MRC PRECISION MEDICINE RESEARCH PROJECTS 2023 (GLASGOW REGISTERED)
A novel Deep Learning method for estimating Cortical Thickness trajectories in Alzheimer’s patients and healthy population
Primary Supervisors:
Project summary:
Alzheimer’s disease (AD) is the most common type of dementia and is a growing public health concern which affects over 50 million people globally, expecting to raise to more than 150 million by 2050. A timely diagnosis and stratification are paramount in determining people who are at risk of progressing from healthy to mild cognitive impairment and Alzheimer’s dementia.
Among available quantitative measurements of disease severity and lifespan progression, mean cortical thickness across the brain has been associated with normal aging and neurodegeneration conditions. Having built trajectories for health population and patients with Alzheimer’s symptoms, the goal of the project is to draft disease progression over time and determine individuals who are at risk. Exploiting recent achievements in deep learning segmentation methods, we will develop a fast and reliable deep learning-based cortical thickness estimator, taking advantage of a unique MRI brain dataset composed by 27,000 structural MRI. The student will build a strong and competitive CV taking advantage from a unique combination of interdisciplinary expertise in deep learning, computational neuroscience, neuroanatomy, and neuropsychological clinical research. The successful candidate is required to have prior knowledge in Machine Learning and/or a degree in related field.
Project Q&A Session
Friday 25th November, 1030 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/85112357787?pwd=b3FzWWZPV1pkc09hdGJxWk5oc0lDZz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Bayesian statistical data integration of single-cell and bulk “OMICS” datasets for accurate prediction of clinical outcomes in rheumatoid arthritis
Primary Supervisors:
Project summary:
Rheumatoid arthritis and Psoriasis Arthritis are immune mediated inflammatory diseases that are very challenging to treat. Treatment outcome depends on many factors (genetics, predisposition, BMI, smoking, previous use of drugs) of which many are unknown and hidden to the clinicians. Many datasets exist, but they are asynchronous, so they cannot be easily combined to help in the stratification of patient outcomes. One challenge is generating computational methods to combine and analyse biological (including genomics, transcriptomics and proteomics) with clinical data. In this PhD we propose to generate computational methods (Bayesian statistical framework in the latent space) to integrate existing data from many studies stored in our IMID-Bio-UK database.
First you will learn about immune mediated inflammatory diseases, why they are difficult to treat and what is required for clinically-relevant precision medicine, from our clinical expert Stefan Siebert. Thomas Otto and his bioinformatics team will teach you what data exist,
ranging from genomic, transcriptomic to spatial data. Finally, you will apply and create machine learning methods to integrate these data to help in the stratification of treatment under the supervision of our statistician expert Mayetri Gupta.
This multidisciplinary project serves as an excellent example of precision medicine, combining big data with machine learning to improve the outcome of treatment, and will leave the successful candidate well placed for a career in precision medicine a the end of the PhD.
Boosting innate T cell responses in colon cancer
Primary Supervisors:
Project summary:
The importance of T cells is well established in colorectal cancer, as their abundance in tumours predicts a good outcome in cancer patients. However, for the largest group of colorectal cancers – the microsatellite stable (MSS) group, which represents 80-85% of cases – T cells are largely absent from tumours. Patients with MSS tumours respond poorly to T cell checkpoint inhibitors, such as anti-PD-1. Thus, a greater understanding of how T cells are excluded from MSS tumours is required. Across the genomic landscape of MSS tumours, mutations in WNT/beta-catenin-related genes are the strongest correlative of low T cell infiltration. Thus, the overall goal of this proposal is to mechanistically dissect the interaction between WNT/beta-catenin signalling, immunosurveillance and immune escape in colon cancer. This proposal will specifically focus on intraepithelial lymphocytes (IELs), a group of gut-resident, unconventional T cells consisting of both alpha/beta T cells and gamma/delta T cells, rather than conventional, dendritic cell-educated CD8+ T cells. The Coffelt lab has discovered that IELs recognize and kill pre-cancerous gut epithelial cells. We have found that WNT signalling negatively regulates T cell interacting molecules, but downregulation of these proteins is reversible if WNT signalling is inhibited.
