Evaluating anti-infective drugs

Modelling viral load kinetics during the COVID-19 pandemic: public health applications and lessons learned, Dr James Hay

One of the most controversial topics during the COVID-19 was the implementation of occupational health testing programmes and guidelines for at-home testing to detect, isolate and release infectious individuals. Much of the evidence to guide these policies initially came from mathematical modelling studies in lieu of sufficient data on viral kinetics; a topic which saw little focus from infectious disease modellers prior to the pandemic. In addition, as the landscape of SARS-CoV-2 infection changed with new variants, immunity from vaccination and infection, and availability of antivirals, models and assumptions required constant updating. In this talk, James will give a brief overview of key mathematical modelling results and data on SARS-CoV-2 viral kinetics (timing, peak and variation of viral load following infection) and testing which he and others generated during the COVID-19. He will specifically focus on data from the USA National Basketball Association occupational health testing programme, which provided an unprecedented volume of longitudinal RT-qPCR testing data through the wildtype, Alpha, Delta and Omicron waves. Quantifying the time course of acute respiratory virus infections in this way has important implications for public health policies around screening, isolation, and surveillance, particularly in the context of vaccines and therapeutics.

TREAT-GNB, a platform trial for severe Gram-negative bacterial infections , Dr Mo Yin

Current clinical trial models for carbapenem-resistant Gram-negative bacterial (CRGNB) infections pose significant barriers to translation including overly stringent inclusion criteria that focus on limited types of infections, rigid randomisation treatment options, and a lack of access to patient cohorts at-risk of CRGNB infections. The ADVANCE-ID (Advancing Clinical Evidence for Infectious Diseases) network was jointly established by the Wellcome Trust, the University of Oxford, Mahidol University, Christian Medical College Vellore (CMC Vellore), and Singapore academic institutions to promote transnational research collaboration and capacity building for a sustainable pipeline to conduct large-scale clinical trials in infectious diseases. We challenge the existing paradigm with our platform trial, TREAT-GNB, which adopts a novel trial design: the Personalised RAndomised Controlled Trial (PRACTical) design. The main strength of the PRACTical design is a flexible randomisation list which tailors treatment based on individual patient requirements. Of all the regimens under consideration, study participants would be randomly assigned only to those regimens that were considered clinically reasonable for that patient at that time, incorporating antimicrobial susceptibility, toxicity profile, and physician judgement (ie using a personalised randomisation list). The set of patients with the same personalised randomisation list would then form the unit analogous to a trial in network meta-analysis. The design allows for existing antibiotic combinations to be included in the randomisation list, with potential to engage industry partners to add novel FDA- or European Medicines Agency-approved antibiotics to the randomisation lists, as they become available, so that they can be ranked against other regimens. Regimens will be ranked according to efficacy, resistance phenotype, safety and cost. In this talk, the speaker will introduce the PRACTical study design and its application for CRGNB infections. 

Influenza, Dr Phrutsamon Wongnak

Viral respiratory infections represent a major global health threat, contributing significantly to morbidity and mortality, particularly in high-risk populations. Developing a robust pharmacodynamic framework to measure and compare the efficacy of antiviral agents is essential for informing intervention strategies aimed at mitigating the public health impact of these infections. This presentation outlines the use of adaptive open-label, phase 2, randomised controlled platform trials and the measurement of viral clearance rates, rather than time to PCR negativity, as a primary outcome in assessing antiviral efficacy. This approach is being applied to infections caused by SARS-CoV-2, influenza, and respiratory syncytial virus.

Once randomised, daily serial oropharyngeal swab samples were collected from participants, and viral densities were measured daily using qPCR. A hierarchical Bayesian modelling framework was employed to estimate the viral clearance rate, defined as the slope of the log-linear decay in viral densities. The antiviral effect is defined as the relative change in the viral clearance rate among participants receiving treatment interventions compared to those who did not receive any treatment.

Additionally, in infections with highly variable viral density dynamics over time, such as SARS-CoV-2, the impact of these temporal variations on head-to-head comparisons of antiviral efficacy and strategies for optimising sampling designs are discussed.

A within-host model of chronic Trypanosoma cruzi infection to help inform drug and regimen selection, Miss Somya Mehra

Trypanosoma cruzi is a kinetoplastid parasite causing Chagas disease, a major neglected tropical disease thought to affect over 6 million people worldwide. The current recommended treatment is 8 weeks of twice daily benznidazole, a regimen which is poorly tolerated in around a third of patients. There has been recent interest and funding in exploring intermittent treatment regimens and developing novel anti-parasitic drugs for T cruzi, with two candidates now in phase 1 trials. However, assessment of anti-parasitic efficacy in vivo for the treatment of chronic disease remains challenging. While correlates of blood-stage parasitaemia can be obtained using PCR methods, patients with chronic Chagas disease typically harbour very low parasite densities in the blood, close to the lower limit of quantification. Parasite biomass in the tissue additionally remains unobserved with current methods. 

