philosophy of science


Is Population Medicine Failing Us? Michel Accad

Is health the same thing for an individual as it is for a population? This question goes to the foundation of how we practice medicine today and that of most of genomic research.

Michel Accad is a cardiologist in San Francisco and the author of a new book, Moving Mountains: A Socratic Challenge to the Theory and Practice of Population Medicine, in which he uses Socrates to spar with Geoffrey Rose, a British physician and one of the architects of modern medicine.

As early as the 1950’s, Rose advocated for the idea that individuals should be treated based on bell curves of an entire population, essentially risk based medicine. This philosophy would lie at the heart of not only the British National Health Service but many public health programs. It informed the famous Framingham studies here in the U.S. In fact, the term “population medicine” is a very positive term for those working in healthcare today. Genomic medicine has been an outgrowth of population medicine.

Michel says this philosophy is failing us at the level of individual health. Third party payers, be they governments or insurance companies, are in their offices working a system based on large datasets. They develop algorithms using all kinds of risk studies. But these payers have little to no contact with the actual patients. Ironically, he says, we call it personalized medicine. Michel points to hypertension, a disease area where sixty years after Rose pushed for risk studies, cardiologists are still divided into camps over whether to treat a patient if their blood pressure lies above the average. Michel argues that population medicine is utilitarian and ultimately utopian. What are framed as scientific studies are really social engineering.

What about clinical trials, we ask Michel. Don't population studies bring doctors and patients many good drugs?

In the second half of the interview, Michel points out that a mechanistic view of biology dominates clinicians and scientists today. It’s true. Our guest last week, a well known geneticist from Stanford, compared people to cars, arguing for the need to wear health data gathering sensors.

"Right now among philosophers of science, there’s a recognition that “mechanism” is inadequate to explain cellular organisms."  The study of biology also has often been developed with tautologies, he says.  "For example, say you’re studying the beaver and you ask what is a beaver. The standard answer is to go to the genetic sequence. From the genetics, you say you have a beaver. But you have to know what beavers are in the first place in order to study a beaver. It’s a circular argument."

So what other models might we use in biology? And what can we do in healthcare if we’re not using large population studies--go back to blood letting?

(Amazon link)

Medicine and the Limits of Science with Michel Accad, MD

Are drug prices really too high? If so, how do we bring them down? Is precision medicine and the use of molecular profiles really making a difference in healthcare today?

These are questions that regularly haunt our industry and the journalists who cover it. But there will be no answers until we face the grand question of all, what today's guest calls the most nagging question in medicine: What is health?

Today we begin a new series focused on just this question.

When I came across Michel Accad’s recent blog, Why I Don’t Believe in Science, of course it provoked me to click. Either he would be a terrible nutcase, in which case I'd lose the time it takes to discover this, or it might turn out to be one of those disturbing points of the day when we have to actually do some thinking. What I found was a cardiologist based in San Francisco who was doing some deep philosophical thinking about medicine today. And, obviously, one savvy enough to get some click through. It turns out Michel does believe in science, but he doesn’t share the pervasive view that medicine is a continuum of science.

What are his thoughts about precision medicine? What is his definition of health?

We always jump at the chance to have a medical doctor on the program, and a doctor who is also a philosopher is a double treat. Today's interview takes us down a different path than our typical shows, and we'd like to invite the audience to send us your feedback by clicking here.

Who Do You Want to Hear From During the Holidays?

It's a tradition at Mendelspod to bring you unique shows that go off the beaten track at the end of each year. In the past, we've brought you interviews with a science historian, a science comedian, sci-fi writers, and futurists.

We're just planning our lineup for holiday season 2014, and we want your suggestions. On the list so far are a philosopher, a popular sci-fi writer, and the former Deputy Director of the NCI.

Make your suggestions here.

Thank you, Theral & Ayanna

What a Physicist Can Tell Us about Cancer

Guest:

Paul Davies, Principal Investigator, Center for the Convergence of Physical Science and Cancer Biology, ASU Bio and Contact Info

Listen (4:05) The phone call

Listen (3:39) Too focused on a cure

Listen (8:21) What is your theory about cancer?

Listen (4:55) Evolutionary roots of cancer can suggest new therapies

Listen (3:31) Is your message taking root?

Listen (5:21) We must have new ideas

Paul Davies has had a full career as a theoretical physicist. He’s the author of some popular books, most notably, God and the New Physics. In 2007 Paul received a call from someone he’d never heard of before, Anna Barker, then the Deputy Director of the NCI. She wanted to recruit him to the War on Cancer.

“Anna said that she felt that physicists had been very successful in their own sphere. They figured out how the atom works and how the universe works. What about figuring out how cancer works. My reply was that I didn’t know anything about cancer. And she said, 'that’s fine.’”

