Customized drugs and a special program

[Stragomagus]

http://www.technologyreview.com/biomedicine/22795/

 

 

 

pg.1

 

[hide=]Monoclonal antibodies, which are engineered to hone in on very specific biological targets, have taken off therapeutically in recent years: several are now approved for treating cancers and autoimmune diseases, and nearly 200 are in clinical trials. But one of the challenges of monoclonal-antibody therapy is the fact that some people respond very well to the drugs while others respond only moderately or not at all.

 

 

 

A startup called PIKAMAB, based in Menlo Park, CA, believes that it can make monoclonal antibodies more effective by grouping patients together based on their genotype and offering a customized antibody developed for that genotype. The company hopes that this "stratified" approach to drug development and treatment will help drug companies achieve better results.

 

 

 

Monoclonal antibodies bind only to specific target molecules, giving them a precision that many other drugs lack. These Y-shaped molecules, which are naturally produced by immune cells called B cells, have a nearly identical base but arms that can vary depending on their intended target. The arms bind precisely to the target while the base of the Y provides an anchor for circulating immune cells to attach to.

 

 

 

Monoclonal antibodies were first identified as potential cancer treatments three decades ago, as the molecules could be engineered to bind to cancer cells and provoke an immune response against them. They have also proved useful for treating autoimmune disease and are under investigation as a treatment for many other conditions.

 

 

 

But scientists have found that patients respond differently to these drugs, largely because the antibodies are not able to bind to the immune cells of all patients equally well. Studies have found that the process, called antibody-dependent cell-mediated cytotoxicity (ADCC), plays a major role in how well several monoclonal-antibody drugs work. How an immune cell attaches to an antibody depends on one of two protein receptors at the cell's surface. People have natural genetic variations in these receptors: certain variations prevent immune cells from binding to antibodies, and these patients respond poorly to these antibody therapies.

 

 

 

Vijay Ramakrishnan, founder and CEO of PIKAMAB, believes that monoclonal-antibody therapies could be improved by taking into account the genetic background of each patient. "A one-size-fits-all antibody drug in this case doesn't work," he says.

 

 

 

PIKAMAB's approach is to first sort patients depending on whether they are expected to respond to a treatment or not. The company is marketing a "theragnostic" test that separates patients into one of nine groups in a matrix according to their receptor type and an analysis of their immune cells. At one end of the matrix are patients likely to respond well to an existing drug; at the other end are those who are likely to respond poorly. Ramakrishnan says that this test alone can benefit treatment, as it could help a clinician decide whether to begin a monoclonal therapy right away in an excellent responder or eschew the drug in favor of other options in a poor responder.[/hide]

 

 

 

pg.2

 

[hide=]The next step is to develop a portfolio of antibodies that are customized for each group of patients within the matrix. The drugs would be altered slightly so that they can bind specifically to the receptors in patients of each genotype. Ramakrishnan says that the portfolio could consist of a minimum of four and a maximum of nine drugs (one for each group) to achieve a high response rate in each group.

 

 

 

The approach is different from "personalized" medicine that is tailored to an individual. Instead, Ramakrishnan says, this "stratified" approach offers some personalization but in a more manageable way. He believes that a stratified approach to monoclonal-antibody therapies can offer advantages to pharmaceutical companies. If they begin stratifying patients in clinical trials, they could achieve better results and help justify the treatments to regulatory agencies and insurers, he says. Companies could also put a higher premium on drugs if those drugs came with theragnostic tests.

 

 

 

PIKAMAB hopes to work with pharmaceutical companies to create commercial theragnostic tests and stratified therapies involving drugs that are already on the market or in development. Together, they also plan to develop their own monoclonal antibodies.

 

 

 

"I think it's useful to have a predictive test that can accurately describe whether a particular individual has a receptor that will make ADCC easier or harder to exploit as an anti-tumor mechanism," says Louis Weiner, a cancer immunologist at Georgetown University who has no ties to PIKAMAB. Weiner is, however, skeptical that customized antibodies are necessary to improve monoclonal-antibody therapies. He sees more potential in "high affinity" monoclonal antibodies that bind tightly to immune cells regardless of a patient's genotype.

