The COVID-19 pandemic has exposed two major weaknesses in our preparedness for respiratory viral threats. Firstly, there is a critical lack of available antiviral drugs which can be deployed at the first signs of symptoms or as post-exposure prophylaxis (given as a short course to people who have been in contact with an infected individual). Secondly, a basic principle of treating viral infections is that a combination of drugs with different modes of action is usually required, and for respiratory viruses, antiviral combinations are only effective if started in the first day or two following symptom onset. As with other respiratory viruses such as influenza, SARS-CoV-1 and MERS-CoV, SARS-CoV-2 viral replication rapidly slows following symptom onset with the later severe stage of disease mediated more by the body's response to the infection rather than active viral replication. Most clinical trials to-date have used single antiviral agents rather than combinations, and have studied hospitalised patients (i.e. late stage of the disease) when antivirals are unlikely to work. Most prioritised studies have been Phase III ttrials of agents that have not first been proven to reduce viral load in Phase II. Unsurprisingly, none of the repurposed monotherapies studied in this way have yet shown any benefit, and in the case of (hydroxy)chloroquine, have been proven to cause harm. There is an urgent need to rationally develop combination antivirals which reduce viral load, disease severity and risk of onward transmission. For vaccines, rational development meant small Phase II studies to assess antibody response, with successful vaccines taken forward to Phase III. The analogy for antivirals is small Phase II studies to find antiviral combinations that reduce viral load before progressing successful ones to Phase III. Repurposing trials such as RECOVERY and PRINCIPLE which took antiviral monotherapies with limited in vitro activity straight to Phase III have now comprehensively proven to be an inefficient way to find effective antiviral combinations. A more rational approach based on sound principles of antiviral drug development is now required. This work will focus on mathematical modelling of SARS-CoV-2 viral dynamics in order to optimally design and analyse the results for Phase II antiviral trials. Looking at the difference in viral load in patients receiving antivirals compared to placebo is complicated by the fact that in the normal course of the disease, viral load changes by the hour: after initial infection viral load in the nose and throat rises to a peak around the time of symptom onset, and then falls away again such that by Day 7 up to a third of people no longer have detectable virus. Viral load trajectories also differ in patients of different age, disease severity, and potentially when infected with different variants of the virus. Therefore a mathematical model of the expected time course is needed to tease out drug effects from these other variables. Using data we have collected during a recent individual patient-level meta analysis, we will firstly compare the performance of various recently published viral dynamic models on how they predict viral load with time. Using data from two ongoing Phase II trials, FLARE and FANTAZE, the models will be refined to account for new variants (both are double blind randomised trials with daily viral loads and whole genome viral sequencing) and to develop models of the repurposed drug combinations being tested (favipiravir, lopinavir/ritonavir and nitazoxanide). We will also work with Pfizer to apply these models to novel agents in their antiviral pipeline, and apply the models to real world data from three London hospitals to assess whether certain patient groups with prolonged viral shedding may benefit from antiviral treatment. The final output will be a modelling framework for the design and analysis of combination antiviral Phase II trials.

In the development of new drugs, studies are conducted to compare the relative benefits of the drug at different doses with placebo and/or other active drugs (which may also be at different doses). Furthermore, the health outcomes may be measured repeatedly over time. In order to decide whether to take the new drug forward into larger clinical trials, the results from all studies that have been conducted on a new drug are combined in meta-analysis to obtain a pooled estimate of the effect of the drug against placebo or active comparator drugs. Recently methods have been developed to allow for relative benefits to depend on dose and time of measurement in meta-analysis that compares the new drug with placebo (or another drug). However, there may be more than one comparator drug, and they have been measured at various different doses and times. Network meta-analysis is a technique that allows one to compare the relative benefits of multiple drugs that have been compared in randomised clinical trials, where not all drugs have been included in every study. This study aims to combine models of the relationships for the relative health benefits with dose and time, with network meta-analysis. This will allow us to combine information from studies comparing different drugs at different doses and different times, even though those studies may not have included the same dose and times. Decisions as to which drugs to take forward into clinical trials, has substantial impact on all patients. Drug companies have limited resources, and so the decision to invest in one promising drug may come at the expense of another. It is therefore important to make drug-development decisions based on as much available evidence as possible. The methods developed in this project will allow as much existing evidence from comparative studies as possible to contribute to drug development decisions. Furthermore, we will explore the possibility of also incorporating evidence from studies that only sudy a single drug, or studies that compare drugs that we are not directly interested in, but that could help us understand the form of the relationships over dose and time. The methods we will develop may require some strong assumptions. It is therefore very important to check whether those assumptions hold, and a key part of this work will be to look at methods to check assumptions and to check how well the models developed fit to the observed data. Decisions should be based on the most robust model predictions, and sensitivity to any assumptions explored. This project will be a collaboration with project partner Pfizer, who will provide the datasets and expertise in dose and time course modelling. The University of Bristol team brings expertise in network meta-analysis, assessing model fit and consistency, and statistical computing. The collaboration is designed to ensure that the methods developed will be relevant to the needs of drug-development organisations, and the interaction with Pfizer will allow the methods to be used by that organisation, and publications and disemination plans will introduce the methods more widely. This approach will help the methods be used by industry to better invest their resources into drugs to improve patient health based on a better summary of the available evidence.

