GUEST POST |Manuel Gea| Big Data: Big garbage? An estimated 85% of research resources are wasted!

bigdata

Manuel Gea

CEO BMSystems

This post appeared originally on Manuel’s LinkedIn pageI thought it important enough to invite as a Guest Blog Post on JAMESLYONSWEILER.COM  It is slightly edited for context. It is extremely relevant for ipaknowledge.org and there are lessons here for us all. Enjoy. JLW

New evidence published in Science confirms the poor reproducibility (less than 1/3) of studies published in peer-reviewed journals.

And, published by Stanford University in PLOS medicine, are findings that show that  many published research findings are false or exaggerated, and an estimated 85% of research resources are wasted (see publication 2 below).

The main objective of this post to launch a discussion and try to prevent big data to become only big garbage in life sciences. It is possible, but we need to work on the right concepts and methods.

What we really need to implement Mechanisms-Based Medicine should be: High value Smart Data. These “Mechanisms-Based Smart Data” to give real medical “sense” to what we measure. It means that they must necessarily be:

  1. Characterized, traceable and contextualized.
  2. Based on a robust biological mechanisms understanding, and
  3. Related to patients base-lines.

For 2015 we should not forget that: “In life sciences, with less than 10% success rate, a dominant recurrent thinking that repeatedly fails may be “false”!, even if supported by Key opinion leaders” if we want to start thinking out of the box!*

Many thanks for all the comments and questions on my previous posts about the issue of big data in life sciences especially for discovery..Find below 7 documents published of great interest that support and better explain my posts. Do not hesitate to join my network or send me feedback

  1. August 2015: A new evidence published in Sciences confirms the poor reproducibility (less than 1/3) of studies published in peer-reviewed.
  2. How to Make More Published Research True. Published in PLOS Medicine by John P. A. Ioannidis Meta-Research Innovation Center at Stanford (METRICS), Stanford University.
  3. Diagnosing the decline in pharmaceutical R&D efficiency. Published Nature Review Drug Discovery. The diagnostic is clear for our industry.
  4. Believe it or not: how much can we rely on published data on potential drug targets? Their title is crystal clear. Published Nature Review Drug Discovery.
  5. The Differences & Complementarities Between « Heuristic » and « Mathematical» approaches. The scientific presentation given by Dr. François IRIS (CSO BMSystems) during the EPA (European Psychiatric Association) conference in 2011.
  6. Psychiatric Systems Medicine success: Invited review in Pharmaco-Psychiatry to present the first Mechanisms-Based Medicine program that led to discoveries validated in-vivo: The late phase of the Creutzfeld-Jacob (Mad Cow) disease mechanisms was deciphered and the indirectly led to discovery of the novel therapy for psychiatric disorders
  7. The principles of Mechanisms-Based Medicine and 9 proof of concepts

*Thinking out of the box already contributed to the creation of two funded Pharma SMEs at clinical stage: Pherecydes-Pharma (2006, novel M.R. bacteria bio-therapies), Theranexus (2013, innovative combined therapies for Psychiatric disorders).

To contact Manual, email him at manuel.gea AT bmsystems.net .

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s