University of California San Francisco
Helen Diller Family Comprehensive Cancer Center

Search Engine: How Artificial Intelligence Techniques Are Aiding the Hunt for New Drugs

By Jacoba Charles | | January 4, 2017

Search Engine: How Artificial Intelligence Techniques Are Aiding the Hunt for New Drugs

Husband-and-wife research team Steven Altschuler and Lani Wu started out their careers in mathematics. Photo by Steve Babuljak

A better cure for cancer – and other illnesses – could already be in existence, hidden right under our noses.

The problem is that possible new lifesaving drugs are created much faster than scientists can study them. Millions of untested compounds wait, jumbled together in no particular order in vast repositories called compound libraries.

“These libraries are basically like black boxes right now,” says Steven Altschuler, PhD, a professor of pharmaceutical chemistry at UC San Francisco’s School of Pharmacy.

“You imagine that somewhere in there is some chemical that might be the key to unlocking any question that you have – but how are you going to find it?”

A new search method that blends cellular biology and computational analytics may be the answer. A husband-and-wife research team at UCSF – Altschuler and his longtime spouse and collaborator, Lani Wu, PhD, also a professor of pharmaceutical chemistry – have developed a way to do the job much faster and at a fraction of the cost of the traditional method. The work involved designing a new kind of cell, writing some new software, and then parsing the resulting landslide of data.

“We were very lucky to be there at the right time and see the connections,” says Altschuler. “Going in, we didn’t even realize that there was a need for this.”

The couple was uniquely poised to develop this method, as their work is informed not only by their current collaboration but also by their earlier shared careers in other fields. They have worked together since they met as students almost 30 years ago.

“We met in the mailroom,” Altschuler says. “It was the first day of grad school for her; I was a second-year.”

The pair started out their parallel careers in mathematics and went on to work for Microsoft, then for a biotech firm, before moving into academia.

“Most of us wouldn’t even think of an analogy between drug discovery and what they were working on at Microsoft with image recognition and things like that,” says Matthew Jacobson, PhD, chair of the Department of Pharmaceutical Chemistry, who recruited Altschuler and Wu to UCSF. “To me, this just shows the power of bringing people with different types of backgrounds into biology and drug discovery.”

Too Much of A Good Thing

Screening compounds for potential medical uses has to date been both time-consuming and expensive. For example, a lab looking to develop better chemotherapeutic agents would likely be interested in DNA-damaging drugs that have yet to be tested. Usually, researchers are looking for drugs that affect the chain of cellular events by which a given disease advances or can be treated – a biochemical process known as a pathway. An unknown number of such compounds are likely available in libraries housed at universities and pharmaceutical companies around the country. But how to find them?

“Over the last few decades, drug discovery has tended to be fairly pragmatic,” says Jacobson. “We tend to make various simplifying assumptions about how things work inside cells.”