Phalanx Biotech Group
At a Glance
Name: Charles Ma
Title: Chief Scientist, Phalanx Biotech Group
Professional Background: 2004-present, Chief Scientist, Phalanx Biotech Group; 1995-2004, Associate Research Professor, Columbia University.
Education: PhD, Molecular Biology, University of California, Los Angeles.
BOSTON — Charles Ma is the chief scientist of Phalanx Biotech Group, the Taiwanese array firm that garnered attention in June 2004 with the promise to commercialize its whole-human-genome Human OneArrays at an introductory price of $100 per array with a minimum total purchase of 100 chips (see BAN 6/9/2004), although the firm has yet to release the product.
He also spoke at IBC's Chips to Hits conference held here last week. His presentation, "A Push for Usage Expansion in DNA Microarrays — Cost and Standardization Issues," summed up the various trends in standardization that are about to affect the industry, and also addressed how a reduction in cost could make microarrays an affordable commodity. Ma said during his talk that one day high school students could look at a microarray experiment as something routine and boring.
BioArray News spoke with Ma shortly after his presentation to get his views on current trends in standardization, and how microarrays can make it from being a fairly exclusive tool to being a bench-top standard in college labs.
You said during your talk that you were surprised to be selected to give a presentation on standardization. Why were you surprised?
Well, we are kind of like newcomers to the field, and in a way, when you talk about standardization, you start with the longer existing people, so I am a little surprised that — since we are late to the market — they actually selected me to talk about standards. In a way we are just coming in. We are interested to see what kind of standards people are setting. So that's why I am a little surprised.
Do you think that gives you an advantage at least? That at the same time you are entering the market these standards are emerging so you don't have to go back and fix your old products?
It definitely will make our job easier because before, often what you'd have is that you would not be sure whether you are ready or not, because the quality [of microarrays] varies so much, so what do you really need to be a good product?
You can range anywhere from saying, 'Well, are we going to the homebrew market or are we going with the big guys?' But at least there will be some standards and sort of give us an opportunity to evolve ourselves a little better, and say, 'OK, where do we stand? How do we compare?' But at the same time it means that if we are not there, we will know also.
There are a number of different organizations working on standards at this time. Do you feel any of them are particularly significant?
I think they all are because they complement each other. For example, the External RNA Controls Consortium is selecting the external control transcripts so that will be the probes put on an array, but the US Food and Drug Administration's Microarray Quality Control project will be developing which RNA sample you use as a standard — so you can standardize both sides, they sort of complement each other.
Do you think they will be adopted quickly or will it take awhile for them to take effect?
My personal feeling is that it will take awhile. At this point I think MAQC is moving along, they already have some progress, they have already given all the samples to labs. But I think, in the end, the [greatest] problem will probably be that all the platforms are so different to begin with. For example, the probe length can be anywhere from 25-mer to 70-mer. And that can be something where you start right off the bat where there's a difference. That's just one reason why I think right away it will be a very long process.
Are there any platforms that you think are better suited for adopting these standards at this time?
Well, you can look at it a couple ways. One is that definitely the more you know about one platform you have more data to evaluate and compare it to. Of course, that means whomever is first on the market has the most data, so definitely there is an advantage there. But that alone may not be enough, because other platforms do have their advantages that you cannot ignore.
So it will be a very complicated process, there's no clear advantage one way or the other. I don't think it's going to happen that there will be one platform and everybody will compare it to that platform. It will be more for simply comparing between different platforms. To me the thing about standardization is not to have one standard, but to know what the difference is between the platforms. It makes the difference between very different platforms clear, so people can make the comparison. So that would be the kind of standardization that I am thinking about. Right now, it's like you have no prior knowledge, so you just judge on other reasons, how expensive, et cetera.
How is your platform coming along at the moment?
I could tell you, but the marketing guy would kill me [laughs]. For me it's mostly science. Definitely I can say that our approach to this is to be very cautious and make sure we're ready. Definitely since I am here, you know we are not thinking too far along the line. It's in progress.
What, in your opinion, would be some obstacles to making these standards global?
[The people creating the standards should] try to get as many people involved worldwide. Then you can definitely reach an agreement easier. But if there are enough big users that are left out of this, then they may not feel obliged to follow them. The worst thing would be if all of these things came out and people said, 'Well, you didn't ask me, so why should I follow them?'
Another idea you touched upon in your talk was the idea of microarrays as a commodity. Why do you think that idea is rarely mentioned anymore?
Well, the reason that idea doesn't come up anymore is because it's so expensive. Right now, definitely with the price I wouldn't think of it as a commodity, [if I did] I would be out of my mind. What I am talking about is that is the way I hope that we can push this whole thing, into a commodity. So basically the idea would be at some point it would be something so routine, that I can imagine that there would be a day that, say you are a new principal investigator, you get your seed money from the university, and you say, 'What are the 10 things I need in my lab that can get my lab running right away?' And a scanner and a microarray will be high on the list. It also will be part of the essentials of a lab. It will be something any normal lab will be using. Of course that's very far down the road but I hope that we can push the technology toward that line.
Is it becoming less exclusive in your opinion? Are more people using it?
I think more people are using it, but it's in a way that's different from what you would think. Yes, it's less exclusive, but basically what that means is that there are still the haves and have-nots. The [users] are still the rich labs. So, yes, you do have extension of usage, but it's still exclusive to many other labs. If you [look at the number] of publications going up you can see what is happening — initially growth is exponential, but we are starting to hit a phase where it is going up, but not at the explosive rate you had before. Basically that means that we are slowing down and at some point, if that does not change, we are going to hit a wall. Because somewhere along the line growth is going to really slow down.
During your talk, you gave an example of high school students using arrays in the future. When do you think that could happen?
Actually, if I had to guess, I would say five to 10 years. Let me give you an example. When I was in college [I was in] some college laboratory course — and we were all disappointed because everything looked so routine, like cloning — you have to remember this was 20 years ago. And the professor sort of noticed that we looked so disappointed and he said, '10 years ago all of these experiments were Nobel Prize-winning experiments.' But the experiments had become so routine that even college students felt bored by them. So, when you think about it, the professor was right. So I can see it coming.
And the nice thing about [that] is that that kind of expansion is actually less complicated than, say, going into diagnostics. As far as microarrays for research, as far as the general tools are concerned, I think there are actually less restrictions on that part. Just using it as a research tool or using it as a way to teach biology [could work]. You tell people that there are 30,000 genes in the human genome, [and] they have no concept. But [if] you show them, 'Here are the genes, and they are being expressed up and down,' they get the picture.