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Monday, August 28, 2006

Craiglist Ad, A Cure for the Flu

Some jobs are advertised on craigslist. Notice that craigslist is not capitalized. It's a website where people peddle their used items. They sell old sofas, stereos, and old jobs. The jobs you see are the ones that were recently abandoned for greener pastures. You're not going to see an important executive job posted on craigslist. To fill an executive position we have recruiters who seek out accomplished individuals. We have compensation experts develop a package that will lure the best candidates to serve a corporation. But is all this Cargo Cult science? Could we advertise on craigslist to fill executive spots and still get the same level of performance?

The executives in a biotech company have one thing missing. They don't know what is going on in the lab. There is not enough time to sort through the details that go into a potential cure for a disease. Execs need to know what the gist of it is and they will move along and do their important work. Meanwhile, the kid who got his job off of a craigslist add has to figure out how to make siRNA prevent the next avian flu pandemic. There really is a company who is taking on such a project. They bought the license from a smaller company and now they are "developing" the technology. Shouldn't the technology be developed before you buy it? Imagine the executives negotiating the deal. Millions of dollars are exchanged. People are flying from coast to coast working out details and writing up contracts. After it's all said and done, they look at what they've got. Is it a cure for the flu? Not exactly. We'll send it to R&D and see what they can do with it. The important work has been done.

Laboratory positions for the company curing avian flu with siRNA are listed on craigslist. Currently they are hiring some process development people and some QA types. Other websites are used as well. Just after the executives struck up the license agreement an ad came out on the WBBA website. They wanted a PhD who had experience with siRNA and the avian flu virus. Hmm.

So what do the executives talk about that puts them out of the craigslist arena? They certainly aren't talking about ways of detecting siRNA interacting with the influenza virus inside a human body. When it comes to developing the next big cure, I assume there is much talk about the the cost of the trials, who will run them and so on. But after all is said and done, the real work must begin. Every aspect of the next steps is critical to understanding whether or not the drug will work. It is at this time that the people involved are more than just some schmucks you find on the internet while you're looking for an old sofa on craigslist. All the agreements and legal battles will become useless the day they shut down the trials due to lack of efficacy.

Executives don't cure disease. They make deals. So do scientists however. The deals we make are with nature. If we're smart we get what we're after. If not we have nothing. It's a high risk endeavor but one we enjoy doing because we are convinced that we are indeed smart. We don't want to talk about making deals with other human beings. The only thing that matters is curing the disease. After that let the execs do their job and get the drug made. They are good for some things.

Wednesday, August 23, 2006

Critical Thinking

What is critical thinking? We all make mistakes even when we are intentially trying to think critically. I recently posted a comment on a blog criticizing big pharma and the FDA for their influence on science. The first rebuttal I received informed the world that I was a left winger with an anti-science attitude, and that I lacked critical thinking skills.

The statement was, "The biggest problem facing medical science comes from the Pharmaceutical industry and the FDA".

The rebuttal: "This is an excellent example of the anti-scientific thinking on the left. The science isn't the problem in the pharmaceutical industry or the FDA (capitalism and deregulation are the problems)."

Now let's break down the rebuttal in terms of critical thinking.

Question A: I'm a left winger.

The comment that I made was on a left wing blog. That is the bias that a critical thinker must avoid. I made no comment regarding my political viewpoints.

Question B: I'm anti-science.

Once it was assumed that I was a left winger it must be assumed that I am vehemently against all things that involve authority. However I made no negative comments regarding science. Rather I derided the influence big pharma and the FDA is having on the scientific process in medicine.

The last sentence, "The science isn't the problem in the pharmaceutical industry or the FDA" represents the real break down in critical thinking.

I say the science (X) is good. Big pharma (Y) and the FDA (Z) have a negative influence on science (X).

The rebuttal says that X isn't the problem in Y and Z. In parenthesis we see that capitalism (C) and deregulation (D) are the problems.

I claim that Y and Z have negatively influenced X.

The rebuttal claims that C and D have negatively influenced Y and Z.

It is assumed then (in the rebuttal) that X is merely a subset of Y and Z and thus cannot be influenced by them.

Science is never a subset of any other organization. It exists in the minds of men. It can be used by anyone who choses to try it. When big pharma goes through the FDA to put a drug on the market they are telling us that they used science to determine that the drug will alleviate some ailment that occurs in the human body. Quite often this is not the case. They manipulate data, which does not serve those engaged in the scientific process. Since the process involves many people putting together many pieces of the puzzle, anyone throwing in nonsense will create confusion along the path to the truth. They hire scientists but use their own ghost writers to write up the papers for the hired scientists to sign their names to. This is a shamefully anti-science practice meant to lend credence to the companies non-scientific marketing of their product.

