Tuesday, October 16, 2007

How personal will Personalized Medicine become?

Personalized Medicine is a great idea in theory...the idea that the drugs that your doctor prescribes to you will be matched to your body's unique biological characteristics. But will it become reality? The "made for me" drug is unlikely, but the "best match for me" drug is both feasible and a significant improvement to the way most drugs are prescribed today.

The financing needed for drug development is substantially high. In order for a drug to be worth the cost of discovery, testing, and marketing (estimated upwards of 1 billion dollars per drug), it must have either 1) a large target patient population who can take the drug, or 2) have very high prices in order to recoup the sunken cost of making the drug. On an economics argument alone, the idea that a drug could be made specifically to match my personal unique biology is unreasonable. At best, we can hope to have some level of prescreening patients to match them with the drugs that are most likely to help and not harm them.

Currently, when most patients see a doctor for an ailment, they are given a treatment or drug in the hopes that it will help them based on the findings that it has previously worked on other people. This seems reasonable. However, this can sometimes be simply a hope. There have been studies that much (some studies even say most) of the prescribed drugs do not help and may even hurt the patients that receive them. Drugs often have the fine balance between the helpful effects (efficacy) and the harmful effects (adverse events). The drugs must go through clinical trials to prove their efficacy and to find the right amount to use (therapeutic dose) while avoiding as much of the adverse side effects as possible. One problem of course is that no two people are identical. Even "identical" twins have biological differences between them. Therefore, drug effects seen in people in the clinical trials will not capture the diversity of the general population. Clinical trials involve thousands of patients, but even these numbers may not be sufficient to catch rare side effects that only occur once in a million people. It is only once the drugs are approved for marketing and are actually prescribed and taken by millions of people do some of these rare adverse events become recognizable.

So often a delimma develops. What do we do with a drug that has been shown to help thousands or even millions of people, but some people not only fail to benefit from the drug but suffer adverse events? Often if the adverse effects are severe or lethal, the risk to the few outweighs the benefit to the many and the drug is pulled from the market. This makes sense because without knowing who will suffer the side effects, no matter how rare they may be, few doctors would be willing to take the chance nor would many patients want to take that chance depending on how severe the adverse event was compared to their ongoing illness. Personalized medicine has promised to help solve this issue. If a test can be made that would distinguish the patients who would benefit from those who would not, the test could then be used to prescreen patients before they take the drug. The drug would then be given only to those who would benefit. Thus, a helpful drug could be kept on the market rather than be removed.

However, lately personalized medicine claims have gone beyond this simple scenario. We are now in the era of genomics. It is possible to read the DNA sequences of individuals and gain insight into their genetic makeup. A large number of scientific publications have come out in the past two years linking DNA sequences that are commonly present in the population to various common diseases such as heart disease, obesity, certain forms of cancer, crohn's disease and others. These diseases are known as complex diseases because no single marker, gene, or environmental exposure appears to cause them, but rather they are due to the complex interactions and relationships of multiple DNA sequences (genes) and environmental exposures and events.

These recent findings (and many more to come) are very helpful in understanding the causes of complex diseases. However, while identifying DNA sequences that are linked to these highly prevalent diseases is very helpful, how that information is used and interpreted can be troublesome if not carefully managed. We are now in an era where the technology of obtaining DNA sequences far outpaces our ability to understand how the DNA sequences are biologically linked to disease. In other words, we are reading the text of the book much faster than our ability to comprehend what it means. What makes the situation even more complicated is that the DNA sequences being discovered are most often not direct causes of the disease but rather are susceptibility indicators. They are identified as being linked to the disease under study because they are found more often in people with the disease than in people without the disease at a statistically significant difference.....and here is where my main concern lies with the public's use of this information. It all comes down to statistics and probability. If a biological test was performed on you to see if you had a DNA sequence that was linked to heart disease, would you know what to do with that information?

First off, you may be thinking you don't want the test if it's going to hurt, but don't worry, collecting DNA for these tests is easy and painless. Your body cells can be obtained by a small blood sample such as a finger prick, or by swabbing the inside of your cheek with a Q-tip, or even by having you rinse your mouth and spit into a small tube. Your DNA can be obtained from all of these simple methods with no harm to you.

