Partrnerships 2010: Thinking Small in Big Pharma: What Will Future Pharma R&D Look Like

Thomas Senderovitz MD, FCP, Senior Vice President, Global Clinical Development, GRUNENTHAL GmbH

The way in which we have been conducting our R&D activities and the manner in which these activities translates into the general well being of our society does not seem to be working very well. This is evidenced by the fact that up to 40% of people receiving medications don’t benefit from them, 106,000 people die a year and there are 2.2 million non-fatal events each year.

Our current model is that one size fits all and that medications are not differentiated. The fact of the matter is that patients are different and efforts should be undertaken to address this diversity in our R&D model. R&D costs with the present system are rising exponentially and the return of share holder value has dropped from 20.3% (1985 – 2000) to -0.7% (2001 – 2007).

Recent estimates indicate that it now takes 13 years and 1.3 billion Euros to develop a drug. The impact of mergers and acquisitions in the development of New Molecular Entities (NME) output is not working as well. Quite frankly, we are at the end of the blockbuster era which was prevalent for many years. The seeking of block buster drugs is no longer a viable business model in today’s times given the previous statements.

The presenter felt very strongly that we have to change our discovery process that will lead to an improvement in the development process resulting in decreased cycle times. Specific steps to take to address this situation were identified as:

• Stratifying personal treatments to individuals needs matching genetic and life style background

• Moving away from one size fits all business model

• Moving away from damaged organs approach to a network based discovery approach

There are multiple areas in the network that will need to be addressed and include:

• Single target drugs versus multiple drugs

• Challenge for regulatory agencies
• Increased attrition rates

It was felt that current disease definitions will disappear. Molecular diagnostics will be employed to address unmet molecular needs and will do so due to earlier intervention and restoration of damaged networks. This translates into early intervention equaling longer treatment.

By using a targeted subpopulations approach, higher efficacy and better safety will be achieved that results in better risk/benefit ratio. All of this leads to a higher compliance in taking of prescribed medications that ultimately result in added value to the customer.

The oveall recommendation was to move from the blockbuster approach towards a stratified R&D approach. This will lead to personalized medicine that will address the uniqueness of each individual.

Modeling and Simulation are a must in the new model of drug development. This will require:

1. Understanding biological networks

2. Translating in vitro and animal data - integrative and translational M&S
3. Designing optimal clinical programs

Building large computer models is needed to simulate human physiology which will lead to the creation of a virtual patient. Other requirements needed to move to the new R&D model include integrated data platforms and real time access to nonclinical and clinical data.

Presently, there are next generation diagnostics (portable data capture devices), next generation sensors (online monitoring of systems on a personal basis, use of I Phone to monitor systems) and next generation drug delivery systems.

An integrated healthcare solution will involve moving from single targets to multiple targets – targeting treatments for intervention, monitoring on-line real time data, early warning using biomarkers before drug interaction is required, using wireless health monitoring devices, personalized treatments and real time biomarker monitoring.

The future of the pharma Industry will include personalized targets for medicine, linking up with diagnostic tools and sensors, increased health surveillance, earlier intervention, using social media and in silico R&D (based on modeling data).

One question that presents itself is how to change the R&D business model in light of current regulatory industry standards. We as an industry need to be bold and to challenge existing methodology. Industry has to make a move to understand the data and make a case for change that will involve the sharing clinical data.