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Modeling at Sanofi-Synthelabo - An Interview with David England, Physical Chemistry R&D Projects Manager

Introduction

The Sanofi-Synthélabo group is one of the world's top 20 pharmaceutical companies, the 7th largest in Europe and the 2nd largest in France. The Group has a presence in over 100 countries spread over 5 continents. It is a major player in the world's pharmaceutical market, especially in four therapeutic areas: cardiovascular/thrombosis, central nervous system, internal medicine, and oncology.

Its two principal goals are to discover new compounds which are essential to the advancement of medical science and to launch pharmaceutical products which constitute real clinical benefit for patients.

See also: Near-molecular Resolution for Drug Formulation Studies

The Interview

What follows is the transcript of an interview conducted by Accelrys with David England, Physical Chemistry R&D Projects Manager.

1. What modeling, simulation, and/or informatics software does your company use?

Sanofi-Synthelabo has access to drug discovery, crystallization, and polymer consortium software. I have a specific interest in the polymer modeling tools.

2. What do you use it for? How does this work fit in with your company's long-term goals?

Polymer and surfactant based formulations are used to improve the bioavailability of poorly soluble drugs and therefore provides important strategies in drug development. Some of the formulations we develop are composed entirely of polymers, surfactant, and the drug. It is therefore appropriate to use the tools developed by the polymer/surfactant industry for studying these polymer drug mixtures. These include analytical techniques, solid state NMR to provide information about different environments in the formulation e.g. by studies of diffusion rates, atomic force microscopy (AFM) to study sub-micron phase separations, small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS) to investigate large scale structure 10-1000 nm, and computer modeling to attempt to predict and understand observations and analytical data.

3. Have you published work in the scientific literature and/or general press that uses computational software? If so, when and where?

Not at this time. All publications are internal. The software is being used to look at real problems, which may have commercial and patent implications.

4. What did the software enable you to do that experimentation didn't?

The issue, which interested me, is the long timescales of physical changes in polymer-based formulations that cannot be accelerated by increasing the temperature during stability studies.

Polymer system changes often occur on the timescale of six to twelve months due to the mobility of a medium as a result of using high molecular weight polymers. This may result in the crystallisation of the drug from the matrix or changes in appearance, making the product unsuitable for development/comercialization.

Temperature is also a problem; a small increase in temperature can change the properties of the excipient matrix e.g. melting a lamellar phase, changing completely the characteristics of the environment seen by the drug.

These long timescales and the inability to accelerate change by increasing the temperature make the development of optimized formulations difficult. Modeling provides an opportunity to evaluate the driving forces behind the physical changes.

5. What would you say are the main scientific advantages of using computation over experimentation? Likewise financial advantages? Did its use save resources - i.e. time, money...?

Modeling is not a replacement for experiment, it is a complement to the experiment, often providing ideas that can then be tested by experiment. Modeling helps to build a more complete understanding of a problem.

6. How long would you say that it took for your company/organization to re-coup the initial investment in the software (including initial, installation and running costs) with any cost savings mentioned in the previous question?

Return on investment is not an easy calculation for this type of work, particularly taking into account overall drug development time.

7. Did the use of the computational chemistry techniques result directly in refinements to existing processes? And, if so, how much has it saved your company? And in the future?

At this time we are using these techniques to understand formulation problems as a way to guiding future development. In the future when the level of confidence in the technology has been improved I hope the computational tools will help guide formulation development.

8. Did the use of the computational chemistry techniques allow you to gain a competitive advantage?

It is difficult to comment at this time.

9. What do you and your organization plan to use the software for in the future?

Continue to use the polymer tools to investigate polymer and surfactant based formulations at the atomistic and mesoscale length scales.

10. Would you recommend the use of modeling/simulation to your peers?

Yes, if the problem is appropriate.