Pertinent to this discussion thread, I wish to draw attention to a special issue of Perspectives in Biology and Medicine. Volume 61, Number 4, Autumn 2018 with the title: The Precision Medicine Bubble. The issue takes up the topic of precision medicine in some depth. It has a refreshingly cynical take on the contributions of precision medicine to date.”
https://muse.jhu.edu/issue/39661
Particular attention is drawn to the paper by Sui Huang.
Huang S. The Tension Between Big Data and Theory in the “Omics” Era of Biomedical Research. Perspect Biol Med. 2018;61(4):472-488. doi: 10.1353/pbm.2018.0058. PMID: 30613031.
Contrasting the value of “big data” in commerce and biomedicine, Huang notes that:
The problem is that the spectacular success of the internet-based applications of Big Data has tempted biomedical researchers to think that using clever algorithms to mine and comb the vast amount of data produced by the omics revolution will recapitulate the success of Google, Amazon, or Netflix.
Going further, Huang says:
The fundamental differences between the natural sciences, on the one hand, which seek new understanding of organisms, and “data sciences” on the other hand, which serve consumer applications, give rise to formidable challenges for a quick adoption of the Big Data approach to biology and medicine. The human body and its (mal)functions are more complex than recognizing cats in photos or predicting client habits from purchase history. The latter tasks can, without denigration, be considered “superficial”: here data directly maps to utility without the need of a theory that formalizes our understanding of the mechanism of how data translate into useful knowledge. But such heuristics does not lead far in basic sciences, notably the life sciences.
In the same issue of this journal, epidemiologists Nigel Paneth and Sten Vermund highlight major advances in public health made over the last century. None used big data, precision medicine, or machine learning.
Considering precision medicine, Paneth and Vermund go so far as to posit that:
Precision medicine built on a foundation of host genetics can benefit some patients, but it has no realistic chance of linking human genetics to population-level health improvement. There are too few diseases where human genetic variation will make a substantial difference in approaches to screening, diagnosis, or therapy to justify the disproportionate investments into this approach as a principal priority for the NIH and for the private sector.
Paneth N, Vermund SH. Human Molecular Genetics Has Not Yet Contributed to Measurable Public Health Advances. Perspect Biol Med. 2018;61(4):537-549. doi: 10.1353/pbm.2018.0063. PMID: 30613036.
Also in this issue, epidemiologist Richard S. Cooper reviews the history of the “cardiovascular prevention movement” over the last 40 years, highlighting its spectacular success in reducing mortality due to cardiovascular disease. He mentions two pivotal observational studies that might be called “little data”–the Framingham Study with 5,209 men and women and the “Seven Countries Study” with about 12,000 men—yet identified the modifiable risk factors for cardiovascular disease (serum cholesterol, hypertension, cigarette smoking) that are the cornerstone of interventions that account for a substantial proportion of the decline in cardiovascular disease mortality.
Cooper notes that:
It will not escape the notice of the reader of this issue of the journal that genomics and “precision medicine” have, to date, made no contribution whatsoever to control of CVD as a mass disease.”
Cooper RS. Control of Cardiovascular Disease in the 20th Century: Meeting the Challenge of Chronic Degenerative Disease. Perspect Biol Med. 2018;61(4):550-559. doi: 10.1353/pbm.2018.0064. PMID: 30613037.