I could go on but I'll stop there. The problem I encountered with my comment was that it appeared that I was attacking science. We want advances in medicine as much as the Cargo Cults want the cargo. We look to any organization who employs "science" to bring us our hopes and dreams in a neat little pill. The problem is that science is more than white lab coats and big words. You have to have the ability to cut through your biases and think critically about the issues at hand. What really matters? Nature will let you know if you set up your experiments properly. If you consider science a subset of the corporate process then you will have a hard time getting to the truth.

Tuesday, August 22, 2006

Visualize the Curves

This is a sigmoidal curve. It represents a system where something happens (y axis) as something is increased (x axis). In the case of the ELISA assay, we could be looking at an increase in absorbance as an antibody concentration is increased. Perhaps we're looking at the HIV ELISA. How can we describe the development of this assay?

Bob Gallo describes it without the useful graph. In 1984 they reported their assay as:

"100% of the AIDS sera were scored positive...84% of the lymphadenopathy patients were found to have serum antibodies to HTLV-III... 21% of healthy homosexual men with an increased risk of AIDS were also positive. No heterosexual controls... had antibodies to HTLV-III. The results strongly indicate that the antibodies to HTLV-III are diagnostic of AIDS or indicate significant risk of the disease, and suggest that HTLV-III is the primary cause of human AIDS."

The Gallo approach appears to be to test people using the ELISA assay. A signal equals HIV. So, if there serum produces a signal on the ELISA they have HIV which corralates with their illness (AIDS). That's not unreasonable, but what about the actual data? What is the cut off signal for a positive and negative signal? Midway up the sigmoidal curve? Let's add another curve to the chart the represents the negative patients blood serum.

The amount of protein in the sera can cause background signal. As you dilute the sera you will reduce the signal. On the sigmoidal curve chart we add a negative curve. It stays with the sigmoidal curve (moving from x and y equal zero) until that curve starts to rise. The negative curve stays close to the base line but gradually slopes up where it will again meet up with the sigmoidal curve. At this point in the x axis we are experiencing false negatives.

Using these two curves we can thus define the false negative and a false positive as points on the x axis. That means at some dilution of blood serum both HIV positive and HIV negative people will give the same signal. There will be a range in between these two point where negative and positive sera can be distinguished. The ideal concentration (dilution) will be where the positive signal has plateaued and the negative signal has not begun to rise. Since this is not the range where you will get false positives or false negatives it can be called the positive positive/positive negative range or ++/+- range. The x axis represents concentrations. They can thus be defined in the following manner

False negative: When positive control give no signal. --
False positive: When negative control gives a signal. -+
Positive positive: When positive control gives a signal ++
Positive negative: When negative control gives no signal +-

at concentrations A, B, C, D, E, F, and G

Positive control A-- B-- C++ D++ E++ F++ G++
Negative control A+- B+- C+- D+- E+- F-+ G-+

We can define our useful ELISA assay range as concentrations C, D and E.

The single data point ELISA followed up with a corralation to AIDS patients and a negative control group is not rigorous science. The assay development should begin by defining the positive and negative curves. Then you can think about changing a blocking buffer perhaps. Does it separate the ++/+- range further? Every tweak to the system must strive for that result. You are trying to get the ++ part to start as soon as possible along the x axis. That means you want to make the ELISA highly sensative to HIV antibodies. You want the false positive signal (-+) to start as late as possible. That means you want the assay to not be sensative to background proteins.

You will find yourself in meetings where Cargo Cult Scientists gather to discuss ELISAs. They will each have a repertoire of buzzwords for buffers, plate readers, plate washers, conjugated antibodies, substrates and graphing software. No one will talk about the curves. But it is the curves that explains how each change in buffers, plate readers and so on, will affect the system you are tying to set up.

Friday, August 18, 2006

Two Cans of Pears

Imagine a case of canned pears, unlabeled in aluminum cans. Pull out two cans. Label one with a brand name such as Delmonte and on the other put a generic looking sticker that says Pears. It is my firm belief that most people who try the pears and would pick the brand name pears as superior quality canned pears. Furthermore, if you were to hire a group of scientists to prove that the first can of pear is better than the next, they would successfuly complete the mission.

I also believe that science can be applied to anything. That would include the psychology of scientists. One way to test science would be to knowingly hire scientists to do something you know is wrong, such as analyzing two identical cans of pears with the goal of proving one superior to the other. When they get the results you wanted them to get, they have to get published. Once that is done you reveal the hoax and study the reactions of all who were involved. What you are studying is the process of pathological science. You could address motives, methods, the contributions of others, the response from the authorities and maybe even the response to the notion of being tested. No one likes to be tested when they are unaware that it is taking place. Yet everyday people go to work and make a contribution to their eventual evaluation. Shouldn't science be given an evaluation from time to time?

