BIOSILICO: Paradigm change

Running through BIOSILICO was a distinct vibe of big change in life sciences. The notion that already there is a pretty well developed industry begat of biology, medicine and computer science suggests that changes already have substance. That is, modern biology isn’t your father’s biology. It’s not even the biology of flora and fauna I studied in school (which brings me the painful reminder that I’m old enough to be a classmate of the fathers of many readers).

Modern biology is about cells, the sub-cellular processes, and the molecules that make it all go. Not much cataloging furry, feathered or leafy things. The genetics of nematodes, yeast, mice and men are studied with equally great intensity, not because of great importance of worms or mice, but because the biological mechanisms of all of them have a common evolutionary heritage and a discovery of fundamental process in one is probably applicable to all.

Moreover, when you study things at the molecular level (DNA, RNA, proteins, etc.), and you study the numbingly complex way those things interact to constitute living things, others get in the act. In talking with “life scientists” today you’re very likely to end up talking to physicists and computer scientists. Which reminds me, Carlos Ortiz de Solorzano who is the subject of an earlier post and who is studying genetic instability in breast cancer is an engineer, specifically a telecommunications engineer by basic training. Why? Because the problem of creating ways to identify chromosome abnormalities in a hunk of real tissue has large measures of a classic communications problem: determining what’s signal (the thing you’re looking for) and what’s noise (all the other things going on that are just distractions). Biologists work for him.

So BIOSILICO was a representation of the truth of modern life science: most research problems involve an amalgam of traditional biologists, chemists, physicists, mathematicians, computer scientists. Nobody knows it all. It’s a team effort, and therein lies its strength and, sometimes, its weakness. It’s not easy to get all those people working together harmoniously.

But there’s another reason that all these disciplines are coming together: an emerging paradigm about the primacy of dynamic complexity and of information across a great hierarchy of real-world systems, including living things. Leroy Hood, founder of the Institute for Systems Biology, enumerated a kind of “chain of being” to which these things apply: DNA, mRNA, protein, protein interactions, protein-gene networks, cells, tissues, organs, organ systems, whole organisms, populations, and ecologies. The task is to understand the dynamics of complexity that unifies all these layers. Hood put the paradigm simply: “Biology is information.” It’s what threads all these things together.

The speakers at the conference spelled out a few implications of this situation. Hood said once we get all these things encompassed by theory, data from experiments and translation into desired outputs we’ll move into predictive, preventive and personal medicine. He says the preparation of physicians within this paradigm will be very different from today. They’ll be dealing in patient gene profiles, risk assessment, counseling, monitoring, and problem solving.

George Poste, DVM, (mentioned earlier) says we’ve entered the era of Big Biology. That means—as with the Human Genome Project—life science research is interdisciplinary, involves massive data, is information-based, infrastructure intensive, requires large financial investment and revamped education of everybody involved—physicians and the public included.

Poste spelled out his vision of Medicine in 2013:

  • Databases: I’ve said enough about that.
  • Smart cards: lots of data about patients, including gene profile data, used throughout health care to be specific and cut down error.
  • Diagnostics: much more refined.
  • Counseling: people have to understand their health risk characteristics and the risks of treatment.
  • Drugs: lots of drugs differentiated for different sub-categories of disease and patient characteristics.
  • Genetic profiling: knowledge of individual genetic characteristics a routine part of health evaluation.
  • Diverse management protocols: no more one-size-fits-all or one treatment protocol for a disease; instead protocols adapted to individuals and changing according to progression.
  • New medical taxonomy: further molecular differentiation of sub-types of diseases such as breast cancer and perhaps re-categorizing diseases according to underlying molecular processes. They may find similar genetic regulatory issues in diseases as diverse as some cancers and heart diseases.
  • Global gene expression: not so much looking for simple one-gene causes and one-target drugs; cancer is a multi-gene disease with many alternative pathways.

Also, the tsunami of information referred to in an earlier post will happened to everyone as they assimilate the information to make their lives as risk-free and productive as possible.