Project Q&A Session
Friday 9th December, 1400 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/84193295568?pwd=YlBDLzFVVVMyQUtrRGFYRXFiTnpMZz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Defining Cellular and Molecular Pathological Signatures to Inform Disease Endotypes and Prognosis in Rheumatoid Arthritis
Supervisors:
Project summary:
The impact of rheumatological disease (e.g. rheumatoid arthritis) on an individual’s well-being is substantial. The associated disease pathology can lead to significant bone loss and subsequent disability. We currently do not know how to determine who will or will not rapidly progress down an erosive pathway, or how to treat this aspect of disease. This project aims to identify cellular and molecular biomarkers that can ultimately inform clinical treatment decisions in rheumatological conditions, with a particular emphasis on the bone-associated pathology. The student will validate and build-on pre-established cellular and molecular signatures for bone erosion identified in patients with rheumatoid arthritis. To achieve this the student will gain experience in working with primary human samples at a cellular and molecular level (i.e., ex vivo tissue culture and single cell RNA sequencing). Furthermore, the student will gain and extensive understanding of bioinformatic approaches to data analysis. In summation, this project will provide a comprehensive training that will enable the student to seamlessly transition between biological, clinical, and computational elements of biomedical science.
Project Q&A Session
Friday 2nd December, 1300hrs
ZOOM Meeting
https://uofglasgow.zoom.us/j/88644535612?pwd=QURVNzRqazFxQ1VCNkF5VjNCbitPZz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Developing a Scottish Type 1 Diabetes Policy Model
Primary Supervisors:
Prof Jim Lewsey
Project summary:
Approximately 1 in 200 people in Scotland have a diagnosis of type 1 diabetes (T1DM); a major cause of blindness, kidney failure, heart attacks, stroke and lower limb amputation. As in many other countries, the numbers of people with diabetes is rapidly increasing largely because of increasing survival. This will lead to an increase in diabetes-related complications that affecting length and quality of life. This PhD project will exploit Scotland’s excellent administrative and clinical databases to develop a T1DM policy model to inform decision making about how to spend money in the health service. This is timely as the number of health care technologies developed for people with T1DM is rapidly increasing and treatment costs for T1DM are very high. Our model will inform how best to use limited resources to achieve the best population health gains and to make decisions equitable for sub-groups of the population.
As well as involving exciting and important research, this PhD project will train the student in key contemporary data science skills using software and version control. Further, the student will develop expertise in statistical and health economic modelling, and learn how to develop web-based apps to improve the translation of results for use by clinical audiences.
Project Q&A Session
Monday 28th November, 1100 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/88162141924?pwd=aFlCYVg4Q2lWM3FIUGtQTmRJU1QxUT09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Does severe mental illness predispose to cardiovascular and metabolic disease via an unfavourable adipose storage profile?
Primary Supervisors:
Project summary:
People suffering from severe mental illnesses (such as depression, schizophrenia and bipolar disorder) have a substantially risk of obesity, diabetes and cardiovascular disease. Reasons for this are unclear, but could be due medication, socioeconomic or lifestyle factors or shared pathological mechanisms. This project use genetic predisposition to serious mental illness to explore whether severe mental illness promotes storage of fat tissue in a way that leads to diabetes and heart disease.
The project will use edpidemiology and statistical genetic approaches, using publicly available data and the UK Biobank study which has extensive genetic and clinical information. This project provides the opportunity to conduct research of global relevance with state of the art resources and in collaboration with leading experts in psychiatric, metabolic and cardiovascular genetics as well as experts in clinical trials of weight-loss intervention.
The student will be trained in the required methods within a data science framework. They are expected to have a BSc or MSc in a relevant field, with an understanding of genetics and statistics. Experience in data science and/or statistical genetics is an advantage.
Project Q&A Session
Wednesday 30th November, 1000 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/81105607507?pwd=VytNdGZ3dGpHaXREandOZ0ZFK0ttZz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Genomic characterization of the virome in acute respiratory illness with no identifiable aetiology: supporting improved diagnostics in Malawi
Primary Supervisors:
Project summary:
The cause of lower respiratory tract infections (LRTI) is often difficult to diagnose, especially in low-and middle-income countries (LMICs) where diagnostic tests are limited. Additionally, the pathogens circulating in LMICs may differ to targets of current tests or the infection may be due to an unknown virus from zoonotic origin. Unfortunately, this lack of understanding of the circulating pathogens and their impact on the disease burden affects predominantly Sub-Saharan Africa. Metagenomic sequencing provide an agnostic diagnostic tool for investigating the diversity of pathogens infecting a patient and circulating within a population.