It is time to evaluate science on a grander scale than ever before. The reason is because science is operating on a grander scale than ever before. And lately things have gotten out of control. The drug money coming in has made some serious alterations to what was once considered science. Asking the drug companies to be honest about their drugs is like asking Delmonte to be honest about the quality of their canned pears.

The "Two Cans of Pears" scenario has a way around claims that one is superior to the other. You simply have to stop looking at the label and put a bar code on the can. Likewise, drugs need to have a non-marketing label. The motivations of drug companies must be taken out of the picture. The current model for clinical trials is often to have the drug company run the trials, analyze the data and report to the FDA. There needs to be a way to get the data points analyzed prior to any knowledge of what group they belong to. In other words, we need blind trials in the true sense of the word blind. The drugs need to be tested like a tin can that contains pears. Analyze what is inside and make your judgements. When it's done, take a look at the marketing label. Not before.

Wednesday, August 16, 2006

30 Million for a New Airport

The people of Florida have never read The Cargo Cult Scientist. They are debating whether or not to shell out another 30 million dollars to Scripps Research Institute. The Torrey Pines Institute for Molecular Studies wants $21 million in county money to put its headquarters in Boca Raton, creating 189 jobs. Scripps and IBM want $9 million to help establish the world's fastest supercomputer to battle avian flu, creating 42 jobs. That's 30 million to bring in 231 workers earning an average of around 56 thousand dollars per year.

Of course local governments want to attract business, create jobs and stimulate the economy. The question is whether or not Biotechnology is the industry to invest in.

Boca Raton Commissioner Burt Aaronson noted that in 2003, the county's $200 million-plus pledge to Scripps was supposed to spark a biotech bonanza. Scripps "was supposed to be the magnet, bringing everybody here," Aaronson said. "Evidently, they're not that magnet. They bring people here asking for more money."


The same thing has happened all over the country. Biotechnology was supposed to be huge. In some areas it has been. Amgen and Genentech have generated jobs at a staggering pace. Overall however the industry has been a disaster. Maryland put up 20 million dollars to set up the Gallo Institute for Cargo Cult Alumnus Bob Gallo. Gallo had predicted 350 jobs and to be self supporting in a matter of a few years. Three years later he had 90 employees and was still dependent on tax payer money. All of his spin off companies were flops. In Seattle Paul Allen has developed a plan to bring Biotech to the South Lake Union area. So far no one has come. Even Lincoln Nebraska has started an organization to bring the industry to the cornfields.

It takes a lot of money for a company to succeed. The success of their products in human bodies is another story. What the local governments are asking for are Cargo Cult Airports hoping that the better the airport, the better the chances are of getting some cargo. It takes money even if you have a good drug. Very few biotech companies have any drug at all. They come with promises of a new and innovative technology that will change the way people look at drug development. They are all world leaders. They all promise big things. And they all come asking for money.

Florida is getting wise. The Biotechnology industry has become very good at obtaining funding. Everyone wants in on the success. But what brings success? Money? Money is suppose to go into the big idea that generates more money. However, it seems that the only money being made are by those who work for the companies who gobble up the capital. Florida is making a big step today. Scripps has been around a long time. Is it in their track record that they generate profits for the local economy? Is it worth the investment?

Tuesday, August 15, 2006

John Darsee, Cargo Cult Alumnus

The case of John Darsee teaches us an important lesson here at the Cargo Cult Scientist. He was indeed a Cargo Cult Scientist in the area of heart damage. He worked at a top laboratory in a top institution, at Harvard Medical School, and he had published over 125 research articles, book chapters, shorter papers and abstracts. His boss at Harvard had authored more the 600 papers. These guys were accomplished at the one thing that will speed up any career in modern science, getting published.

Getting published requires skill in understanding what people want to hear and how to write about it. That doesn't mean that you have skills in scientific research, merely writing up what people want to hear. Those who accept or reject your paper will not be going into the lab to watch you work. Nor will they require any evidence that you actually did the work such as lab notebooks or any other form of raw data. The powers that be will read what you send in and use their superior knowledge of, well... reading papers, to determine if what you said is the honest truth or not. Furthermore, they will also know if you used all of the proper controls and formed the proper conclusions. Getting published means getting into the heads of these sorts and writing a paper that they can stand behind. It must then support their own theories, flatter their own body of work, and be authored and co-authored by respected individuals working at respected institutions and universities.

