March 14, 2010

Business models and open IP platforms in personalized medicine


Personalized Medicine is a frequently discussed concept in healthcare thought to hold great value for the future. Since I am currently involved in a project where the technology could provide utilities for personalized medicine while at the same time co-authoring a paper on open IP platforms, I thought that a blog post that combines the two worlds could be interesting to write - so here it goes.


What is personalized medicine and why does it matter?

Medical practice relies on evidence-based medicine - the development of standards of care based on epidemiologic studies of large cohorts - a practice that has been around more than 50 years. The rationale is that a statistical approach to large cohort studies enables reduction of background noise, i.e. ignoring individual differences in the data points. Traditionally, individual care by a medical practitioner is built on the patient's family history, social circumstances, environment and behaviors - meaning that the doctor's personal observations, skills and intuition have been crucial factors.

Personalized medicine seeks to provide an objective basis for consideration of individual differences by the systematic use of genetic information about each individual patient to select or optimize the patient's preventative and therapeutic care. A simple example would be to be recommended to take a genetic test before being prescribed a certain drug to shows whether you have a genetic profile that makes you more responsive to drug A or drug B (used for the same disease). Obviously tremendous health-economic gains could also be expected where one example is hypersensitivity to gluten (for which Phadia is developing diagnostic technology) that currently takes an average time of eleven years to diagnose in the US according to Phadia.


Two examples of business models personalized medicine could enable in the future

1. Insurance model: Let's say that you consider buying a life insurance. Obviously, it is in your best interest as well as in your insurance company's best interest that you live a long and healthy life. With the latest advances in genomics your insurance company provides you with a voucher to get your genome sequenced and get access to a web portal where you can see your genetic profile - without the insurance company having any access to your data! This means that you can make dietary and lifestyle changes to improve your chances against your genetic predisposition toward obesity, diabetes, high blood pressure, dyslipidemia, etc. while lowering the risk for your insurance company. A win-win situation!

2. Diet model: Your latest cholesterol checkup suggests that you should reconsider your diet. At the dietist's office, your current diet is matched with your genetic predisposition to absorb nutrition. The results show that the diet is not the issue, it is your body that does not handle some of your daily intake very well. Consequently, your dietist recommends you to ask your doctor for drug X to enhance your nutrition absorption.


Personal Genome Project (PGP) - an Open IP Platform

The Human Genome Project provided the first drafts of nearly complete human genome sequences in 2001. This "generic" human genome sequence is now being used to advance medicine, human biology and knowledge of human origins. The available information, however, is not enough to determine individuals' risk profiles for disease. PGP - led by George M. Church, Professor of Genetics at Harvard Medical School - was launched to create a platform to do just that.


The cost to extract all the information during the human genome project was close to US$ 3 billion, which has decreased all the way down to US$ 1500 per genome by now (although most sequencing companies charge US$ 30-50k to sequence a genome). PGP aims - as its first milestone - to collect genomic information from 100 000 people together with their trait information (i.e. phenotypic data such as diseases). Sample collection is entirely built on samples contributed by volunteers all agreeing on their personal information being open for access to the public, mainly providing two utilities;

  • Profiles of patients getting their genomes sequenced can compare their genetic profiles to the genotypes of risk profiles
  • Statistical correlation of the data can provide novel gene-trait associations leading to new drug targets


The platform is open in multiple layers and several IP transactions take place in an open innovation fashion. Core R&D data making up the platform is - as mentioned - donated by volunteers by collecting cells that are then cultured in cell line libraries for future reference pooled together with written trait data collected via a virtual interface. Genomic data is available for download and cell lines are available to order. Analysis of the data is conducted through open source software to ensure that users can help develop the tools in case something seems to be missing. Sequencing technology and tools are inlicensed from commercial sequencing companies. PGP is conducted at nominal cost and most of the financing is raised through donations.


So what about IP ownership? The Material Transfer Agreement states that: " i) the Provider retains ownership and title to the Materials (including any Materials contained in any Modifications) and ii) the Recipient retains ownership and title to the Modifications (except that the Provider retains ownership and title to any Materials contained in any Modifications). The Recipient is free to file patent application(s) claiming inventions made by, or on behalf of, the Recipient through the use of the Materials, but agrees not to file any patent application containing a composition of matter claim on the original Materials or an Unmodified Product.".


To me, the PGP initiative exemplifies an extremely interesting example of an open IP platform with the potential to create value for both society and knowledge based companies leveraging diagnostic tools, drugs and preventative medicine and I may come back to do a deeper analysis in an upcoming blog post.


Tobias Thornblad

(Contact via Twitter)


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  2. I agree with your points as you said Profiles of patients getting their genomes sequenced can compare their genetic profiles to the genotypes of risk profiles
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