The advances in drug delivery over the past twenty years have been significant, in particular
focusing on the areas of making formulations by combining therapeutic molecules with other
chemicals to improve their efficacy as a therapeutic agent. Along with advances in drug delivery
has been the rapid rise of the use of genetic material in all industries, but especially in the
healthcare space, with advances such as gene therapy and the COVID-19 vaccinations providing
evidence of the enormous potential of genetic material as a therapeutic agent. Alongside these
healthcare breakthroughs have been major advances in the computational fields, including the
development of Machine Learning and Artificial Intelligence, the widespread use of parallelised
and distributed computing, and the wide availability of high-level software for users with any
skill level. The work in these thesis focuses on the intersection between these areas by conducting
computer simulations to improve the speed of development and understanding of some of the
complex formulations used in gene therapy and the controlled release of drugs.
We will use a selection of molecular dynamics simulations and coarse-grained models to investigate
a series of systems relevant for controlled gene- and drug- delivery applications. After providing
a brief overview of the problem and some relevant literature in this chapter, Chapter 2 reviews
the methods employed, whereas Chapters 3-6 contain the main original results of this work.
In Chapter 3, we begin by describing the structure and functionality of the hydrogels software
that I have developed, which underpins all of the software development required to present
the results later on in the thesis. In practice, hydrogels is a high-level wrapper that allows
users to seamlessly interface with other available software packages previously developed for
different kinds of molecular simulations, allowing for a unified computational framework that
offers a portable method for simulating different polymeric systems with little prior knowledge,
from their initial synthesis to their self-assembly, to interactions with drugs and their enzymatic
degradation, all within a single software. Developing efficient software stacks is an important
and integral part of computational research in the modern era, which allows improvements to
the usability of otherwise complex, variegated models. Because of its potential to drastically
expand the user-base for the kind of simulations we present in this thesis and thus study many
other important polymer-based drug delivery systems, this chapter holds particular importance
in terms of its contribution to the scientific community focusing on drug delivery vectors. After
presenting the software I have developed, the subsequent chapters put hydrogels to good use.
In Chapter 4, we address the problem of the enzymatic degradation of hydrogels, starting from
their synthesis in silico. To generate a realistic model for their internal structure, interacting
particle reaction dynamics (iPRD) simulations were conducted to study how the degradation
process is affected by a range of experimentally relevant parameters, for example the relative
length of the polymer chains and cross-linking density.
Following this in Chapter 5, we describe a set of simulations where the complexation of star
polymers of different architectures with genetic material is considered, looking in particular at
understanding how to tune the stability of the complex formed. Chapters 4 and 5 together allow
one to appreciate the power of combining different simulation approaches and computational
models to optimise existing delivery systems.
Finally in Chapter 6, we combine the previously described systems to simulate a less traditional
and somewhat novel delivery system, a polymer gel which is directly crosslinked by its payload.
Inspiration for this system came from very recent experimental work on the delivery of genetic
material using cationic gels, and to the best of our knowledge, the work presented here represents
the very first simulation work addressing this system.