John Darsee and his boss Eugene Braunwald certainly had what it takes to get published. 109 of Darsees papers had 47 co-authors so there were plenty of people verifying the work. Yet Darsee managed to fool them all. He had fabricated data for many of his publications. In one startling case he proposed that a 17 year old subject had four children, ages 8, 7, 5, and 4. Eugene Braunwald didn't see it. The co-authors didn't do the math that would make the father 8 or 9 at the time of his first childs birth. The referees who read the paper didn't see it. The editor didn't see it. The readers of the article didn't see it either. Not until the notorious NIH duo Feder and Stewart got involved did anyone bother to bring up this puzzling set of data.

But not everyone was convinced that John Darsee was infallible. At Harvard three of Darsees laboratory colleagues started to wonder where he was getting all of the good data. They soon became convinced that he was outright making it up. They reported their suspicions up the chain of command forcing Darsee to finally show his superiors some raw data. Back in the lab he set out to obtain the final set of data to be presented. With co-workers looking on he began to mark down his data, Day 1, Day 2..., thus demonstrating his most effective method of obtaining positive data. You just make it up as you need it.

Three laboratory workers uncovered what 47 co-authors, scores of superiors and journal editors could not see. John Darsee was a fake. But he was a skilled paper writer and that is what made him a star early in life. The culture still exists. It is of course, The Cargo Culture, that we are interested in here on this blog. John Darsee is a high ranking member of the cult. He knew absolutely nothing about airplanes but he knew what the leaders wanted to hear. Not the sound of airplanes coming from the sky, but the sound of their own ideas being backed up by a bright young Cargo Cult Scientist. They sure did have a good run.

Where did the truth come from in this story? The laboratory. It's a tough place to be for Cargo Cult Scientists. If you want to make it in the ranks of the Cargo Cult, stay out of that lab.

Wednesday, August 09, 2006

We'll Do It Anyway

Science 9 July 2004:Vol. 305. no. 5681, pp. 158 - 159DOI: 10.1126/science.305.5681.158

News of the Week

OBESITY RESEARCH:Labs Fail to Reproduce Protein's Appetite-Suppressing Effects

by Trisha Gura

"In an unusual joint letter in Nature this week, more than 40 scientists announced that they cannot reproduce the central findings of a 2002 Nature paper that showed that a molecule called peptide YY3-36, when injected into rodents, dampens appetite for 12 hours or more."

AFX News: March 2, 2006

"...the Bothell, Wash.-based company said Merck terminated its agreement with XXXXX on March 1 after determining that earlier clinical data had shown PYY3-36 wasn't effective.

Regardless of Merck's decision, XXXXXX said it intends to pursue development of PYY3-36"

August 14, 2006

"XXXX announced today the initiation of a dose ranging study designed to evaluate the pharmacokinetic parameters, appetite, food intake and safety of various doses of XXXXXs proprietary PYY(3-36) nasal spray in obese subjects."

Here we go!!! Get ready for another study!!!

Aug. 14, 2006 PRNewswire-FirstCall/ XXXXX announced today the initiation of a dose ranging study designed to evaluate the pharmacokinetic parameters, appetite, food intake and safety of various doses of XXXXX's proprietary PYY(3-36) nasal spray in obese subjects

By the way, if it works 2 out of 20 studies, does it count? Since the FDA is not a close follower of the ways of science, they will allow it. The question is how well it will work this time and if it doesn't, what will comapany XXXX do? Remember, the decision to continue on with PYY was listed as number 4 on "The Five Dumbest Things on Wall Street This Week" by Colin Barr back in March of this year, 2006. We here at the Cargo Cult Scientist will stick it out to the bitter end. We will never give up until the airplanes either land or the cult gives up it's latest ceremony.

Another Case

In my last post I presented the reader with an actual case of scientific misconduct. This kind of misconduct occurs everyday in industry and academia throughout the land. It is the kind of dishonesty where you get to select what data gets used. It happened to the doctor I spoke about who worked with Actonel data. It happened around me at a previous company involving siRNA and TNF alpha. I wanted to open up a discussion with other people who may be feeling guilty about the work they do. How many others put up with this sort of data mishandling? How many actually orchestrate it?

I believe I could come up with a case of similar misconduct from every position I've had except for one. That is to say, I think it's the most common form of Cargo Cult Science. People have lives to lead. They earn the money for those lives by working in science. If you run an experiment 10 times and only once do you get the desired results, you may disregard the other 9 experiments. You may choose to not report them. No one will find out most likely so you keep you mouth shut. The scientist who manufactures data most likely ran his or her experiments more than 10 times but never got the desired results.

