The glue between Partners & Alliances - 2010 Biopartnering Study

We are in the process of developing our BioPartnering 2010 study. The study examines three areas:

1. Deal Sourcing: - Proactively sourcing for the best deals and enabling prospective partners to easily access the pharma company; building a reputation for being a “Partner of Choice”
2. Deal Making: - Trust building, due diligence, valuation, negotiation and contracting
3. Alliance Management: - Realizing value through the creation and execution of an alliance business plan, organization and governance arrangements

The study surveys companies in the biopharma industry and delivers three tangible outputs:

• Fresh thinking - every study builds on the last and new insights are derived every time we run this. One key area of focus is always on what did "outperformers" do that the "underperformers" did not.
• Scoring for Companies that participate in the study - Top 5 rankings for each of the three areas we study (Merck and Genentech were the only companies in the 2008 study that made top 5 ranking for all three areas).
• Drivers of Alliance Formation - Understanding what motivates interest in a deal. The "Deal on offer", not suprisingly, is the most important; however what else drives the deal?

In preparation for this year's study I have been doing some research and took time to read Stefan Lindegaard's blog. In his most recent posting he responds to an open innovation posting from John Hagel and John Seely Brown. The nugget I really caught onto was at the end of his posting.

He refers to a talk given by Peter Erickson who leads the innovation efforts at General Mills. General Mills have been leaders in the open innovation field along with companies such as P&G (Connect & Develop) and IBM. He writes in his blog "The next practices of open innovation will be about developing systems, enablers, and processes that speed the connection to innovation partners in a repeatable, cost effective, quick way".

Open innovation is not a new practice. In fact Professor Chesbrough first coined the term back in 2003. So my hypothesis is that outperformers in the biopharma industry have mature processes and systems for the operation of their alliances and collaborations.... not just the scouting and deal making aspects.

Therefore in the 2010 study we will aim to evaluate this hypothesis; we will examine the maturity of systems, enablers and processes and see if they are at a level where one could describe them as "repeatable, cost effective, and fast"?

Check out the 2008 study titled "A Marriage of Minds" and a related publication "The Power of Many" to understand the ABCs of collaboration.

Innovation - New Life Sciences Collaboratory from IBM

I have been a fan of the collaboratory model since I first learned of it. However I wasn't able to really share a life sciences example. Until this week. IBM, the University of Melbourne and the Victorian government today announced a new IBM Research Collaboratory for Life Sciences, located in Melbourne, Australia. The collaboratory is IBM’s first life sciences collaboratory, and IBM’s first collaboratory in the southern hemisphere. It will use high-performance computing – including IBM’s BlueGene super computer – to advance biological sciences and medical research.

Collaboratory Goals
The collaboration is dedicated to dramatic improvements in human health through technology innovation in medical diagnostics, drug discovery and drug design, underpinned by a deep understanding of disease. The collaboratory will use data and high-performance computing to model biological systems in order to accelerate research and treatments for conditions such as cancer and neurological disease.

Scientists from VLSCI and IBM Research will work to accelerate the translation of our fundamental understanding of biology to improvements in medical care and health outcomes, with projects such as:

• Medical Imaging and Neuroscience: high performance computers are used to analyse images from the devices such as MRI, PET and the synchrotron.
• Clinical Genomics: the identification of combinations of genes implicated in disease and the ability to predict susceptibility to disease and treatment outcome from an individual’s genome and medical history.
• Structural Biology: understanding the structure and shape of biological macromolecules, fundamental to pharmaceutical discovery.
• Integrated Systems Biology: understanding and modelling the dynamic behaviour of complex systems, from genes, proteins, cells, tissues and organs to organisms.

What is the bottom line?

By bringing computation to medical research, breakthroughs in diagnosis and treatment can be achieved much quicker. What may have taken two years or more using traditional computational and wet laboratory techniques can be achieved in a matter of days or weeks.

See more on this youtube video....