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Mike Milburn, Incoming Metabolon CSO on Personalized Medicine in Metabolomics

Mike Milburn
Chief Scientific Officer
Incoming Metabolon

Name: Mike Milburn

Position: Incoming Metabolon chief scientific officer

Background: Senior vice president of Research and Corporate Development, Sirtris Pharmaceuticals, February, 2005 — the present

Senior vice president of Research, Plexxikon, 2001 — 2005

Education: PhD, Structural Chemistry, University of California, Berkeley

Postdoc, Harvard Medical School, 1991

Mike Milburn was recently hired as chief scientific officer of Metabolon, and Pharmacogenomics Reporter called him up to get his view of whether and how metabolomics would influence personalized medicine, and to get his view of the company's direction.

John Ryals, CEO of Metabolon spoke this week at the conference's section reserved for lectures on 'Metabolomics as an Indicator for Disease and Personalized Therapeutics.' Where do you see Metabolon and the field of metabolomics going, in terms of personalized therapeutics?

From my perspective, with mostly drug-discovery experience and pharmaceutical and biotech [experience], I think the level of understanding in pharmacogenomics or personalized medicine, with regard to genes, gene-expression analysis, and proteomics, is actually quite high. Obviously those technologies are continuing to develop as time goes on. But the ability to do the same kind of system-wide analysis with small molecules has been, somewhat surprisingly, lacking. And I think Metabolon is a company that has focused over the last two years on developing a high-quality platform that will allow one to look at — whether it's in serum or tissues or other types of fluids — being able to look at all the small-molecule metabolites.

The reason why I think that's incredibly interesting, and you can see it with many of our pharmaceutical partners, is they've been able to start taking the systems information about genes and about gene regulation, and once you start incorporating that with the ability to look at small molecules, then you start really developing a good picture of what [the] important genes [are] in a disease that can be related to the actual biochemical changes that are going on in a disease model. And of course, looking at disease and coming up with those disease biomarkers is something that we're very focused on with the small-molecule metabolite approach.

But at the same time, you can look at it in the same way with the toxicology of drugs, or with efficacy of drugs. In other words, you're getting biomarkers for the drug with gene analysis, or in our case with metabolite analysis. [It's] equally feasible, and [we're] working with a number of pharmaceutical partners to develop [it].

Do you see metabolomics having a future in predicting adverse drug responses, or in finding people who will respond to a particular drug?

I actually think both. What we're really focused on as a company right now, is to continue to deliver high-quality data to pharmaceutical partners, but also to develop diagnostics for particularly neurodegenerative diseases — [work] which we've been fortunate enough to get grants to support.

But I think, moving forward, the potential of using this same technology to apply to looking at the safety profile of drugs in certain tissues, or the safety profile of drugs in animals, and basically getting a fingerprint of liver toxicity or muscle toxicity, or neuropathies, and getting that biochemical signature and being able to relate that to new drugs and what their potential toxic effects might be. That [involves] going and gathering that database and running those experiments, and I think there's a pretty high level of opportunity there that will work very well.

You can carry the safety profile to the same in terms of therapeutic efficacy. So with this metabolite approach, you can develop the ability to get the metabolite signatures of what an inflammation efficacy might look like, or what a neuroprotection efficacy might look like, or what an anticancer efficacy might look like, and potentially even relate that to the magnitude of the effects. And then, one could start looking at the drug candidate effects in animals or in humans and start getting a better picture of how that drug's effects and safety profiles might look, relative to this metabolite database.

And I think that's something that we're keenly interested in doing, but that's a little bit down the road right now.

When do you expect something like that to reach clinical utility?

I think in terms of diagnostics, we're probably there. I mean we're working very hard with the ALS Foundation to deliver small-molecule biomarkers for [amyotrophic lateral sclerosis, or Lou Gehrig's disease], and I think the current studies that we've been doing are quite encouraging, and we've just been awarded a Phase II grant [from the ALS Foundation] to look at a larger clinical patient population size. So I think that's going quite well.

One of the advantages of looking at the metabolites is, when you think about the number of human genes being on the order of tens of thousands, and when you think about the metabolites probably being a more manageable set, I think it's a type of technology that can move quite quickly relative to what had to take place in terms of gene-expression analysis, and so forth. Some of the instrumentation, particularly around mass spectrometry, is advancing — you need the software to hook up to that mass spectrometry, and it's something we've been able to do. It allows for a more automated way of looking at these metabolites, and my feeling is that that analysis with this relatively smaller set of small molecules is going to be something that can move quite rapidly.

Are you bringing a new direction to the company? Do you have special ideas for it?

I think the one thing that I bring to the company is having a lot of experience, both in a pharmaceutical setting in terms of drug discovery, but also in terms of the biotech setting, where you're focused on delivering a product as rapidly as possible, and utilizing all the best technologies available to do that. And I think when you do that, you focus like a laser on [what] the key experiments [are] to advance a drug. And I think having that kind of perspective, hopefully, will be advantageous to Metabolon as it starts to try to deliver these high-quality technologies for disease diagnostics or for drug efficacy, or for drug safety kinds of analysis.

In addition to its work with ALS, what diseases and drugs will Metabolon focus on?

I think one of the things we're interested in is using this technology in particularly debilitating diseases that are real unmet needs, such as ALS, Huntington's [disease], Alzheimer's [disease], the neurodegenerative diseases. These are diseases that still are in need of treatment, and this type of technology could enable not only diagnostics, but ways of looking at molecules that are very difficult in neurodegenerative diseases.

In addition to neurodegeneration, we're also very interested in cancer and metabolic disease, but we have an initial focus, and we've been fortunate enough to get a lot of support in those neurodegenerative diseases.

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