Imagine however, if you truly could clone a stem cell. Imagine if you got the desired results because you were right about something. You know what? That still doesn't make you a scientist. You got lucky. Getting the desired results comes from standing on a large volume of information that lead you to design and conduct a proper experiment. Maybe you failed 900 times but each time you learned something. Each time you got closer to the truth. This is real science. Failing is good if you are prepared for it. If not you will be fabricating or selecting the data you want. Either way, you are a fraud.

This next case describes a way around selective data. It involved a protein purification. The goal was to purify a protein to make an antibody. Since there was no antibody available I used a few basic techniques. In the end I had 3 bands on my gel, which to some indicates that I have 3 proteins. What I did showed that there were at least 4. I would guess many more.

The 3 bands were all very close together indicating that there were three major sizes of protein purified. To further separate the bands I ran them on a higher percentage gel. They were still too close together. The cubicle scientist needed one of the bands to be the protein we were after. He merely wanted to be able to point to which band on the gel was the one. He wanted to show the gel and then a western blot of the same gel. The western blot would indicate which band was our protein but the bands were still too close together.

Out of the blue, a passing technician solved the problem. Our protein was glycosylated. Simply run a PNGF digestion, which would deglycosylate the protein, and run the gel and western again. This time the 3 bands showed up at the same location on the regular gel. On the western however the band shifted down well below the three major bands. This meant that none of the bands represented the protein we were after. Furthermore, there was no band on the gel where the western blot band was located. That means there was not enough of the protein to be visible on the gel.

Now the western blot varies in sensitivity. This particular western was very sensitive. As a young technician who had done at least 100 of these westerns by this time, I felt that the 3 bands were too big to give the kind of western results we were getting. The western would have showed a huge black blob up and down the western. Instead it gave a neat little band. What I learned from this was that many proteins migrate with others there size in a gel. A band is probably an aggregate of proteins close to each other in size. The amount of proteins it takes to make a visable band on a gel can be hundred and thousands of times more than you would need to get a nice sharp band on a western. Indeed I learned a lot from that experiment and how to look at these gels that so many use in there research. Each protein antibody combination differs when it comes to western blots. There is a cut off level where slight changes in concentration either way will give big differences in band intensity. At some point they'll remain the same over a range of concentrations. At some point they will give high background signals. Some combinations will detect the protein all throughout the lane but show a blob where most of the protein is.

I also learned that this experiment was not described by the cubicle scientst. He insisted that I give an answer as to the percentage of purity I had acheived in spite of the fact that we both had access to the whole set of data. I came up with less than one percent as my answer. He reported 20 percent. To back this up he showed the gel with 3 bands on it. He showed the western blots and said that it could not be determined which band was the protein of interest but the western proved that it was one of the three. They were just too close together to discern which one it was.

So he lied. He did not manufacture data but he did select what he needed. Furthermore, he left out the data that proved his conclusion to be wrong. I hung my head but I was powerless to change his report. I was out of the picture by now and just a lowly technician. Oddly enough, when the antibodies started showing up we found a few that were specific to the protein. It didn't matter that 99 percent of what I sent out was not the protein of interest. What little there was gave rise to specific antibodies to our protein. No harm not foul right? No one will ever know what happened.

Tuesday, August 08, 2006

Actual Case

Let's take a look at a real Biotech research project. We'll break it down piece by piece in laymans terms. I want to make this as clear as possible. (Do scientists ever think this way?)

TNF alpha is a popular drug target. There are three monoclonal antibody drugs against TNF alpha already on the market. TNF alpha has a number of functions and most of them are not known. I won't discuss the science behind our understanding of TNF alpha. I will say that there are three drugs against TNF alpha. They are intended to alleviate rheumatoid arthritis and Crohns disease. The drugs reduce the effects of extra TNF alpha in the body by binding to it thus preventing it's usual interactions.

Another way of getting rid of TNF alpha is to use siRNA. DNA makes messenger RNA which makes proteins. If you take a small piece of the RNA however, it can result in the destruction of the messenger RNA by a newly discovered mechanism called RNA interferance. That's the story anyway and biotech is sticking to it. So if you want to start a biotech company you can choose TNF alpha as your drug target and siRNA as the way of zapping your target. It's that simple.

There appears to be only one company attempting this simple thing. They have over 200 mice sitting in formaldahyde waiting to be "scored" for arthritis. "Scoring" is an arbitrary method of measuring joint inflammation. The bigger the inflammation the higher the score. The goal then is to get as low a score as you can. You start with mice that have been bred to have high levels of arthritis or high scores. You use one of the antibodies as a positive control and a saline solution as a negative control. You also have a "scrambled" siRNA that has a nucleic acid sequence that is not linked to any known protein.