Almost every single process in the human body is controlled at some level by electrical signals, from the way our hearts beat, the way our muscles move, to the way we think. These electrical signals are generated and controlled by ion channels which act as electrical 'switches' to control the selective movement of charged ions like potassium (K+) and sodium (Na+) into and out of the cell. They therefore play a fundamentally important role in normal cellular function and their dysfunction is known to result in a wide variety of disease states. The 'Two-Pore' or 'K2P' channels are a major subfamily of potassium channels found in many different tissues throughout the human body and are involved in many important physiological processes, in particular the control of electrical activity in nerve cells. However, in marked contrast to many other types of K+ ion channel, the molecular mechanisms which control K2P channel function and their 3D structure are still poorly understood. In an attempt to tackle this problem we have recently identified a range of high-affinity drugs which can be used as molecular tools to probe the structure of the K2P channel and the mechanisms by which they open and close. We have also identified an important difference between two particular K2P channels (TREK and TRESK) which now provides us with a fresh insight into how these channels function and why their gating mechanism is different to other types of K+ channel. In the proposed study we aim to exploit these exciting new findings and to use these molecular tools to investigate the structural mechanism of K2P channel gating. The proposed industrial partnership with Pfizer also provides us with access to a variety of chemical tools, expertise and resources that are not normally available in an academic environment and which place us in a unique position to be able to pursue these goals.

Macrophages are large white blood cells that are the first line of defense against pathogens, but also contribute to much of the pathology of infectious and inflammatory disease. Macrophages are also the bodies cellular waste disposal system, and they are needed for wound healing and for many aspects of normal development. Chickens are of interest because they are an economically important livestock species, they are tractable model in which to study development, and they are vectors for diseases that can affect humans including bacteria that cause food poisoning and avian influenza. This project aims to understand how the production of macrophages is controlled in birds and the function of macrophages in embryonic development. Our hypothesis is that two growth factors, macrophage colony-stimulating factor (CSF-1) and interleukin 34 (IL-34) act through a common receptor (the CSF-1 receptor) to promote the production, migration and function of macrophages in an embryo. In turn, the macrophages are needed for the normal process of organ formation and overall growth in the embryo. To address this hypothesis, we propose to make transgenic animals in which all of the macrophages are tagged with a fluorescent transgene so we can monitor when they appear and how they move about in the embryo. We will make the two growth factors as recombinant proteins, and make antibodies that prevent their actions. And finally, we will test the hypothesis by introducing the factors, or antibodies, into the developing embryo in the egg, to see whether macrophage production or location can be altered, and whether this changes the course of normal development. These are experiments that cannot be done easily in mammals, because the embryo cannot be access in the uterus. If our hypothesis is correct, we will identify candidate modulators of chicken immunity and growth, and also gain an insight into normal development that might be relevant to understanding human pregnancy and developmental defects.

The pharmaceutical discovery process is changing rapidly generating a greater need for conduct chemistry in a more efficient and timely fashion. As the global emphasis towards achieving the highest safety standards and sustainable practices unfolds, it is becoming necessary to re-evaluate how chemical synthesis is conducted. In medicinal chemistry in particular the acceleration of cycle times through high-throughput assaying and fast iterative design has put new emphasis on the reliability of processes and compound preparation times. A more integrated and continuous relay of information regarding the ongoing synthesis and its products in terms of basic characterization, physical properties and their functions needs to be captured. These requirements coupled with a desire for flexible synthetic implementation seem ideally suited to a flow-based approach to chemical synthesis. It is therefore our conclusion that future MedChem programmes will make increasing use of flow techniques and many of these will benefit from the use of solid-supported reagents and scavengers.Monoliths have been proposed and developed for use in solid-supported continuous flow synthesis. Monoliths are a single continuous piece of porous material which can be made from either organic or inorganic materials. These monoliths can be readily generated from various polymers or polymer blends and posses permanent, well-defined porous structures that are independent of the solvent or reagents used. In addition such constructs offer significantly higher mass transfer compared to oval beads as they rely on convective flow instead of diffusion factors (key for reproducible optimisation and small scale synthesis). They also have a higher loading than polymers prepared by suspension polymerization due to the fact that polymerisation occurs within a single phase avoiding the problem of partitioning. It is also possible to prepare these polymer units in any shape and size which is very advantageous for the translation between micro- and meso-flow systems by readily enabling scale up in a more consistent manner.This proposal describes the preparation and use of a series of active reagent functionalized monoliths to be used in flow base synthesis.