  August 27, 2014 at 4:50 PM EST

Scientists are attempting to grow human tissue on small computer chips. Video by Wyss Institute

Scientists working out of the University of California, Berkeley are trying to grow thin layers of human lung, liver and heart tissue on minuscule computer chips in an effort to reduce the delay between initial laboratory research and clinical trials.

By manipulating adult cells harvested from skin, the team has recreated the tissue of vital organs that might otherwise be difficult or dangerous to obtain from test subjects. Using these so-called “organoid chips” in lieu of people might give doctors the chance to further refine drug treatments both for their effectiveness and overall safety.

Similar research is being done at Harvard’s Wyss Institute, where “organs-on-a-chip” are used to conduct drug testing to treat Barth syndrome and other diseases.

In many ways, the human body is like a complex puzzle composed of more than 7,500 individual parts, which are generally grouped into 78 organs and 13 organ systems. These chips act like simplified puzzle pieces that, when assembled, can simulate the ways in which drugs affect both individual organs and the body as a whole.

These chips, however, typically lack the complexity of the full-grown human tissue. Moreover, their shelf lives are too short for long-term testing periods. Yet, these chips can still be of value to drug companies. Like traditional computer microchips, “organoid chips” are meant to be mass-produced, providing a massive pool of semi-living subjects on which multiple iterations of a drugs-in-development could be tested.

For every one drug that eventually reaches consumers, there are some 40,000 that do not because of the monumental costs associated with bringing drugs to market. Much of the costs, according to drug companies, is attributed to failed drug trials. Organoid chips, unlike individual human or animal test subjects, could be created uniformly, possibly eliminating many of the variables that complicate and slow down the testing and eventual approval process of experimental treatments.