Making Drugs Smarter

Aug 01, 2005

Nicholas Peppas
The world of drug delivery—at least at its cutting edges—has begun to converge with diagnostics, tissue design, and materials science in ways that promise to transform some areas of medicine. One of the most interesting developments involves "intelligent therapeutics" that detect specific substances in the patient's bloodstream and respond to them by releasing an appropriate dose of drug. One of the key figures in the world of intelligent therapeutics is Nicholas Peppas of the University of Texas at Austin. Peppas got on the phone with Pharm Exec recently to talk about emerging work in the field. What follows is an edited transcript.

Pharm Exec: What has changed about the work being done in drug delivery compared to 10 or 15 years ago?

Peppas: In the 1970s and 1980s, we were talking about a once-a-day tablet that could be taken in the morning and be available in a patient's body for the next 16 hours. But as we solved that problem, we realized that there were diseases where a drug didn't have to be released continuously, but only as necessary.

The classic case is type 1 diabetes, in which insulin has to be delivered only when glucose levels are high. People started talking about coming up with systems that would respond to the patient and release the drug only when the patient needed it.

What form did that take?

In diabetes, for instance, some of the early—and unsuccessful—approaches involved devices or systems that could be left in the body for a period of time. They contained glucose oxidase, the enzyme that breaks down glucose.When glucose levels were high, glucose oxidase would break it down and the system would release insulin. As I said, this hasn't worked. Other systems have been more successful.

How does one of these systems recognize an undesirable compound?

Different investigators are using different techniques. In my laboratory, we use patented methods of what we call molecular recognition, with which we are able to recognize a specific undesirable compound and only that compound.

For example, we have nanoparticles that are able to recognize cholesterol. Different nanoparticles are able to recognize glucose.

Other investigators use other systems. Some use a chemical reaction.Others use an electrochemical reaction to recognize a chemical compound and start the release process.

How does the intelligent material go from recognizing the substance to reacting to it?

Again, there are different techniques. The mechanism might be a chemical reaction that breaks down a polymer and allows the drug to come out. Or you might have a coating of polymer that contains enough of the drug for the first treatment of the patient. And later, a second recognition process will lead to a second coating being released, and so on.

It might be something simpler—for example, a swelling process that allows one layer to be released and then a second layer and then a third. In some of our new developments, we have what we call multi-depot structures. Basically, you have a big matrix, inside of which you have minute spheres, each one encapsulated to release at specific times.

It sounds like you're talking about techniques that have been used for pills to determine when they're released in the gut, and you're now taking it all the way into the bloodstream.

It is true that systems using oral delivery have had an impact in our way of thinking. But the response in the blood is significantly different than what it is in an oral delivery system. And so one has to be careful when one generalizes. And many of the nanoparticulate systems we're discussing here, although they seem to work from an engineering point of view, don't work in medical applications where there is a strong immune response to them.

Are there other approaches to intelligent delivery besides nanoparticles?

We are also developing microchips that hopefully will be miniaturized to the nanochip level. The chips will be implanted in the body and will have the ability to recognize and release at specific intervals. Some companies are working on this approach right now—MicroCHIPS and Immed, for example.

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