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.