The mice, as I've stated, are still in formaldahyde. They have not been scored. The reason is due to an obvious lack of efficacy. Even the anti-TNF alpha control mice had developed arthritis. So big deal. It didn't work. The only place you will here about this is here on the Cargo Cult Scientist. I can't tell you what company did the experiment because I once worked there and I don't want any reprisals from them. But what they did with this experiment is wrong. The committed a cargo cult sin. They didn't report the results because they didn't get what they wanted.

In mainstream science they are struggling to define scientific fraud. Where is the line between fraud and sloppy practices? There are cases for example where a researcher will make up data. That is flat out fraud. There are cases where one out of ten experiments obtains the data that is desired. Using the favorable set of data and ignoring the rest is a lesser offense than manufacturing data. Yet to the Cargo Cult Scientist it is as bad. The only data that is useful is data the can be reproduced. If you sit in a board room or you are an editor of a journal you may not be aware of how many tries the researcher attempted before getting the data that supports his paper. This is a shame. If you are a lowly lab tech you probably know what is happening but you are powerless to stop it. It probably doesn't even matter in the big picture. Like the TNF alpha story I've just reported, most projects will fade away. The trick to being a Cargo Cult Scientist is to make sure that happens smoothly. As long as no one finds out about it you live to write another paper. Whether or not anyone uses that paper is another story. The chances are that no one will ever use siRNA to relieve the pressures of having excessive TNF alpha in their bodies. It won't matter however. There are plenty of drugs in the pipeline. Mostly they are me-too drugs. The research was me-too and the fade away will be a me-too method of resolving the scientific dilemma. Brush it under the rug and no one will know about it.

Perhaps this is why it's best to lab personel powerless.

Sunday, August 06, 2006


Bob Schieffer, on Face the Nation this morning, said that the difference between a Totalinarian government and a Democratic government is that all of the news you get about a Totalinarian government comes from the government. In a Democratic society you have a free press to offset government spin.

What then do we make of the scientific press? Cell, Nature, Science and all of the other publications at times like to blur the lines between reporting science and being science. They often come across as the authority between what is fact and what is not. However, they have been duped time and time again with little recourse. They self police themselves and thus they are sciences self police force. If fraud or misconduct is caught a retraction is in order. How often does that happen however? Is there another source that can report contrary information that, while it is not a retraction, is an alternative explanation of the facts?

The current model of science represent a totalitarian system of governance. You have researchers, professors, principle investigators, reviewers, editors and so on. Who is the leader? How is science structured to keep bullshit from creeping into the fabric of its daily operations? A democratic society will wage war against liars and cheaters who want to use our resources for their own purposes. We must constantly update our laws. We must seek out scams that are draining our tax base. Science too needs leadership to prevent negative factors. It must begin with a free press that is allowed to speak out against what is considered bad science?

What if there were scientific articles written about Dr. Hwang's cloned stem cells? Articles on how we are simply taking his word for it? Articles asking the questions that the reviewers did not ask? Ariticles from people trying to reproduce this work? There is in fact a great oppportunity to create a more mainstream interest in science by discussing the claims made in Science, Nature and the rest of them. They of course will tell you that they police themselves. Furthermore, they are science and any commentary from other scources is simply chatter from the peanut gallery. Amateurs don't have the same rights as the professionals. But isn't this the same attitude of a totalinarian government? They run the show. Anyone not involved doesn't understand what they do and thus have no rights to discuss the details. It leaves the leaders too much room for corruption however.

Science needs more voices, more ideas freely floating around for all to discuss and think about. With the onslaught from the pharmaceutical companies and the financial pressure for certain outcomes, science is up against the wishes of a non-scientific powerhouse. They want science to say what they want to hear. But science isn't about individuals. It doesn't matter where you went to school or how much money you have. It's about getting to the truth. The way to do this is to open up the process to all people and to hear what they think. What does the research associate working at Pfizer think about his project? What results has he seen that perhaps didn't make it onto a report? What about researchers who have disagreed with a papers conclusions? Does he or she get a voice? There must be a place for these voices. Is it just going to be the blogging world, where no one reads anyone elses stuff 99% of the time? Who will fight against sciences totalitarian system and let others be heard?

Friday, August 04, 2006

Failures to Follow

I've mentioned that Cell Therapeutics spent over 878 million dollars put one drug on the market, which they sold for 70 million. They are left with one more candidate that will make or break the company. So far the drug has failed miserably in clinical trials. What other companies failed, how much did it cost and what was learned?