 

 

 

Ramakrishnan argues that such drugs may not completely optimize the responses of all genotypes, and that there is room for further improvement with customized drugs. He points out that when monoclonal antibodies are used to treat cancer, it is usually in combination with radiation or other treatment. By optimizing the drugs, he says, it may be possible that certain patients could receive them as stand-alone therapies, thereby reducing the side effects and cost of treatment.[/hide]

 

 

 

I'm glad to see that some progress is being made on our ability to produce drugs that are tailored to each recipient of it. The most beneficial thing I can see coming out of this is that having customized drugs, for each patient, will significantly reduce all the side effects we see due to them being made for the masses.

 

 

 

In other news...some Stanford researchers have created a program that does calculations on "folding", which relates to ribosomes. (found a video on this a few weeks back while surfing youtube)

 

 

 

http://folding.stanford.edu/

 

 

 

Home page

 

[hide=]What is protein folding and how is folding linked to disease?

 

Proteins are biology's workhorses -- its "nanomachines." Before proteins can carry out these important functions, they assemble themselves, or "fold." The process of protein folding, while critical and fundamental to virtually all of biology, in many ways remains a mystery.

 

 

 

Moreover, when proteins do not fold correctly (i.e. "misfold"), there can be serious consequences, including many well known diseases, such as Alzheimer's, Mad Cow (BSE), CJD, ALS, Huntington's, Parkinson's disease, and many Cancers and cancer-related syndromes.

 

 

 

You can help by simply running a piece of software.

 

Folding@home is a distributed computing project -- people from throughout the world download and run software to band together to make one of the largest supercomputers in the world. Every computer takes the project closer to our goals. Folding@home uses novel computational methods coupled to distributed computing, to simulate problems millions of times more challenging than previously achieved.

 

 

 

What have we done so far?

 

We have had several successes. You can read about them on our Science page, on our Awards page, or go directly to our Results page.

 

 

 

Want to learn more?

 

Click on the links on the left for downloads or more information. You can also download our Executive Summary, which is a PDF suitable for distribution. Also, you can learn more by watching recent seminars (Stanford BMI ; Xerox PARC). One can also help by donating funds to the project, via Stanford University.[/hide]

 

 

 

If you want to give them a hand, you can not only just download the program, but can get your entire family involved in the project with a team number.

[fastortoise]

The possibility of tailored drugs is what attracted my to genetics in the first place. I've been watching my grandmother suffer for 5 years trying to find a blood thinner that doesn't give her heart palpitations :cry: .

 

 

 

However, in order to make such specific drugs for each individual based on their genome, a LOT of trial and error in required. Hopefully, with the rise of super computers, genome sequencing and data storage will rise to the occasion and enable scientists to make accurate and efficient advances in these trial and errors. I expect genome-based drugs to be effective in 10-15 years and a full catalogue of custom drugs in 30.

 

 

 

As they say: 'survive for the next 15 years and expect to live another 100'.

[Stragomagus]

I expect genome-based drugs to be effective in 10-15 years and a full catalogue of custom drugs in 30.

 

 

 

Hmm...at the rate we are going I would give it another 30 years to see significant effects and an additional 20 before we see mass tailored drugs. The additional 20 being for the conversion of the factories themselves to be able to handle such a burden.

[warri0r45]

The concept is called pharmacogenomics - tailoring drug treatments to suit an individual's genome. The potential of this approach is huge, not only for the efficacy of drugs, but to mitigate potential side effects as you said. Of course there are masses of data we have to deal with here, and high grade computing ability and data management will be essential.

 

 

 

I like the stratified approach this article talks about. It seems like a logical place to start. We can work down to a person-by-person specificity in good time.

[fastortoise]

I like the stratified approach this article talks about. It seems like a logical place to start. We can work down to a person-by-person specificity in good time.

 

I was wondering - since the human genome is so complex and since we hardly understand most of it, which will come first; tailored drugs or an 'annotated' genome?

 

 

 

The former can be slowly built up by trail and error-ing drugs for stratified groups of people based on their genotypes (like in the article) and the latter can be understood by studying model species like drosophila melanogaster or zebra fish. After some though (I left for a bit before finishing this post), I feel like they go hand-in-hand. I'd like to elaborate, but I don't feel qualified to do so.

 

 

 

On a side note, my new life goal is to get a job in a biotech firm somewhere in California and have a slice of the major coin they're making.

[Stragomagus]

The quickest way I can think of to make an annotated genome would be to advance our knowledge of cloning, which in turn would speed up the "former" as you said fastortoise.

[fastortoise]

The quickest way I can think of to make an annotated genome would be to advance our knowledge of cloning, which in turn would speed up the "former" as you said fastortoise.