In order to characterise the dose-response relationship for drugs against tissue stage and blood stage parasites, it is necessary to develop stochastic within-host models of T cruzi parasites. Multitype branching processes yield a natural theoretical framework to explore the cycling of T cruzi parasites between the bloodstream (trypomastigotes) and a tissue reservoir (amastigotes), including determinants of the steady state parasite burden; the probability of stochastic extinction at low parasite densities; and the potential consequences of drugs with differential effects on tissue and blood stage parasites. Interrogating simple models of T cruzi parasite clearance and replication can yield insights of practical value.

Optimal Resource Allocation for Infectious Diseases, Dr David Price

Design of experiments is not a new concept. However, much of the classical experimental design work was developed for the purpose of hypothesis testing, ie how many resources are required to ensure sufficient statistical power to test a formal hypothesis. In contrast, many disciplines of research, including discovery science and public health, are often more concerned with estimation of a quantity or learning about a system, rather than hypothesis testing.

This talk will introduce the optimal design framework, a decision-theoretic approach to get the most information from the limited available resources. We will consider scenarios where the purpose is to either estimate parameters or discriminate between competing models as well as possible. Examples in each case will relate to learning about infectious disease dynamics.

Dr James Hay

Dr James Hay

James is a research fellow at the University of Oxford Nuffield Department of Medicine funded through a Wellcome Trust Early Career Award. He completed his PhD at Imperial College London in 2019 and spent three years as a postdoc at the Harvard Chan School of Public Health. His expertise is in infectious disease modelling, with a specific interest in using quantitative biomarker data, such as viral loads and antibody titers, to understand and track the dynamics of infectious diseases, particularly influenza and SARS-CoV-2. He typically uses Bayesian multi-level models to link data and models across scales, from within-host models of viral kinetics and immune responses to agent-based models of disease spread.

Dr Mo Yin, University of Singapore, Singapore

Dr Mo Yin, University of Singapore, Singapore

Dr Mo Yin is an Infectious Diseases physician and a clinician scientist based at the National University Hospital, Singapore. Her research interest is in antimicrobial resistance and emerging infectious diseases. Driven by the ideal of using quality clinical research to improve patient outcomes and propel global policies, Dr Mo Yin designs and leads large multinational clinical trials which focus on pragmatic clinical solutions. In addition, Dr Mo Yin has expertise in mathematical modelling, statistics, bioinformatics and qualitative research. She is the deputy director of the ADVANCE-ID, a large clinical trial network consisting of over 60 hospitals globally. She has received numerous awards for her achievements in clinical care, research and teaching, and served as an external consultant to the World Health Organisation and Public Health England. Dr Mo Yin obtained her MBBS from the National University of Singapore and DPhil from the University of Oxford.

Dr David Price, University of Melbourne, Australia

Dr David Price, University of Melbourne, Australia

Dr David Price is a Senior Research Fellow in the Department of Infectious Diseases and Melbourne School of Population and Global Health, at the University of Melbourne. His primary research interests are in the development and application of statistical methods for the study of infectious diseases, particularly regarding the optimal use of resources in experimental and observational investigations. He works on infectious diseases across multiple scales, from within-host infection dynamics to multi-site clinical trials and population-level epidemiological modelling and analysis. At the Doherty Institute, he is co-lead of the Computational Sciences and Genomics Cross-Cutting Discipline and leads a team providing collaborative statistical and modelling expertise to a breadth of infection and immunity research. 

Dr Phrutsamon Wongnak

Mahidol Oxford Research Unit, Thailand

Dr Phrutsamon Wongnak

Mahidol Oxford Research Unit, Thailand

Dr Phrutsamon Wongnak currently serves as a statistician for the PLATCOV trial and is an active member of the mathematical modelling group at the Mahidol Oxford Tropical Medicine Research Unit (MORU). With a background in veterinary medicine and a strong passion for public health, he is committed to advancing evidence-based decision-making and improving health policies, related to human, animal, and environmental health, through computational approach. His current projects primarily focus on assessing the effects of antivirals on accelerating viral clearance rates in randomised controlled trials, particularly for infections caused by SARS-CoV-2, influenza, and respiratory syncytial virus, contributing to more effective treatment strategies and interventions.