Cancervax was a one drug company. Their drug was a cancer cell that displayed over 20 antigens that would provide an immune response that would rain hellfire down on a tumor. That's what they said at least. It failed clinical trials and the company folded. The drug itself was 20 years in the making. How much money went into the notion that this would work? The answer to that would be hard to sum up. Let's just assume it's over 100 million dollars. The lessons learned are also not clear. This sort of thing happens all the time. This month in biotech:

PDL Biopharma Inc. Reports Results From Phase 3 Trial Of Terlipressin In Type 1 Hepatorenal Syndrome - Did Not Meet Its Primary Endpoint

NPS Pharmaceuticals faces a class action suit for making allegedly false statements about the prospects of osteoporosis drug PREOS.

Icagen Inc. said Friday it is cutting out approximately half of the patients involved in a late-stage study on the recommendation of an independent data monitoring committee. The announcement sent shares in a nosedive, dropping $3.26, or 77.1 percent

Takeda Pharmaceutical has informed BioNumerik Pharmaceuticals that it is considering terminating their alliance over Tavocept after the drug candidate failed to meet the primary endpoints of two phase III trials in cancer patients.

You get the idea. Many big ideas turn into dust and alot of money disappears. There are of course a few success stories. The Cargo Cult Scientist however is a study on things that don't work. It is meant to be an exercise in striving towards the positive, starting from the negative. The negative being things that don't work. What is so shocking about making drugs is how much money gets dumped into things that don't work. I began this post by asking who failed, how much did it cost and what was learned. The answer is that every month there is going to be a number of big projects that fail, costing millions and millions of dollars, and nothing is being learned from it.

The Cargo Cult Scientist has learned something about PREOS however. The active ingredient in PREOS is parathyroid hormone (PTH). Forteo is also a PTH drug that is on the market. There are still other PTH drugs trying to make it to the market as well. How will we know if they will make it or not? We at least know a drug containing PTH is not gaurenteed to work. Curious. It is highly possible that a new clinical trial could show PREOS to be effective. What seems to be not working here are clinical trials. This is the true Cargo Cult Airport. Clinical trial professionals are not very good at reproducing results. There is a need for reform but first we simply state the obvious, clinical trials are not run scientifically. How can we fix the situation and what is at stake? More later.

Thursday, August 03, 2006

The Doctor is Out

There is a doctor in England who received a 250 thousand dollar grant from Procter and Gamble. He claims that the company had denied him access to key data and then tried to ghostwrite his analysis of it. The doctor and one of his superiors were to evaluate the effectiveness of P&G's osteoporosis drug, Actonel. Their analysis was suppose to further demonstrate how Actonel affects women's bones and their susceptibility to fractures. The doctors superior (and cohort in this research) had already reviewed blood and urine samples from two previous P&G clinical trials of Actonel. The doctor was supposed to evaluate a third trial, with the aim of providing a final analysis of all three.

The doctor and his staff reviewed data from thousands of blood and urine samples from women with osteoporosis. They were blinded as to who had taken Actonel and who had been given the placebo. This is of course the fun part of science. Get you facts straight then open the envelope to see which group is which. Did the drug work. Procter and Gamble however didn't want the doctor to go that far. They had a ghostwriter who would take his information and use what was needed to publish a paper with a positive spin. They would be using his name on the publication but not necessarily his conclusions. The doctor repeatedly asked for the codes so he could properly interpret the results. They refused.

Ironically, P&G continued to pursue their plan to write up a manuscript using the doctors analysis which they expected him to present at the American Society of Bone and Mineral Research. The ghost writer would "help write up the Actonel manuscripts for publication" and the doctors name would be listed as an author. Noting that he and his superior could be guilty of scientific misconduct if they let their names be listed as authors without having seen the underlying data P&G came up with a compromise. They would let him perform his own analysis of his data but they would let him review what the company had worked out.

He went to their headquarters and saw what they were working on. On one critical graph on fracture rates, he noticed that 40% of the data was missing. He believed that inclusion of that 40% of data would have disproved P&Gs key message about their drugs effectiveness against bone fractures. As a scientist, the doctor could not allow this. After many months of trying to get P&G and the university to do the right thing, he decided to go public with his story. He was suspended from the University.

Wednesday, August 02, 2006

Why'd We Study So Hard?

If you've ever wondered how things could stray so far from reality you need only read Dilbert to gain some perspective. Dilbert was created by a disgruntled engineer who worked at Lucent Technologies. Frustrated with the way things were he lashed out with a comic strip depicting his daily work life. You laugh but you know it comes from real life experiences. It is the clash between scientists/engineers and corporate people. Many scientist/engineers know the pain of studying for a differential equations test and a physics test that'll be given on Monday and a statistics test on Tuesday. You walk past the frat house at 3 p.m. on your way to the physical chemistry test on Thursday and the frat brothers are already drinking beers in anticipation of a big weekend.

