Identifying polymer structures for oral drug delivery – A molecular design approach
Introduction
Polymers are ubiquitous in everyday life because of their wide range of applications. Plastics, textiles and rubbers are the most common polymers with extensive use in the society. All the polymers need to be designed through laboratory scale experimental trial-and-error techniques. However it is inefficient to completely rely on experimental synthesis and testing of many alternatives, since the number of possibilities can be exponentially large. Polymer molecular design can help in the screening of polymer structures, which then can be followed by laboratory scale experiments. This is also economical and less time consuming.
The chemical industry has been designing new polymers with desired functional properties for different applications (Gani, 2004, Gaspar and Duncan, 2009). One such application is in the pharmaceutical industry, where a drug is to be encapsulated inside a polymer matrix to aid in oral drug delivery. For example the drug is to be protected from the various influences in the GI (gastrointestinal) tract. There are several factors in the GI tract which may limit the absorption and solubility of the drug in the intestine; examples are the morphological barriers (mucus layer, micro villi, etc.), chemical barriers (acids, bicarbonates, etc.) and physiological barriers (a wide range of pH, enzymatic activities, specific transport mechanisms, etc.) (Gaucher et al., 2010). Therefore, the dissolution of a drug is quite often, the rate-limiting step, which ultimately controls the bioavailability of the drug. Polymers can be used as drug carriers because the chemical groups present in the structure can firmly bind with the drug and form an amorphous matrix. Polymers also aid in targeted drug release in the small intestine where maximum absorption takes place.
Biodegradable polymers are defined as polymers, which degrade in vitro and in vivo either into products that are normal metabolites of the body or into products that can be completely eliminated from the body with or without further metabolic transformation. The degradation products should be nontoxic, and that the rate of degradation and mechanical properties of the material should match the intended application. Nondegradable hydrophobic polymers initially used for drug delivery applications such as poly(dimethylsiloxane) (PS), polyurethanes (PU), and poly(ethylene-co-vinyl acetate) (EVA) (Mathiowitz, 1999) were not suitable for in vivo applications due to the need to remove them. Since biodegradable polymers do not have to be removed after delivery, they are preferred vehicles for drug delivery applications (Sharma et al., 2013, Kim et al., 2014). The release of drugs is favored by bioerosion of polymer matrices. Thus, both natural and synthetic biodegradable polymers have been extensively investigated for drug delivery applications.
Natural polymers are mostly chosen due to their excellent biocompatibility, as structurally they closely mimic native cellular environments, have unique mechanical properties, and are biodegradable by an enzymatic or hydrolytic mechanism. However, some of them have certain inherent disadvantages such as risk of viral infection, antigenicity, unstable material supply, and batch-to-batch variation in properties (Barbucci, 2002). Synthetic polymers, on the other hand, offer tremendous advantages over natural polymers from the material side. Due to their synthetic flexibility it is possible to develop polymers with a wide spectrum of properties with excellent reproducibility. Furthermore, fine-control of the degradation rate of these polymers is highly feasible by varying their structure.
Polysaccharides such as cellulose derivatives are important matrices for drug delivery applications (Swarbrick and Boyan, 1991, Robert et al., 2006). Starch has several applications as drug delivery systems. A slow-release drug delivery system based on amylose-rich starch under the trade name Contramid is available in the market. Alginate hydrogels have shown potential as drug delivery systems (Mumper et al., 1994, Tønnesen and Karlsen, 2002, Izawa et al., 2013). Alginate beads are employed for the controlled delivery of many cationic drugs and various growth factors. Polyelectrolyte complexes of alginate with other cationic polymers such as chitosan have been extensively investigated for cell encapsulation or as drug delivery matrices. Cross-linked chitosan hydrogel are attractive materials for controlling drug delivery by varying the cross-linking density. Other drug delivery systems include proteins, gelatin complexes etc. Polyhydroxyalkanoates (PHA) are biocompatible, processable, and degradable and hence used as matrices for drug delivery applications (Kassab et al., 1997, Ueda and Tabata, 2003, Shrivastav et al., 2013). Poly(γ-glutamic acid) (γ-PGA) was used to deliver a novel drug delivery system to deliver anticancer drug Taxol (Li et al., 1998). The hydrogels of poly(glutamic acid) prepared by γ-irradiation are under investigation as drug delivery matrices (Choi et al., 1995).
