Bio & Life Sciences

Do We Get Sick Like Rats? A New Philip Morris Prize Asks the Crowd

It might be surprising to hear a tobacco giant described as a tech innovator. But Philip Morris researchers are pioneering new territory with a crowdsourced approach to checking the accuracy of life sciences data.

In partnership with computational biologists at IBM’s Watson Research Center, Philip Morris’s so-called sbv IMPROVER project creates open challenges to encourage scientists to augment traditional peer reviews of research data. On Monday, Philip Morris launched its Species Translation Challenge, which will award three $20,000 prizes to teams whose results best define how well rodent tests can predict human outcomes.

Similar competitions have emerged in the academic world, but sbv IMPROVER (short for “systems biology verification of industrial methodology for process verification in research” in case you were wondering) is the first that taps the crowd to verify industrial research. An initial challenge last year awarded $50,000 to two Wayne State University researchers who proved best at confirming genetic features that could be considered “diagnostic signatures” for particular diseases.

sbv IMPROVER at a Glance (via www.sbvimprover.com)

sbv IMPROVER at a Glance (via www.sbvimprover.com)

Why is a cigarette manufacturer sponsoring such competitions? “Our number one objective is to do something about our dangerous products,” says Philip Morris scientific communications director, Hugh Browne. (The company is known for its periodic candor about such matters, even as it continues to dominate the industry.) From heart disease to cancer to emphysema, the potential consequences of smoking are well known. But not every smoker suffers all or any of those health effects, suggesting that a combination of environmental and genetic factors lead to disease.

To understand precisely how smoking and chewing tobacco leads to complex interactions in a user’s biological systems, “Philip Morris is increasing its investments into systems biology,” Browne says. The company is looking at networks of genes, proteins, and biochemical reactions to identify the exact biological mechanisms perturbed by smoking.

But such biological data is notoriously complex to analyze. The profession as yet lacks any standard methodology for verifying results, and traditional peer-review methods have “struggled with the volume and complexity of the data,” according to Philip Morris.

IMPROVER breaks research workflows into components and asks the crowd to apply its own computational methods to verify results. IBM computational biologist Gustavo Stolovitsky says the project “provides an excellent platform on which to test and develop some of the most cutting-edge approaches to the analysis of high-throughput biological data.”

The 2012 IMPROVER challenge asked participants to identify signs in a patient’s set of transcribed genetic material that could be relied on to diagnose any of four diseases associated with smoking: psoriasis, multiple sclerosis, chronic obstructive pulmonary disease, and lung cancer. Competitors looked at clinical data from patients—some of it licensed from third parties and provided by Philip Morris; some from the public domain.

More than 50 teams worldwide competed in the challenge that the Wayne State researchers won. Says Ajay Royyuru, director of IBM’s Computational Biology Center in Yorktown Heights, NY:  “There was a refreshing variety of competitors.” The most successful applied fundamental understanding of biology “rather than brute force machine learning,” or automated big-data analysis methods. “Some came at it from a mathematical modeling approach, others came from biology, and others combined those,” he continues. (The Wayne State team comprised a bioinformaticist and a perinatal researcher.) Royyuru adds that the challenges can provide young scientists without scientific publications under their belt with a way to get recognition, and computational biology startup companies with a way to showcase what they can do.

A team of IBM computational biology experts scored entries, and a five-man outside panel reviewed the scores. While no single team identified the data perfectly, the leading methods, considered in the aggregate, performed exceptionally well, Royyuru says.

The new challenge launched this Monday seeks to determine if gene expression pathways identified in rodents will predict the same in humans. Scientists typically rely on them to study the impact of products on consumers, even though it remains unclear how well rodent results translate to humans.

Four sub-challenges ask participants to determine 1) if the way signaling pathways in one species react to a given stimulus really predicts similar response in another species, 2) which biological pathway functions and gene expression profiles are most parallel in rodents and humans, 3) how much that depends on the nature of the stimulus or data type collected, and 4) which computational methods are most effective for inferring responses between species.

Competitors will get access to about 5,000 human and rat samples Philip Morris generated for the challenge, and will look at 57 stressors to a single cell line exposed at different time points.

Browne suggests that the IMPROVER approaches for verifying results could be useful as well in the pharmaceutical, biotechnology, nutrition, and environmental safety industries. And Royyuru sees the project as a step toward creating “a verification methodology that will become routine industry practice.” Who knows how Philip Morris might utilize the outcomes? For better or worse, they may seek to create safer tobacco products.

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4 Responses to “Do We Get Sick Like Rats? A New Philip Morris Prize Asks the Crowd”

  1. Yul Dorotheo says:

    More than seventy years ago, tobacco industry scientists discovered the addictiveness of nicotine and the deadly harms of tobacco on health, yet tobacco companies decided for the sake of profits to deceive the public and keep that information secret. When the scientific community years later firmly established the addiction and health harms, tobacco companies not only denied such reports but also challenged their veracity so as to stir up controversy and confuse the public, and part of this cover-up was the hiring of “independent” scientists and researchers, quite similar to what PMI is attempting again here. Are they really trying to develop “safer” products? That’s what they also said before, and they eventually concluded and begrudgingly admitted that there is no safe cigarette.

  2. Jon Krueger says:

    When Philip Morris was convicted of racketering, Judge Gladys Kessler noted a key offense was its manipulation of science to mislead the public.

    This industry for decades used science to obfuscate, not reveal. It went to such lengths that there is now a literature on that alone:


    Anyone who believes Philip Morris is a legitimate research partner, who lets their good name be used by Philip Morris, is, not to put to fine a point on it, a fool.

  3. Jon Krueger says:

    “Our number one objective is to do something about our dangerous products,” says Philip Morris scientific communications director, Hugh Browne.

    But of course nothing stops Philip Morris from doing something. It could do big things, right now, today.

    It could stop aggressively marketing its lethal product.

    It could stop engineering it for addiction and for initiation (“smooth smokes”).

    It could stop undermining tobacco prevention.

    It could stop its lobbying and litigation and PR campaigns that push up smoking.

    It could stop lying and stonewalling about what its product does to the customer and to the people closest to the customer.

    It could stop any and all of those things today. Right now. That would do big things. Would save lives.

    But it chooses to keep on doing these things. Because it puts its profits over people’s lives.

    And it pretends that more research is needed. Gosh if only we had more data.

    Of course it knows that’s nonsense. It knows exactly how it could reduce the harm its products cause. It chooses not to do that.

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