We propose to use this precision medicine approach to provide an unbiased investigation of respiratory samples collected from a cohort of adults with hospitalized LRTI in Blantyre, Malawi between 2013 and 2015. No aetiology was identified in a third of the patients. We hypothesise that these infections are due to viruses untargeted by current diagnostic tests, known viruses that have diverged sufficiently from targeted viruses in the current test, and/or unknown viruses of zoonotic origin. Identifying novel viruses through this method will contribute to better diagnostic and management of LRTI in Malawi.
The student will be trained in a combination of bioinformatics, genomics, general virology, respiratory virology and virus evolution.
Project Q&A Session
Tuesday 6th December, 1000 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/85685283104?pwd=N2hTYmhsL2duVTRPdkNCb2Z5UnNkdz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Harnessing the microbiome to improve therapeutic efficiency in childhood acute lymphoblastic leukemia
Primary Supervisors:
Prof Christina Halsey
Project summary:
Cancer is the leading cause of death for children and young adolescents, and despite improvements in survival, leukaemia accounts for about a quarter of these deaths. Paediatric Acute Lymphoblastic Leukemia (pALL) is the most common childhood cancer. Maintenance therapy with intensive multi-agent chemotherapy is currently not personalized, and lasts 2-3 years. Even if cured, many survivors have significant treatment side-effects resulting in late mortality, poor quality of life and accompanying health and societal impacts. Hence, there is an urgent need to develop more effective, and less toxic treatments for childhood ALL.
With this interdisciplinary project, we will study how the microbiome changes during pALL progression. We will use in vitro experiments to identify which microbiome-derived metabolites can affect and predict response to chemotherapy. Ultimately, we will employ advanced preclinical mouse models of pALL to modulate the microbiome to reduce disease progression and improve therapy efficacy
Project Q&A Session
Friday 2nd December, 1030 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/88120410579?pwd=UlZCcUpSM0VHVHlsR0x4bUdRUnV0dz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Identifying Clinically Relevant Metabolite and Lipid Markers for Precise Diagnosis and Treatment of CNS-Leukaemia
Primary Supervisors:
Project summary:
Cancer is the leading cause of death for children aged 1-14 years with about a quarter due to leukaemia. Furthermore, even successful treatment causes significant side-effects. The commonest long-term effects in children with acute lymphoblastic leukaemia (ALL) are problems with IQ, learning and memory which affect 20-40% of survivors. This reflects the use of toxic chemotherapy to prevent ALL recurrence within the brain/central nervous system (CNS). Previous work has identified that ALL cells undergo profound changes in their metabolism in response to the CNS microenvironment. In this project, advanced metabolomic strategies will be used to define the biochemical changes in cerebrospinal fluid (CSF) samples from murine models with and without ALL. These data will be compared against an existing human CSF metabolomic database to characterise and validate candidate biomarkers. The student will obtain practical experience of animal handling, high-grade mass spectrometry as well as becoming proficient in the bioinformatic and statistical interrogation of the data sets generated. The project is part of a larger, long-term study of CNS leukaemia and offers the potential to discover clinically relevant biomarkers that can be used to direct the diagnosis and treatments for ALL.
Project Q&A Session
Monday 5th December, 1530 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/89025815335?pwd=d3dzMlFOUDlIdzlyYnk0MTMvYUd1QT09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Immune Spatial Relationships within the Malaria Spleen (ISREMAS)
Primary Supervisors:
Project Summary:
Immunity to malaria takes many infection exposures to develop, in contrast resistance to disease (or disease tolerance) is quickly acquired. We believe the secret to this conundrum lies in the spleen. Although the spleen is the key immune organ responding to malaria infection, the interactions of malaria parasites with immune cells in the human spleen are poorly characterised. This project aims to address this knowledge gap, using an ex vivo spleen perfusion model, that will allow us to introduce malaria infected Red Blood Cells (RBC) then visualise their interactions with immune populations in the spleen using state of the art techniques, including intravital, multiphoton laser scanning microscopy (MPLSM) and spatial transcriptomic profiling. These studies will a detailed map of the impact of malaria infection on immune function in the human spleen that is absent from the current literature. Together with our ongoing BBSRC-funded project investigating the molecular basis of malaria immunity and disease tolerance, this information will lead toward precision medicine strategies to reduce disease or promote immunity in malaria infection.
