Tailoring the Chemical Modification of Chitosan Hydrogels to Fine-Tune the Release of a Synergistic Combination of Chemotherapeutics

Abstract

Combination chemotherapy with a defined ratio and sequence of drug release is a clinically established and effective route to treat advanced solid tumors. In this context, a growing body of literature demonstrates the potential of hydrogels constructed with chemically modified polysaccharides as depots for controlled release of chemotherapeutics. Identifying the appropriate modification in terms of physicochemical properties of the functional group and its degree of substitution (χ) to achieve the desired release profile for multiple drugs is, however, a complex multivariate problem. To address this issue, we have developed a computational toolbox that models the migration of a drug pair through a hydrated network of polysaccharide chains modified with hydrophobic moieties. In this study, we chose doxorubicin (DOX) and Gemcitabine (GEM) as model drugs, as their synergistic effect against breast cancer has been thoroughly investigated, and chitosan as the model polymer. Our model describes how the modification of chitosan chains with acetyl, butanoyl, and heptanoyl moieties at different values χ governs both the structure of the hydrogel network and drug migration through it. Our experimental data confirm the in silico predictions for both single- and dual-drug release and, most notably, the counterintuitive inversion of release vs χ that occurs when switching from a single- to a dual-drug system. Consensus between predicted and experimental data indicates that acetyl modifications (χ = 32–42%) and butanoyl modifications (χ = 19–24%) provide synergistic GEM/DOX release molar ratios (i.e., 5–10). Collectively, these results demonstrate the potential of this model in guiding the design of chemotherapeutic hydrogels to combat cancer.

A multiscale coarse-grained model to predict the molecular architecture and drug transport properties of modified chitosan hydrogels

“…The number of contacts with the M beads is low and independent of the modification pattern; the increase with w Ac is related to the formation of hydrogen bonds with the amide moieties connecting M and A beads. 56 The number of contacts with the backbone beads is higher and rather unaffected by either w Ac or pattern. The observed sharp increase in Dox diffusion coefficient with w But can be attributed to the formation of the large pores in the network following the transition from uniform structure to the cluster/channel morphology.…”

“…Concurrently, the number of contacts with the backbone increases; as Dox molecules are attracted towards GlcNAc beads by hydrophobic interactions, they also form secondary contacts with the intercalated GlcN beads via hydrogen bonding. 56 A different trend is observed with blocky acetyl-chitosan, where the number of interactions between Dox and M beads grows with w Ac , whereas the number of contacts with backbone beads decreases; the blocky modification pattern, in fact, by removing the intercalation between the monomers, lowers the probability of Dox forming secondary interactions with GlcN as a consequence of initial hydrophobic binding to GlcNAc monomers. a New simulations were performed to avoid cluster formation.…”

“…Hydrogels comprising acetyl-chitosan (w Ac = 16% or 50%), butanoyl-chitosan (w Ac = 16% or 32%), or heptanoyl-chitosan (w Hep = 8% or 24%) were constructed and loaded with either Dox or Gem at the same concentrations utilized in the simulations, following a procedure that we previously developed. 56 Every drug-loaded gel was put into contact with an aqueous supernatant, which was sampled at set time points (1,4,8,24,48, and 72 hours) and analyzed by UV spectrophotometry to determine the amount of drug released from the gels into solution. The values of diffusion coefficient were finally calculated from the temporal data of drug release by applying a derived form of the Fick's second law outlined by Fu and Kao.…”

“…[1][2][3]13,14,82 Their optimization as drug delivery carriers for clinical applications, however, is extremely laborious due to the width of the experimental space of design controlling drug loading and release. 56 Computational models capable of predicting the transport of drugs through chitosan-based hydrogels hold great promise to accelerate pre-clinical development and ultimately improve translation potential. Key to this end is the ability of the model to connect physicochemical properties and architecture of the chain network and drug properties.…”

“…The diffusion of Dox and Gem through the networks was analyzed by tracking the mean-square displacement (MSD) of the drug molecules vs. time, from which the corresponding diffusion coefficients were calculated. In parallel, following the experimental procedure developed in prior work, 56 the above-listed hydrogels were constructed and loaded with either Dox or Gem at the same concentration as utilized in the simulations, and the drug release was measured as a function of time. From the resultant drug release profiles, the values of diffusion coefficients were calculated by applying a derived form of the Fick's second law for slab-like devices.…”