Writing in The New Atlantis Scott Gottlieb has written a survey of how computer technology, gene arrays, and other advances are transforming how drugs are developed, diseases are detected, and treatments are delivered. His essay is entitled The Future of Medical Technology.
This new ability to diagnose and treat certain diseases early, from infectious agents like hepatitis C to degenerative ailments such as Alzheimer’s and Parkinson’s, may obviate the need for the types of tissue, organ, or stem cell therapies that often attract the most public attention. Moving from wet lab to computer, from random to rational drug design, from species biology to the individual unique DNA profile, companies adopting the in silico paradigm are unlocking the long-hyped promise of genomic medicine, making targeted drugs and diagnosis a reality and drug development faster, cheaper, and better.
While the ability to detect diseases earlier is helpful the real problem with a disease like Parkinson's or Alzheimer's is that there is currently no way to halt disease progression regardless of when it is discovered. Early detection of a neurodegenerative disease at this point pretty much just allows you to start worrying about it sooner.
Of course, some day there probably will be treatments that will halt disease progression for some diseases and early intervention with, say, gene therapy may allow later cell therapy or growth of replacement organs to be avoided. But early detection is not going to eliminate most of the demand for stem cell therapies and replacement organs. Organs grow old. Adult stem cell pools become senescent. Also, accidents in the form of everything from physical trauma to toxic chemical exposures happen. There are going to be plenty of uses for stem cells and replacement organs no matter how many advances are made in drug developement and in gene therapy.
The only thing that is going to reduce the reduce the demand for embryonic stem cells is the development of techniques that allow adult cell types (and not just adult stem cell types) to be transformed into other cell types including other stem cell types. This will come with time. The ways that cell diffentiation state is controlled will be elucidated. An increasing number of techniques for manipulating cell differentiation state (e.g. gene therapies, hormones, drugs developed for that purpose) will be found.
Gottlieb is on firmer ground when he describes the future potential of computers to speed drug development and generally to speed the rate at which biological systems are figured out.
In the future, a supercomputer sitting in an air-conditioned room will work day and night, crunching billions of bits of information to design new drugs. Multiplying at the speed of Moore’s Law, which predicts that computer processing power doubles every three years, this drug discovery machine will never need to rest or ask for higher pension payments. It will shape how we use the abundance of genomic information that we are uncovering and will be the deciding factor for the success of medicine in an age of digitally driven research.
The big challenge of biological systems is that they are complex and small. They are hard to watch. We do not know most of what there is to know about what goes on in cells. We can not predict how molecules we might introduce will interact with the existing systems in cells. Our problem is that we need tools that are commensurate to the systems we are trying to understand. We need the ability to sense more things at the same time continuously and cheaply. We need faster DNA sequencing. We need better tools for manipulating biological molecules very precisely on their own scale. After decades of chasing cancer, neurodegenerative diseases, and other disease what is changing is that we can begin to see the day coming when we will have those tools which operate at the scale of biological systems and that will make it fairly easy to take apart, manipulate, and predict the behavior of biological systems.
Computers are great general enablers for the development of instrumentation. They collect data, control actuators, and process the data. But semiconductors are being used in ways that go beyond just connecting to sensors and collecting dat from them. Semiconductor technology is being used to scale sensing and manipulating systems down to the level of biological systems. Silicon chips are being used to sense and interact with biological systems. Silicon chips are even being made into mini-chemistry labs. Tools are being developed that operate on the same level as the systems under study.
The other way that computers are contributing is in simulations. But the "rational drug design" process that Gottlieb reports on in his article is still an ideal to strive toward that lies in the future. There have been a few success stories. But computers are not yet fast enough and we do not have enough information on all the proteins in cells to be able to simulate how a drug will interact with a real biological system. For a sense of how drug development is done currently read Derek Lowe. When he writes about drug development he gives a real sense of where drug development is at when he describes the inability to get drugs to where they are desired and only where they are desired.
We have enough trouble just getting our compounds out of the intestines and into the blood; subtleties past that are often out of our range. As far as targeting things to specific spots inside the cell, that's generally not even attempted. What we shoot for is selectivity against the enzyme or receptor we're targeting (as much as we can assay for it, which sometimes isn't much.) Then we just try to get the compound into the cells and hope for the best.
Numerous unforeseeable problems come up. Cell outer surfaces and internals have enormous numbers of different surfaces. They have many different proteins that are constantly changing in shape and presenting new surfaces for possible drug binding. A drug which is developed to be aimed at a particular receptor might also end up having affinity for other types of receptors whose existence are not even suspected. Truly rational drug design will happen when it becomes possible to predict in advance whether a drug will reach the desired target receptor and that it will bind only on that receptor. We are a long way away from being able to do that. All these unforeseeable problems mean that in drug development there is still a very large element of luck at every stage of development.
Derek also has a great recent post on the same theme that I've struck above: we need tools that get down inside a cell to watch and manipulate it on the scale that a cell operates.
But I think the general trend is unstoppable. If we're going to understand the cell, we're going to have to get inside it and mess with it on its level. There are doubtless plenty of great ideas out there that haven't been hatched yet (or have been and are being kept quiet until they've been checked out.) For example, I'd be surprised if someone isn't trying to mate nanotechnology with RNA interference in some way. (There's a hybrid of two hot fields; I'll bet that grant application gets funded!) It all bears watching - or participating in, if you're up for it.
Here is the most important point I'd like to make about the future of medicine: the most powerful future treatments will not be classical drugs. Cell therapies will be incredibly powerful and of course they will be cells, not drugs. Granted, cells will be manipulated by drugs as part of the preparation to make them suitable for delivery. But the cells, properly programmed in their DNA, will be the main agents of therapy when they are used. Also, replacement organs are going to become incredibly important. Another major type of treatment will be gene therapy. The gene therapy will be more akin to a computer program than a classical chemical drug.
The biggest change coming in medicine is coming as a consequence of a fundamental limitation of classical drug compounds: they do not carry enough information. Cells, organs, and complete bodies are very complex information processing systems. The genome is akin to an extremely complex computer program. It seems unreasonable to expect that when a very complex information processing system goes seriously awry that the most serious problems that arise can be dealt with using molecules which have such low information content. By contrast, gene therapy and cell therapy should both be thought of as therapeutic agents that have much higher information content.
|Share |||Randall Parker, 2003 May 12 12:48 AM Biotech Advance Rates|