In today’s interview Paul explains the theory he has developed by following cancer back to its evolutionary roots.

“Cancer is a reversion, or throwback, or rewinding of the evolutionary clock at high speed,” he says.

And therefore, looking at the conditions of life and of the earth at the time cancer developed, Paul argues, can offer new ways of developing treatment. Paul says that we’ve been too focused on “the C word” or a cure. He thinks that rather, we should look at ways to be able to delay cancer.

Is his message taking root? Join us as we probe an entire new way of looking at cancer.

Podcast brought to you by: Chempetitive Group - "We love science. We love marketing. We love the idea of combining the two to make great things happen for your marketing communications."

The Story of Aubrey de Grey and How the Study of Aging Became Mainstream

Guest: Aubrey de Grey, CoFounder, CSO, SENS Research Foundation

Bio and Contact Info

Chapters: (Advance the marker)

0:35 First Rejuvenation Biotechnology Conference

4:50 Shackled by “short-termism”

6:00 Aging was not a topic for biologists

11:32 A serious nuisance

17:13 Smoking out the opposition

22:05 Is the body really a machine?

24:52 The community takes a longer view

30:15 What is your challenge today?

Gerontology, or the study of aging, was a “backwater” science when Aubrey de Grey began his career. Today there are well financed companies with the word "longevity" in the name (i.e., Craig Venter’s latest project).

Today we bring you the story of Aubrey de Grey—scientist, author, provocateur--and how he became one of the world’s leading gerontologists. Currently CSO of the SENS Research Foundation, Aubrey tells how he went from working in artificial intelligence to the leader of a new movement in biology. Thrilled that the research community has “come to him,” Aubrey finishes the interview by explaining some of the challenges he faces today.

Podcast brought to you by: Chempetitive Group - "We love science. We love marketing. We love the idea of combining the two to make great things happen for your marketing communications."

Why Internet Traffic Directors Should Sit Down with Biologists: George Poste Talks Complex Systems

Guest:

George Poste, Chief Scientist, Complex Adaptive Systems; Regents’ Professor and Del E. Webb Chair in Health Innovation, ASU
Bio and Contact Info

Listen (5:51) A paradigm shift to systems thinking

Listen (4:28) Note to those setting curriculums

Listen (4:37) How do we bring the clinical and research worlds closer together?

Listen (8:53) Simulating complex adaptive systems

Listen (2:46) Science only one of the challenges

Listen (5:13) Why the disparity in reimbursement rates for Rx and Dx?

Listen (7:51) Something special happening at ASU

If you’ve ever heard a talk by today’s guest, George Poste, you’ve no doubt come away scratching your head, overwhelmed by the complexity of human biology. As if the science challenges don’t give one enough of a headache, George continues his carpet bombing approach with all that is wrong with our healthcare ecosystem as well.

Back in the '90s at SmithKline Beecham, George realized that the field was way overly reductionist and that we must do more to look at human biology as a system. He made his way to ASU where he then launched the Complex Adaptive Systems Initiative to bring together biologists, engineers, data scientists, and others.

What is a complex adaptive system and how can simulating it help us decipher human biology?

"A complex adaptive system,” George answers, “is one in which the collective behavior of the component parts cannot be predicted by an analysis of one or more of the these component parts.”

Whether you’re looking at global climate or intracellular wiring, George says it’s all about information transfer in a "network architecture."

The architecture of George’s way of speaking is also complex. With frequent use of the “dash”, George mimics in his own sentence structure the systems he’s describing. His syntax tends to bloom like a natural organism.

An example:

“The question now, then, is how can--by understanding the molecular pathways and coupling of those pathways—because we all tend to think in linear terms (you see the diagrams of a molecular pathway tend to be a series of straight arrows, but in fact what it is is a series of pathways that are interlinked)—because the one other feature of complex adaptive systems is that they have enormous redundancy built into them, so that if one bit goes down --you know it’s the classical model of the internet—if you take out a series of nodes, there are whole ways of distributing traffic around that . . . if you extrapolate that to cancer therapy, yes, you may knock out a particular node with your targeted therapy, but what you need to know now is what are the most likely network couplings of that particular pathway for the compensatory redundancy pathways which will kick in that will confer resistance on a cancer cell.”

Did you get all that? The internet is an interesting comparison. So if we bring together some of those engineers who work on routing internet traffic with some biologists they should be able to have a good time, right?

"Absolutely," George says.

As we conclude the interview, he acknowledges that there is something special going on at ASU, a new paradigm and openness to inter-disciplinary work that is unique. How is it fostered and funded? And what can we expect from this approach?

Fasten your seat belts and hold on for the ride. Suspend your need for short, easy sentences, and rewards await. Presenting systems thinker, George Poste.