Project Q&A Session
Friday 9th December, 1400 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/89835679774?pwd=N0NUa0pwVFZ6WUtMdG1pc3hwTDlpQT09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Metabolomics to Stratify Psoriatic Arthritis and Direct Precision Treatments
Primary Supervisors:
Project summary:
Psoriatic arthritis (PsA) is a common chronic inflammatory condition affecting the joints and musculoskeletal system. PsA is characterized by considerable clinical heterogeneity, making the disease difficult to assess in routine clinical practice. Treatments are focused on controlling inflammation in affected joints, however patient responses to these treatments are varied and unpredictable. Therefore, there is a need for biomarkers that stratify patients according to their molecular endotypes and predict treatment response. There is increasing evidence that PsA has a significant metabolic component and that metabolite signatures may be key in chronic inflammatory conditions. In this project, advanced metabolomic strategies will be used to correlate the biochemical changes in blood and urine samples from PsA patients with clinical phenotype and response to therapeutic interventions. The student will obtain practical experience of processing of liquid biopsy samples and high-resolution liquid chromatographymass spectrometry as well as becoming proficient in the bioinformatic and statistical interrogation of metabolomic data sets. The project ties into a large project focused on defining molecular changes in PsA (HIPPOCRATES Innovative Health Initiative (IHI) Consortium www.hippocrates-imi.eu/) and offers the potential to develop tools for improving prognostic evaluation and directing treatment decisions under the supervision of experts in the field.
Project Q&A Session
Wednesday 30th November, 0915hrs.
Zoom Meeting
https://uofglasgow.zoom.us/j/81590023755?pwd=SGJOSTF6Q2JjTEp6VmZIQ0ljTXF4dz09
Identifying blood brain barrier signatures in cerebral malaria and central nervous system infections to inform treatment targets and patient stratification
Primary Supervisor:
Dr Christopher Moxon
Project summary:
Cerebral malaria is the deadliest complication of malaria caused by Plasmodium falciparum. P. falciparum infects red blood cells that stick to blood vessels in the brain, leading to fluid leak–“Blood-brain-barrier (BBB) breakdown” and potentially fatal brain swelling. Identifying the cause of BBB breakdown is key to identifying new treatments but has been elusive using prior approaches. Rapid advances in spatial biology including spatial transcriptomics and multiplex imaging techniques have enabled a step-change in our understanding of such complex biological processes. We will employ these spatial techniques on an archival collection of post-mortem cerebral malaria samples to characterise in unprecedented detail what individual cells in the brain are doing and how they are interacting with other cells and with the parasite – enabling prediction of series of events leading to BBB-breakdown. We will then use a cell culture model to validate these findings and test potential treatments. These data will provide vital steps to identify treatments that prevent BBB-barrier breakdown and improve outcome in patients.
Project Q&A Session
Monday 5th December, 1400 hrs
ZOOM Meeting:
https://uofglasgow.zoom.us/j/84945028511?pwd=T0FTWVVNK3U2MnhCNXJGbmdOS05xQT09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Omics-driven Stratification of Patients in Blast Phase Chronic Myeloid Leukaemia: From Signatures to Treatments
Primary Supervisors:
Project summary:
In chronic myeloid leukaemia (CML) the disease is initiated and driven by leukaemic stem cell (LSCs) which have acquired the BCR-ABL1 oncogene. Whilst most chronic phase CML patients respond well to life-long tyrosine kinase inhibitor (TKI) therapy, patients with aggressive blast phase (BP) disease have drug-resistant, heterogeneous LSC sub-populations, fail TKI therapy and their prognosis remains very poor. Thus, there is urgent clinical need to develop novel therapies for BP patients. This projects aims to determine computationally and experimentally which BP patients may respond most favorably to agents that we have identified in our laboratories to target LSC. The project will make use of existing RNA-seq and DNA-seq datasets that inform on the activity of LSC drug targets, and will generate additional RNA-seq experiments for BP patient samples at diagnosis and at relapse. All of this ‘omics data will be integrated computationally and state-of-the-art machine learning and artificial intelligence will be used to stratify samples with respect to LSC target activity and anticipated drug responses. Based on these predictions, samples will be tested with agents in the laboratory to determine whether they are effective at eradicating LSC populations in vitro and in pre-clinical mouse models. The outcomes of this project are likely to inform the design of future clinical trials for BP disease.