You think that they'll be sorry. Then you get a job and you reallize that those guys are running around with suits and ties and making decisions on your research budget. They cancel your request for a 30 thousand dollar a year research associate and they give themselves a 35 thousand dollar a year raise. They deny your request to give your current associate a 2 thousand dollar a year raise. The associate gets mad and sues the company. The same executives shell out 10 thousand dollars to defend against the lawsuit.

Worst of all however is the decisions that effect your scientific inquiry or your engineering designs. If you work in Biotechnology for example, you have a drug pipeline. Whatever project you are working on, the goal is to advance the drug towards the market. Here is what one blogger had to say about her job in the clinical affairs department of a large pharmaceutical company. "I've witnessed my industry manipulate, distort, subvert, suppress, and otherwise mangle facts in pursuit of increasing their consumption of the nation's wealth." You do not get credit for stopping a project that is going nowhere. You're job is to advance the project, not stop it. Executives make those decisions.

They are not teaching you how to mangle facts when you are studying for the big tests in college. Science, math and engineering are disciplines that have been advanced by people who have ignored their own hopes and dreams in order to see the world as it is. We learned about forces in nature and a little bit about how to discover such forces. The executives learned about people. They learned about being the best in a group. It has a lot to do with image. It's about looking good and speaking with authority, whether you have any or not. The current business model puts those skills at the top of the food chain. The geeky stuff that comes from science is only sexy when it's a break through. A vaccine for polio or the discovery of PCR will get you noticed. Verifying that the latest siRNA treatment is a bust will get you in the dog house.

So why do we study the hard stuff and work with the hard stuff? I believe that some people are simply wired that way. Some people can sit in meetings and talk about things that lead to nowhere and be satisfied that they've done work. Others aren't satisfied until the talking has ended and it's tiime to test out the theories. The latter prefers more doing than talking. There is a sense of satisfaction that comes from working as a scientist or engineer. It comes from thinking, applying, and seeing results. That's why we study so hard. Nature is tricky and you can't bullshit your way around it. If you're wrong, nature will find a way to let you know. A drug that doesn't work or a bridge that collapses are a couple of ways. You really have to let go of the notion that you will be rewarded financially. You have to be the kind of person who would pursue the cure for cancer even if you knew you would never receive the notoriety for it. Rather than dreaming of a big house and fancy new car, you dream of the day when you do that mouse experiment and you see with your own eyes that the tumors did not grow. You don't want to sit in a board room and here about it from someone else. You want to be there. The only way to get that rush is to work as a scientist with a white lab coat.

Tuesday, August 01, 2006

When to Say When

"It takes a wise doctor to know when not to prescribe." - Gracian.

Modern day doctors sometime take the helm at large biotech/pharmaceutical companies. That creates an interesting situation. M.D.s have often taken it upon themselves to solve some of the mysteries of medical science. Scientists are trained to do the job but any reasonable person should be able to spot obvious things like Dr. Listers observation that washing ones hands prior to surgery cuts back on infections.

Dr. Louis Bianco is an M.D. and the CEO of a company called Cell Therapeutics. He decided long ago to prescribe a drug called XYOTAX. The patient was all of society. XYOTAX is a biologically enhanced chemotherapeutic that links paclitaxel, the active ingredient in Taxol, to a biodegradable polyglutamate polymer. The idea with this is that the glutamate will render paclitaxel inactive until it enters a tumor cell. Thus it would be the perfect solution for delivering this drug. The only problem is that XYOTAX doesn't work any better than paclitaxel alone. Nonetheless, Dr. Bianco is adamant on prescribing this drug to those who have cancer.

I think this would be a good time to not prescribe. It would be a good time to find another drug to invest in. What's stopping Dr. Bianco from making the obvious decision? As of March 31, 2006, Cell Therapeutics had incurred aggregate net losses of approximately $(878.5) million since inception. That's what is stopping them. Without the approval of XYOTAX, the company has no other means of generating an income.

878.5 million dollars of investor capital went into a company that is now sitting on roughly 80 million bucks and a potentially ineffective drug. Where did the money go? Who made that money in the process of getting the drug where it is today? If you've ever wondered about the figure of 800 million dollars to get a drug to the market, you have to figure in fiascos like this. Investors can be hoodwinked quite easily when it comes to science. The entire executive team at Cell Therapeutics have a reputation for being long on hype but short on results. Three years ago, James Bianco confidently predicted that XYOTAX would be on the market by 2005. He now claims that it will be done by early 2007.

CEOs and executives continue to reap the rewards from just working in the business. You don't have to have a good drug. You have to have the juevos to keep going back for more. You tell the investors, "next year, trust me," and if they bite, you are in business. The Cargo Cult analogy is clear, the promise of the airplanes landing is enough to get paid. In fact you can have a fabulously successful career and never have an airplane land.