In silico modelling of polymer-based drug delivery systems
Creators: name: Mandal, Debesh
Publisher: name: Imperial College London
Year: 2022

description: 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.