Miss Somya Mehra, Mahidol Oxford Tropical Medicine Research Unit, Thailand

Miss Somya Mehra, Mahidol Oxford Tropical Medicine Research Unit, Thailand

Somya has recently commenced a DPhil in the Nuffield Department of Medicine at the University of Oxford, focusing on mathematical models of chronic Chagas disease. Since late 2022, she has been based at the Mahidol Oxford Tropical Medicine Research Unit in Bangkok, where she has developed within-host models of relapse dynamics for vivax malaria, and classification models for falciparum malaria treatment failure. Prior to this, she had a placement at the Harvard School of Public Health as a Fulbright Future Scholar, working on the estimation of relatedness between malaria parasites. She completed her previous studies, including an MSc in Mathematics and Statistics, at the University of Melbourne, where she concurrently worked as a research assistant on stochastic and epidemic models of malaria.

Professor David Price, Vice-Provost, Research, UCL

Professor David Price, Vice-Provost, Research, UCL

David is Vice-Provost (Research) at UCL and Professor of Mineral Physics.

David has an undergraduate degree and a PhD from the University of Cambridge. He was a Fulbright-Hayes Scholar and Research Associate at the University of Chicago, and a Research Fellow at Clare College Cambridge, before coming to UCL in 1983 as a Royal Society University Research Fellow. At UCL, he was appointed Professor at the age of 34, and later served as Head of the Department Earth Sciences, and as Dean of Mathematical and Physical Sciences, before being appointed to his current position of Vice Provost in 2007.

He was one of the first to establish the now major interdisciplinary field of computational mineral physics, and has published over 230 research papers. He was awarded the Schlumberger Medal of the Mineralogical Society of Great Britain in 1999; the Murchison Medal of the Geological Society of London in 2002; and in 2006 he was awarded the Louis Néel Medal of the European Geosciences Union for "establishing the importance of computational mineral physics in Earth sciences and for outstanding contributions to the physics of the Earth’s core". He is a Member of the Academia Europaea and an Elected Fellow of the American Geophysical Union and of the Mineralogical Society of America. He has been an editor of Elsevier’s "Earth and Planetary Science Letters" (2005-8), and was President of the Mineralogical Society of Great Britain and Ireland (2004-6). He was a member of the UK’s HEFCE RAE2008 sub-panel on Earth and Environmental Sciences, and is now chair the REF2014 sub-Panel in this area. He is Chair of Governors of the UCL Academy School; a Council Member of the STFC; a non-executive Director the North Middlesex University Hospital NHS Trust; a Member of the Knowledge Advisory Group of the World Economic Forum; and a Member of Elsevier’s Academic Executive Advisory Board.

The success of malaria control relies on the availability of highly effective antimalarial drugs. The widespread emergence of drug-resistant parasites now threatens the efficacy of first-line treatments, necessitating the urgent development of novel regimens and combinations of existing and new therapeutic agents to ensure adequate cure of malaria. 

To addressing this challenge, mechanistic within-host models that integrate the blood antimalarial drug concentrations with the parasite-time profile (also known as antimalarial pharmacokinetic-pharmacodynamic (PK-PD) models), provide a valuable decision tool for determining optimal antimalarial dosing regimens.

This presentation will provide an overview of published antimalarial PK-PD models, highlighting the differences in the mechanistic structure to capture malaria biology, and the relationship between drug concentration, drug-drug interaction and pharmacodynamic effect. Additionally an evaluation of the statistical approaches used for model validation against clinical data will be described, and a three step framework for the development and evaluation of PK-PD models recommended.

Professor Julie Anne Simpson, University of Melbourne, Australia

Professor Julie Anne Simpson, University of Melbourne, Australia

Professor Julie Simpson is Head of Biostatistics at the Melbourne School of Population and Global Health and Director of the Methods and Implementation Support for Clinical and Health research (MISCH) Hub at the University of Melbourne, and a Visiting Professor of the University of Oxford. She has 30 years’ experience collaborating on multidisciplinary research projects with clinicians, laboratory scientists, epidemiologists and health policy-makers at universities and hospitals worldwide, and has published >370 papers. Her main area of research is the integration of biostatistics and mathematical modelling to improve the control of infectious diseases.

Chikungunya is an arboviral infection whose clinical presentation is very similar to those of dengue and zika. Fever occurs in the great majority of individuals and viremia is measured in all patients till 72 hours of the beginning of symptoms. Viral decay is homogeneous and most individuals are negative at 4 days after they are first seen. Although most symptoms are limited to the first days of infection, at 7-9 months after infection, 50% of patients who had chikungunya still reported some degree of discomfort and 25% needed to take some kind of pain killer to decrease symptoms. In patients with Chronic Chikungunya infection, there are 3 major clinical syndromes: (i) Rheumatoid arthritis-like; (ii) Spondyloarthropathy-like  and (iii) fibromyalgia-like syndromes. This classification of clinical presentation is useful for therapeutic purposes and follow-up of patients. Most individuals report their disease is significantly better at 18 months after infection. Experimentally, Chikungunya virus infection of mice is associated with transient viremia and viral infection of the site of infection and significant persistent inflammation and TNF expression at the dorsal root ganglia that innervates the infective site. These studies show that the viremia that follows chikungunya infection is high and has a kinetics compatible with the testing of antiviral compounds. In participants, with chronic infection, aggressive anti-inflammatory and pain management is needed for return to normal activities, especially because there is much impact on quality of life and the disease tends to very limited in duration.