Podcast brought to you by: National Biomarker Development Alliance - Collaboratively creating standards for end-to-end systems-based biomarker development—to advance precision medicine

Training the Next Generation of Bioinformaticians: Russ Altman, Stanford

Guest:

Russ Altman, Dept Chair, Bioengineering, Stanford University

Bio and Contact Info

Listen (5:32) A bioinformatician bottleneck?

Listen (4:19) Does the engineer or coder have enough basic biology?

Listen (5:04) Have we been overly reductionist?

Listen (5:16) Beautiful but useless algorithms

Listen (4:13) New breakthroughs in natural language processing

Listen (3:39) A new regulatory science

For our last episode in the series, The Bioinformatician Bottleneck, we turned to someone who has not only done lots of bioinformatics projects (he's been lead investigator for the PharmGKB Knowledgebase) but also one who is training the next generation of bioinformaticians. Russ Altman is Director of the Biomedical Informatics program at Stanford. He's also an entertaining speaker who's comfortable with an enormous range of topics.

It's been some time since we had Russ to the program, so we had some catching up to do. What are his thoughts on the recent philosophy of science topics we've been discussing? Are the new biologists becoming mere technicians? What is meant by open data? Etc. He warns of being too black and white when it comes to reductionism or antireductionism. And agrees that the new biologist needs quite a bit of informatics training. But he's not worried that all bioinformaticians have to be better biologists, saying that there's a whole range of jobs out there.

What's Russ excited about in 2014? The increased ability to do natural language processing, he says.

"We have 25 million published abstracts that are freely available. So that's a lot of text. Increasingly we're having access to the full text and figures. I think we're near the point where we'll have an amazing capability to do very high fidelity interpretation of what's being said in these articles," he says in today's interview.

Russ finishes up by talking about a new West Coast FDA center in which he's involved. The center is focused on a program for a new emerging regulatory science, which he defines as the science needed to make good regulatory decisions.

"This area of regulatory science," he says, "has great opportunity to accelerate drug development and drug discovery."

I saw Russ at Stanford's Big Data conference after our interview and asked him at what age he decided against Hollywood and for going into a life of academia and science.

"Who says I did?" he retorted without hesitation.

Podcast brought to you by: Roswell Park Cancer Insititute, dedicated to understanding, preventing and curing cancer for over 115 years.

Philosophy of Science, Part IV with Nathan Pearson: A Scientist Responds

Guest: Nathan Pearson, Senior Director of Scientific Engagement & Public Outreach, New York Genome Center

Bio and Contact Info

Chapters: (Advance the marker)

0:44 Asking the "why" questions

5:55 The biological editor

11:53 Has the language of biology limited us scientifically?

16:02 Latin vs. plain language

20:17 Presenting genomics to the lay audience

23:30 Has the reductionist approach been codified into the language of biology?

29:58 Do scientists listen to philosophers?

For the next segment of our Philosophy of Science series, we talk not with a philosopher, but with a scientist. Nathan Pearson has been a genome scientist at Knome and Ingenuity Systems, and just this month began with the cool title, Senior Director of Scientific Engagement & Public Outreach at the New York Genome Center. On today's program Nathan responds to some of the ideas that have surfaced in this series. How is the study of biology limited by language? Is a certain amount of reductionism codified right into the language of biology?

Nathan studied linguistics in college, so his knowledge of language is deeper than that of many scientists. But he's also part of the working industry of science. Starting with a discussion about the many ways language and biology intersect, Nathan explains how the history of language affected the study of biology.

Becoming aware of his own language in the interview, Nathan says that since Latin was first used as the language of science, we have always "prized the long flowery way of saying something as somehow being better than the one syllable--or beat [he corrects himself]--way of saying it."

He's against the flowery approach, and says there's a movement in science, law, and business toward using plainer language. And what is the argument against this transition?

"That it's less precise," he says, "which is fluff."

He recites several older Saxon words which are every bit as precise--and more impactful, he argues--as the latinate words. Gut vs. intestine and gullet vs. esophagus, for example.

That's all fine and interesting, but the big question is whether Nathan thinks language is responsible for an overly reductionist approach to biology?

The culprit is more math than language, he says. We end with a discussion about whether scientists even listen to philosophers.

While chatting about philosophy of science at a recent conference with Nathan, industry veteran Lee Hood walked by, and we threw some ideas at him. Always focused and in a rush to somewhere with a retinue following him, Lee nonetheless stopped in his tracks and demonstrated some enthusiasm for the topic.

"Scratch a scientist and you get a philosopher," quipped Nathan.

So we put Nathan in front of the camera and scratched him.

Podcast brought to you by: Chempetitive Group - "We love science. We love marketing. We love the idea of combining the two to make great things happen for your marketing communications."