Ok, so now I have your DNA. I run the test on you and find that you have a DNA sequence that has been shown to be linked to heart disease. What do you do? Well, it is important that you understand probability and the fact that this DNA sequence does not guarantee that you will have heart disease. You should find out how strong the statistical correlation is between the DNA marker and the likelihood you'll get heart disease. The correlation may be strong, hence you are likely to suffer the illness, or could be weak, in which case you are at less risk.

You may say that heart disease is such a life threatening illness that you will make a lifestyle change no matter what the odds may be. Maybe you had relatives with heart disease giving you more reason to believe your chances of having the disease are high. You can vow to change your diet to have less fat and cholesterol, you can exercise more, your doctor may prescribe cholesterol lowering drugs, etc.

Ok, great. Eating better and exercising more is fantastic and strongly recommended. The prescription of drugs can be benefitial, but what if you're taking medications for an event that won't happen? Let's change the scenario. What if the test wasn't for heart disease, but rather for restless leg syndrome or pattern baldness? Diet and exercise are unlikely to help much (although I would still recommend them anyways). Are the risks of getting these ailments of such great concern to you that you might start taking medications to prevent restless leg syndrome or baldness? Remember, the test showed you were more likely than not to have them, but not a guarantee you will. What if the medications for these have side effects? How do you balance the side effects with the fact that you may not need these medications at all if you aren't going to have the problem?

What if the test was for alzheimer's disease for which their are no well documented ways of preventing it or curing it? How would knowing that it may be in your future effect you? These types of questions are being addressed now. In recent cases of a genetic test for breast cancer (BRCA genes), women who have mutations in these genes are more likely to develop breast and ovarian cancer than women who don't have the mutations. There is a test available for this and some women who test positive for the mutation have opted to have both of their breasts and their ovaries removed to try to prevent the cancer from occuring.

This issue is likely to quickly become even larger not only because more and more DNA markers are being linked to common diseases, but your DNA information may become readily accessible to you as a consumer. Several companies have now been formed where you can send your DNA to them and they will test you for not just one or a few DNA sequences, but rather 500,000 or more at once. Imagine that you can send in your cheek swab or tube of saliva to a company via the mail, and within a few weeks, receive your DNA profile on what markers you have that are linked to heart disease, breast cancer, restless leg syndrome, psoriasis, Crohn's disease, macular degeneration, Alzheimer's disease, attention deficit disorder, schizophrenia, major depression, arthritis, diabetes, manic-depression (bipolar disorder), etc, etc..

How do you process all this information and who will explain it to you? How will you feel when you log onto the internet to retreive and search through your genetic profile and find targeted advertisements for diabetes medications and hair loss treatments matching your genetic risk profile page? Will you be asked to join social networking sites and blog groups for people who share your disease risk markers? Not only should you consider how you will respond to it, but consider how others will respond to it once it becomes available. Your spouse, family, employer, insurance company?

We're far from the movie Gattaca where people were socially and economically stratified at birth based on their genetic predispositions, but we are moving towards a time when the general public will soon be just like the scientists are today, i.e. they will have the text of their genetic book long before they have the ability to understand what it means. My advice to those out there ready to mail in their saliva and see what their DNA blueprint shows......make sure you take a statistics class on probability theory!

Saturday, October 13, 2007

my first posting

This is my first post, so I'll do a little introduction about some of the current interests that I've been focusing on. As you can see from the interests I listed in my brief bio, I am very much into science and business. My current job commute is 4+ hours per day by train (BART and Caltrain). Fortunately, this is a workable commute and I use it to get work done. I also use this time to listen to some great podcasts. The two main podcast topics I've been listening to are project management and investing. I list some of my favorites under the "favorite books" section in my bio. I highly recommend these to anyone interested in these areas as well.