Professor Mauro Martins Teixeira, Federal University of Minas Gerais, Brazil

Professor Mauro Martins Teixeira, Federal University of Minas Gerais, Brazil

Mauro Teixeira is professor of Immunology at the Federal University of Minas Gerais (UFMG). His MD if from UFMG and PhD from the University of London. He works with inflammation in the context of infectious and chronic inflammatory diseases. His group has provided extensive preclinical and more recently clinical evidence that anti-inflammatory drugs may be useful as adjunct treatment of infectious diseases. He has collaborated extensively with the Brazilian effort to design trials and evaluate strategies to control arboviruses, including vector and vaccine trials. He participates in several relevant international cooperations, including CERCLE (Coalition for Equitable ResearCh in Low-rEsource settings), DNDI-Dengue Alliance, PlatCOV (with MORU Tropical Health in Thailand) and Coordinating Research on Emerging Arboviral Threats Encompassing the Neotropics (CREATE-NEO, with UTMB). He is president of the International Association of Inflammation Societies.

Pharmacometric studies allow for greater efficiency in determining effects which translate to smaller sample sizes. Certain rare diseases with particular profiles, and particular drugs, discussed in this talk, may allow for sample sizes of 1.

Dr William Schilling, Mahidol Oxford Tropical Medicine Research Unit, Thailand

Dr William Schilling, Mahidol Oxford Tropical Medicine Research Unit, Thailand

Will is a an Infectious Diseases/ Microbiology Registrar working at St George’s Hospital London and was a research physician working at the Mahidol Oxford Tropical Medicine Research Unit (MORU) prior to this. At the time of reading this biography he may or may not now have a DPhil.

Will’s work at MORU focussed on COVID-19. This was initially a large multinational prophylaxis study of hydroxychloroquine/ chloroquine but as the pandemic progressed, a platform pharmacometrics study assessing various therapeutics in early treatment- PLATCOV. Subsequently, Will has been involved in similar studies in influenza, RSV and dengue.

Will has previous experience working in Medicine in Mbarara, Uganda. He hopes to one day do a 5K or 10K fun run.

Regulatory agencies have been adjusting their requirements for early clinical development of anti-infective agents, taking into account scientific advances in the area of PK/ PD so make dose finding studies as efficient as possible. PK/ PD evaluations are considered now standard practice for antibacterial medicines. Proper preclinical evaluation of PK/ PD together with Phase I PK and safety data could allow skipping formal dose finding studies in the context of antibacterial agents development. In other areas, clinical trial to select appropriate doses for confirmatory clinical trials are still needed. Surrogate endpoints based on a pharmacodynamic marker could be considered based on the level of confidence that has been gathered with respect to specific microbiological evaluations, eg viral loads measurement in upper respiratory tract for new antivirals for respiratory viruses. More work is needed to advance translational medicine that could increase the efficiency of clinical development for new treatments for infectious diseases.

Dr Marco Cavaleri, European Medicines Agency, Netherlands

Dr Marco Cavaleri, European Medicines Agency, Netherlands

Marco Cavaleri is Head of Department, Public Health Threats. He is the Chair of EMA Emergency Task Force (ETF) and responsible for EMA activities for emergent pathogens, vaccines and AMR. He serves in different advisory groups at WHO, including PDVAC, AMR priority pathogens and R&D Blueprint SAG and clinical trials working group.

Marco Cavaleri is a Pharmacologist who spent several years in industry in R&D mainly in the area of anti-infectives covering different positions in preclinical and clinical development of new antibacterial, antitubercular and antifungal agents. He has expertise in microbiology, animal models, PK/ PD and clinical trial design for antibacterial and TB drugs, from early phase to late stage clinical trials. He is involved in several areas of vaccines and innovative therapies development, such as bacteriophages, that could tackle AMR.  He has been driving the EMA AMR strategy on human medicines since 2009 including the international partnerships that lead to alignment of clinical trials requirements for new antibacterial agents with FDA, PMDA and HC. He is co-author of several publications related to AMR, TB, antibiotics, vaccines, and phages.