Rethinking Biomarker Development with Anna Barker

Guest:

Anna Barker, Co-Director, Complex Adaptive Systems Center, ASU

Bio and Contact Info

Listen (7:54) Have we been overly reductionist in the study of disease?

Listen (6:32) Applying new knowledge about complex adaptive systems to biomarker development

Listen (7:09) The National Biomarker Development Alliance

Listen (3:05) What do you think of the 'Snyderome' model?

Listen (5:44) Confident that FDA will regulate LDTs

Southern Arizona is emerging as a hotspot in the world of diagnostics. And one of the leading lights there is Anna Barker, who has been bringing folks together to think about biomarkers for a long time. As the former deputy director of the NCI, she assembled many different groups including the Nanotechnology Alliance for Cancer and The Cancer Genome Atlas (TCGC). She's now at Arizona State University where she co-directs the Complex Adaptive Systems Center and seeks to establish a new paradigm in the way we look at the biology of disease.

Beginning with some philosophy of biology, Anna takes us into her latest thinking on complex systems.

"We have to start thinking of a disease like cancer as a system," she says. "As you perturb one part of it, you perturb all of it. . . . We have to think more 3D."

Anna is someone who likes to go back to the basics, not only in the study of biology, but also in the business side of diagnostics.

In the interview she announces a new National Biomarker Development Alliance (NBDA) that is bringing a higher level of standardization to every phase of biomarker development. She argues that there are several decision points in the process, whether it's to validate an assay, or take it into commercial development. Right now, she says, the diagnostics community does not agree on the current standards for these decision points, or modules, and this is a problem. The aim of the Alliance is to bring the community together to agree on higher standards. The NBDA has just launched their website and is publishing their standards in an effort to better educate those developing diagnostics.

"We believe this approach will really enable us to develop biomarkers more predictably all the way through regulatory approval."

And what are Anna's thoughts on regulation? She says outright that the FDA is going to regulate LDTs.

Ms. Barker's vast experience and deep commitment to better science and better industry standards shine a light for anyone involved in translating biomarkers to the clinic.

Podcast brought to you by: Myraqa Clinical Research: The CRO for Point of Care and PMA Diagnostics.

And by: DxInsights: Presenting a Diagnostics Summit at the Miraval Institute May 4-6.

Myths of Big Data with Sabina Leonelli, Philosopher of Information

Guest:

Sabina Leonelli, Philosopher, University of Exeter

Bio and Contact Info

Listen (6:44) Not a fan of the term Big Data

Listen (4:20) Something lost in bringing data together from various scientific cultures

Listen (3:36) Are data scientists really scientists?

Listen (4:11) Controversies around Open Data

Listen (3:03) Data systems come with their own biases

Listen (6:22) Message to bioinformaticians: Come up with the story of your data

Listen (1:15) Data driven vs hypothesis driven science

Listen (2:46) Thoughts on the Quantified Self movement

For the next installment in our Philosophy of Science series, we look at issues around data. Sabina Leonelli is a philosopher of information who collaborates with bioinformaticians. In today's interview, she expresses her concerns about the terms Big Data and Open Data.

"I have to admit, I'm not a big fan of this expression, 'Big Data,'" she says at the outset of the show.

Using data in science is, of course, a very old practice. So what's new about "big" data? Sabina is mostly concerned about the challenges of bringing data together from various sources. The biggest challenge here, she says, is with classification.

"Biology is fragmented in a lot of different epistemic cultures . . and each research tradition has different preferred ways of doing things," she points out. "What I'm interested in is the relationship between the language used and the actual practices. And there appears to be a very strong relationship between the way that people perform their research and the way in which they think about it. So terminology becomes a very specific signal for the various research traditions."

Sabina goes on to point out that the nuances of specific research traditions can be lost as data is integrated with other traditions. For instance, most large bioinformatics databases are done in English, whereas some of the individual research data may have been originally done in another language.

This becomes especially important with the new movement toward Open Data, where biases are built into the databases.

"The problem resides with the expectation that what is 'Open Data' is all the data there is," she says.

In fact, the data in Open Data tends to come from databases which are highly standardized and often from the most powerful labs.

How can bioinformaticians deal with these challenges? Sabina says researchers should be more diligent about creating "a story" around their data. This will help make the biases more transparent. She also says that a lot of conceptual effort must go into creating databases from the outset so that the data might be used for yet unknown questions in the future.

We finish the interview with her thoughts on the Quantified Self movement.

Podcast brought to you by: Chempetitive Group - "We love science. We love marketing. We love the idea of combining the two to make great things happen for your marketing communications."



New to Mendelspod?

We advance life science research, connecting people and ideas.
Register here to receive our newsletter.

or skip signup