(317c) A Molecular Design Approach for Drug Tablet Formulation and Impact On Personalized Medicine

Authors: 
Pavurala, N., Virginia Tech
Achenie, L., Virginia Tech



A molecular design approach
for drug tablet formulation and impact on personalized medicine

Naresh Pavurala, Luke E.K Achenie

Department of Chemical Engineering,
Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24060

One of the major challenges faced by the
pharmaceutical industry is to accelerate the drug innovation process and reduce
the time-to-market for new drug developments. This involves billions of dollars
of investment due to the large amount of experimentation and validation
processes involved. A computational modeling approach, which could rapidly
explore the design space, reduce uncertainty and make better, faster and safer
decisions, fits into the overall goal and complements the drug development
process.

In the drug discovery and development process, the
tablet formulation (oral drug delivery) is an important step. The tablet
consists of active pharmaceutical ingredient (API), excipients and polymer. A
controlled release of drug from this tablet usually involves swelling of the
polymer, forming a gel layer and diffusion of drug through the gel layer into
the body. The polymer is mainly responsible for controlling the release rate
(of the drug from the tablet), which would lead to a desired therapeutic effect
on the body.

In this presentation we propose a molecular design
strategy for generating molecular structures of polymer candidates with desired
properties estimated through structure-property models. Our work is expected to
aid in generating the most favorable polymers based on the biopharmaceutical and
pharmacokinetic properties. This could help in precipitating development
failures in the early stages of drug discovery as well as reduce the very
expensive late-stage failures.

In greater detail, we utilized group contribution
models to estimate several desired polymer properties such as grass transition
temperature (Tg), density (ρ) and linear
expansion coefficient (α). We subsequently solved an optimization
model, which generated molecular structures of polymers with desired property
values. Some of the polymer repeat-units are already available in the literature;
these include polyvinyl alcohol (PVA) and polyvinyl chloride (PVC) repeat-units.
Examples of new repeat units are ?CH=CH-COO?, ?CHCl?CH2?CHCl?.
These repeat-units could potentially lead to novel polymers with interesting
characteristics; a polymer chemist could further investigate these. We recognize
the need to develop group contribution models for other polymer properties such
as porosity of the polymer and diffusion coefficients of water and drug in the
polymer, which are not currently available in literature. We expect our
modeling approach to aid in the drug development process and contribute to the
development of personalized medicine.