The most important biodegradable polymers for drug delivery applications are aliphatic polyesters such as PLA, PGA, and their copolymers (PLAGA) (Jain et al., 2011). PEG (Bezemer et al., 2000) and poly (ester carbonates) (Nair and Laurencin, 2006) are used as drug delivery systems. Another aliphatic polyester that assumes importance as a drug delivery matrix is poly(caprolactone) (PCL). It has low degradation rate and higher permeability of drugs compared to PLAGA (Cynthia D’Avila Carvalho Erbetta et al., 2012). Poly(ortho esters) and polyanhydrides were developed as matrices for drug delivery to achieve zero-order release kinetics (Mathiowitz, 1999, Attawia et al., 2001, Chiu Li et al., 2002, Heller et al., 2002).
Several other biodegradable polymer systems investigated as drug delivery matrices include polyphosphazenes (Lakshmi et al., 2003), polyphosphoesters (Zhao et al., 2003), poly(amino acids), poly(alkyl cyanoacrylates) (Harmia et al., 1986, Nicolas and Couvreur, 2009, Dossi et al., 2010), polyhydroxy alkanoates (Kassab et al., 1997, Shrivastav et al., 2013) and poly(glutamic acid) (Li et al., 1998, Yuan et al., 2010). Langer et al. proposed polyanhydrides to be ideal candidates for drug delivery applications (Rosen et al., 1983, Jain et al., 2008). Biodegradable polyphosphazenes are now being extensively investigated as matrices for drug delivery applications, particularly protein delivery (Andrianov and Payne, 1998, Lakshmi et al., 2003, Brüggemann and Teasdale, 2013).
The rest of the paper is organized as follows. Section 2 gives a brief description about polymer property prediction methods. Section 3 describes the CAMD model development for polymers to be used as drug carriers. Section 4 describes the outer approximation algorithm, which is used to solve the CAMD model developed. Section 5 describes the results and discussions, which include the generated polymer structures, a method to rank these generated structures, solubility parameter analysis and the parameter sensitivity and uncertainty analysis. Finally, Section 6 provides conclusions and some on-going or future work.
Section snippets
Polymer property prediction
A polymer is a macromolecule consisting of identical repeat units (monomers), which are linked by covalent bonds. A polymer containing identical repeat units is called a homo-polymer. The design of a polymer repeat unit requires the ability to estimate the physico-chemical properties of the repeat unit and by extension the polymer itself. There are several property prediction models, some of which are geared toward thermodynamic properties, whereas some are geared toward transport properties.
CAMD model development – polymers as drug carriers
This section discusses the various factors considered in developing the CAMD model. The first factor is identifying and studying the effect of various polymer properties on the rate of release of the drug from the polymer matrix. A detailed description of the problem formulation and the techniques used to solve the problem are also discussed.
Using the outer approximation algorithm to solve the CAMD model
In the previous section, we formulated the CAMD problem as an optimization model. The latter is a mixed integer non-linear programming (MINLP) problem. There are several methods for solving such models: these can be classified under (a) deterministic methods and (b) evolutionary methods. Deterministic methods include branch and bound and outer approximation (Grossmann, 1996, Grossmann et al., 1999, Wang and Achenie, 2002, Biegler and Grossmann, 2004, Karunanithi et al., 2005). The use of these
Results and discussion
Following the step-by-step procedure as discussed in the previous section, the resulting problem formulation is given in Table 3. The model was used to generate molecular structures of novel polymers, which could be used as potential drug carriers. We will proceed with a discussion of the results in the following sequence. In Section 5.1, we will discuss a method to rank the polymers generated, followed by solubility parameter analysis in Section 5.2 and parameter sensitivity and uncertainty
Conclusions
A CAMD framework is used to generate molecular structures of polymers with desired properties. We have successfully generated molecular structures of repeat units of polymers, which have the potential to be used as efficient carrier materials for drug delivery. The properties used in the problem formulation, namely, glass transition temperature (Tg), expansion coefficient (αf) and water absorption (W) were effective in reducing the number of possible candidates to a few. As the total number of
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