 

I think that's also the reasoning of many biotech firms, not sure though. Since we cannot clone humans, we clone species that share similar traits with us; such as mice or fruit flies. It's only until we understand how genes interact with each other to produce complex organisms that we can produce drugs without any side-effects. Studies on mice and fruit flies are so crucial for understanding how complex diseases like autism work. I still can't believe a strong advocate for autism cures, Sarah Palin, complained about how much 'science' wasted their budget on fruit fly studies... when they were paving the way to find cures for autism. If there was anyone I'd slug in the back of the head, it would be her.

 

 

 

So, to repeat, I think scientists need a better understanding on how the genome operates before they start pinning labels on disease-causing genes.

[warri0r45]

 

So, to repeat, I think scientists need a better understanding on how the genome operates before they start pinning labels on disease-causing genes.

 

 

 

That would of course help, but I think in the interim knowledge of specific genes, the protein they produce and how they are regulated is crucial. Check out this article for an interesting look into P450 pharmacogenomics research and the hurdles that have been faced:

 

 

 

http://www.nature.com/tpj/journal/v3/n1 ... 0144a.html

 

 

 

The P450 genes are particularly promising because they target drugs and toxins for removal from the body.

[meol]

This sounds really interesting, but I just can't understand the whole of it. Can anyone explain how this works to someone with no college biology knowledge?

[fastortoise]

This sounds really interesting, but I just can't understand the whole of it. Can anyone explain how this works to someone with no college biology knowledge?

 

I'll try:

 

As most people already know, DNA is the chemical that is responsible for making you you. It does so by translating it's information into proteins, which make up the majority of your dry weight. We each differ from one another by 0.0001% (invented number) of our DNA sequences. Since we are all unique, we each have our own 'personal' DNA genome (the sum of all the genes in your body) which was inherited by your parents (50/50).

 

 

 

These genetic differences account for the variety of skin, hair, eye colour in our species. A pharmaceutical scientist, however, is more interested in the differences of our metabolisms, how we handle drugs. The important part is here: we now know all diseases have a genetic basis. Therefore, with the complete knowledge on how our genes interact with the environment and themselves, we can potentially cure every single known disease. If we can directly link a certain gene to a disease, we could single out babies who carry this gene prone to a certain disease, then prescribe drugs to counter it. The only (big) problem is, we're all different, and we do not all react to drugs the same. Furthermore, there is hardly ever a direct link between a gene and a disease. Most of the time, it is a combination of several genes and environmental factors that result in a disease, which is why I think it is important to fully understand our genome before linking diseases with genes.

 

 

 

An example of how this would work:

 

I'm immune to morphine, so there is probably a mutation in my 'morphine gene' which I inherited from my mother (she too is immune). To 'cure' me, scientists would first have to discover where this gene is located (where on the chromosome) by comparing my genome to a genome of someone who does not have this mutation. Obviously our genomes would differ not only by that one gene but also by several other million genes. That's where the tricky part comes into play. We simply do not have enough humans to cure my problem, which is why scientists turn to organisms who's genomes closely resemble ours (mice/fruit flies). When they find where this mutation is, they can sequence (or 'read' it) to find where the problem is and fix it by prescribing drugs. Of course this example is silly since my immunity to morphine has no health risks, but hopefully you can now appreciate the potential in genetic-based drugs.

 

 

So, to repeat, I think scientists need a better understanding on how the genome operates before they start pinning labels on disease-causing genes.

 

 

 

That would of course help, but I think in the interim knowledge of specific genes, the protein they produce and how they are regulated is crucial. Check out this article for an interesting look into P450 pharmacogenomics research and the hurdles that have been faced:

 

 

 

http://www.nature.com/tpj/journal/v3/n1 ... 0144a.html

 

 

 

The P450 genes are particularly promising because they target drugs and toxins for removal from the body.

 

An interesting read, but only because I find it was very badly written (strange phrase structuring and obvious spelling mistakes.. and written by a MD). I had trouble following it, and I'm usually capable of reading articles like these (except those leaning heavily to statistics). I read it only an hour ago and I already have trouble picking out the main arguments of the paper - it was just so terribly structured. Was it just about scientists discovering the different levels of the cytochrome based on ethnicity, or about actually finding the gene that coded for it?

[warri0r45]

Was it just about scientists discovering the different levels of the cytochrome based on ethnicity, or about actually finding the gene that coded for it?

 

 

 

It was about studies into polymorphisms of some P450 genes and how they may contribute to a difference in drug efficacy between individuals.