My main career focus now is to build and strengthen my project management skills. I am now working towards obtaining my PMP certification, so if anyone out there wants to contact me about that, please do. I would love to hear from you if you are either pursuing or have a PMP. My goal is to become a project management expert and leverage that along with my scientific research training and background to help lead a company in the biotech/pharmaceutical industry. If you have thoughts, comments, and advice, I'd love to hear them. I especially want to hear and learn about life science research and manufacturing management in addition to software development and IT managment. The latter two areas tend to dominate the vast majority of PM topics and tools that I see out there on the internet, blogs, podcasts, and books. I would love to hear and learn more about managing clinical trials, drug discovery, drug and medical device manufacturing, and other biotech/pharma topics.

Some management podcasts I think every manager should listen to:
Manager Tools: I think by far the best practical guide to day to day management and career advice. I highly recommend this podcast. Mike and Mark are a great duo. Each one is about 30 minutes long.

Ethan Becker's Speech Coaching Tip of the Week: I started listening to this thinking from the title that I might get some good tidbits of information about public speaking and presentation skills. However, this podcast is much more than that. It gives excellent advice on a wide variety of managerial topics. It's short (about 5-10 minutes). It doesn't go into nearly the detail that Manager Tools does, but it has great short bits of advice. Listening to Ethan Becker clearly enunciate every syllable and consonant of every word as he speaks is sometimes humorous, but really gets the point across that most of us mutter our words and don't speak clearly when we talk.

Project Management Podcast: This podcast is on the long side (45min - 1 hour) and does have a lot of chatter and reading of listener emails that I think you can skip over to cut it down to the main points. I listen to this regularly because it has some very good interviews with PMs and was my first introduction to the nuts and bolts of a lot of PM tools and terminology such as PMBOK, PMI, Agile, ITIL, scrum methodology, PRINCE2, etc. If you're already a PMP, a lot of those are second hand, but you'll still benefit from hearing the interviews and can now use the podcast as PDUs to maintain your PMP certification.

Switching gears now to investing: As a hobby, I have been learning a lot about investing and equity trading. I'm being smart about it and make sure to erase all debt and fill up my retirement and emergency funds first. However, with a little bit of the leftover, I have been doing swing trading. I'm fascinated by day trading, but realize that I would need to do this as a job, not a hobby, to be successful. Therefore, since this is a hobby (or maybe I'll call it a part time job), I stick to trend analysis and swing trading. I look to hold for days to several weeks. Anything longer than several weeks gets boring since it ties up cash and prevents the ability to take advantage of other opportunities that come up. I'm learning about but too hesitant to do options trading for now. I may eventually move into options once I feel I've started to better understand a lot of the equity trading.

Some podcasts I recommend:
Real Story with Aaron Task: This is my favorite daily Wall Street wrap-up podcast. Always about 30 minutes long, it is a great overview of how the major markets behaved that day, what stocks were moving, and some great interviews from insiders on where they think the trend is going. I'm sad that Aaron had to stop playing rock and roll songs because of copyright problems, but he used to do a great job of picking rock songs to reflect the mood on the street. I hope he can find a way to bring this back because it added a great touch to the show and it's not the same to hear Aaron sing "Warning!!" for the Jeff Tate zone segment without any background music.

The Dividend Investor: This has become a lot more self promotional (new book release) lately, but still has some good advice for the average person without a lot of the "Buy this stock now!" advice out there.

The Money-guy.com: This is kind of long and repetitive now that it's moved from just a podcast to a podcast/radio show format, but it does have good plain-speaking advice about your whole financial planning strategy. Brian gives good advice on retirement plans, 401ks, insurance, etc.

The Fast Money Machine: I listened to the Market Guys podcast hoping to learn a lot of chart analysis tips, but was overall very disappointed. Then I found this podcast. It started and still is an analysis of CNBC's Fast Money show to see how well that show's stock pickers actually perform. This was modeled after the Mad Money Machine blog that follows how well Jim Kramer's Mad Money show does for stock picking advice. However, what I really love are the "Tools in the Crib" sections of the Fast Money Machine's podcasts. This gives some great tips on chart reading and analysis. You should listen to them in order because he builds the tools up from the ground so that you can assemble them sequentially on your desktop or in your head to follow how he uses them. Great stuff.

If you have podcast recommendations for me on these topics, please let me know.

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