Scientific MOOCs follower. Author of Airpocalypse, a techno-medical thriller (Out Summer 2017)

Welcome to the digital era of biology (and to this modest blog I started in early 2005).

To cure many diseases, like cancer or cystic fibrosis, we will need to target genes (mutations, for ex.), not organs! I am convinced that the future of replacement medicine (organ transplant) is genomics (the science of the human genome). In 10 years we will be replacing (modifying) genes; not organs!

Anticipating the $100 genome era and the P4™ medicine revolution. P4 Medicine (Predictive, Personalized, Preventive, & Participatory): Catalyzing a Revolution from Reactive to Proactive Medicine.

I am an early adopter of scientific MOOCs. I've earned myself four MIT digital diplomas: 7.00x, 7.28x1, 7.28.x2 and 7QBWx. Instructor of 7.00x: Eric Lander PhD.

Upcoming books: Airpocalypse, a medical thriller (action taking place in Beijing) 2017; Jesus CRISPR Superstar, a sci-fi -- French title: La Passion du CRISPR (2018).

I love Genomics. Would you rather donate your data, or... your vital organs? Imagine all the people sharing their data...

Audio files on this blog are Windows files ; if you have a Mac, you might want to use VLC ( to read them.

Concernant les fichiers son ou audio (audio files) sur ce blog : ce sont des fichiers Windows ; pour les lire sur Mac, il faut les ouvrir avec VLC (

US healthcare system is broken. Google using big data to "solve death"; 23andMe using big data to "solve health"

"The Google of Spit"
"With 23and­Me, Wojcicki wants to do with DNA what Google did for data—because, after all, DNA is data."

"Anne Wojcicki is CEO of a company she co-founded called 23andMe (so named for the number of chromosomes in human DNA) that could help forestall that legacy—could 'solve health,' as she puts it—by collecting the genetic information of a critical mass of humans on the planet.

Anne launched her company with the conviction, which happens to be the conviction of many of her friends and peers, that health care in America is broken, inefficiently treating the sick while insufficiently supporting the well, and that, enabled by the power of Big Data, Silicon Valley can fix it—accelerating to light speed the development of drugs and therapies by harvesting unprecedented insights from a reservoir of the nation’s genes.

By last fall, 23andMe had extracted and analyzed DNA from 650,000 people, making it one of the biggest genetic banks in the world. That was when the Food and Drug Administration stepped in. 23andMe was performing what it regarded as a medical test without its approval and without the oversight of any doctor, the FDA said, and until Wojcicki could demonstrate that those tests would inflict no harm, she was ordered to retreat from her quest to hoover up the world’s DNA.

But Wojcicki is undeterred. With 23and­Me, she wants to do with DNA what Google did for data—because, after all, DNA is data. Want to compare huge numbers of people with hereditary Parkinson’s disease against people who carry a gene for Parkinson’s but are healthy? Here’s a database of millions: All a researcher needs to do is create the algorithm. Want to look at genetic variances among people with very complex diseases, like diabetes, or Alzheimer’s, or coronary-artery disease? 23andMe can isolate disease groups and scrutinize the genotypes within them. Want to figure out why a tiny number of folks taking a certain multiple-sclerosis drug also get blood clots? Cull the patients from the database, email them a questionnaire, and compare answers. And then there are those connections algorithms might make between genes and health that humans hadn’t even thought to ask about.

These results might efficiently steer scientists toward especially promising targets for research, and the resulting discoveries—drugs, surgical procedures, nutritional information, eyeglasses, sunscreen—might then be marketed back to individuals who 23andMe already knows are predisposed to osteo­arthritis or hereditary blindness or melanoma. It’s a vision of seamless scientific research that is also a business—like, say, Google—tempting you with products the data engine has already discerned you need."

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