Project Q&A Session
Friday 2nd December, 1100 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/2760997553?pwd=RE1qWTNjNW5UVldNQWxsUS82d3h5dz09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
Predicting homologous recombination deficiency (HRD) using machine learning and experimental immunofluorescence assays to optimize targeting of PARP inhibitors
Primary Supervisors:
Dr Ross Carruthers
Project Summary:
PARP inhibitors are particularly effective in treatment of high grade serous ovarian cancers (HGSOC) that are homologous recombination defective (HRD). There is currently no consensus on a gold-standard HRD test. Using WGS data from a cohort of HGSOCs we have used machine learning to develop a predictive model for HRD trained for the first time in HGSOC, the cancer type with the highest prevalence of HRD. Our model aims to comprehensively capture the role of extensive genomic rearrangements which characterise this and many other cancer types. This project aims to improve, validate and expand the potential clinical impact of this model. First, we want to establish if the model performs well for non-ovarian tumour types. Second, we aim to explore the relationship between the model developed and HRD as assessed by a functional HRD assay (rad51 foci by immunofluorescence). Finally, given that WGS is difficult to deliver in clinical practice our second priority is to evaluate if the model can perform well using existing data from more clinically applicable genomic assays (shallow WGS, WES, panel).
Project Q&A Session
Thursday 8th December, 1430 hrs.
Teams Meeting ID: Meeting ID: 336 965 921 132
Please email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.
VascuSenS – A platform for active self-reporting implantables for cardiovascular disease
Project summary:
Cardiovascular disease (CVD) is the single most significant medical, social and financial problem, both in Scotland and across the globe, with one third of global mortality attributable to vascular complications (WHO Stats 2022). These include the majority of heart attacks, strokes and loss of central vascular access (BHF, Heart UK), essential for chronic kidney disease patients requiring renal dialysis (Kidney Research, UK), but also for the delivery of chemotherapy drugs for cancer patients (Cancer Research UK).
Patient care can be significantly improved by integrating electrical biosensors into existing medical devices to report on vascular status, such as blockages and blood clots. Our group have devised active vascular implants that can wirelessly detect biological conditions in real-time. Not only does this provide an alert for patients and clinicians but also offers the potential to detect and treat the very earliest signs of disease, thereby avoid costly inventions. To achieve this high throughput, testing of cell/sensor interactions is required. The successful candidate will be trained in the latest bioengineering techniques, devise new labware systems of quantitating cell sensor interactions that directly lead to preclinical testing of our devices. They will contribute to developing new understanding and advancing our technology. Not only finding new ways to miniaturise and integrate the sensors to appropriate 2D and 3D devices but also understanding their interactions with biological materials. Detecting and treating restenosis and blot clots would be transformative to healthcare and would significantly reduce clinical complications, inpatient stays, follow-up and repeat interventions by stratifying the patient cohort.
ICASE - MRC PRECISION MEDICINE RESEARCH PROJECTS 2023 (GLASGOW REGISTERED)
MRC’s iCASE awards provide students with experience of collaborative research with a non‐academic partner, enabling the student to spend a period of time with the non-academic partner (usually no less than three months over the lifetime of the PhD).
Augmentation of PDE4D7 activity as a novel treatment strategy for men that have been stratified with high risk prostate cancer
Primary Supervisors:
Industrial Partner: Philips Research (Eindhoven)
Dr Ralf Hoffmann
Project summary:
Prostate cancer becomes more difficult to treat as the disease progresses so it is important to have diagnostic tools to be able to stratify men into different risk groups. Over the last decade we have shown that a downregulation in the expression of the phosphodiesterase PDE4D7 happens in prostate cancer cells as they transition to an aggressive stage that is unresponsive to androgens. This switch increases cancer cell proliferation renders the cells insensitive to pharmaceuticals and alters the transcriptome to an androgen independent genotype. The prognostic power of PDE4D7 in metastatic PCa positions this enzyme as an attractive drug target where men at risk of deleterious biological outcomes could be given treatments to augment PDE4D7 activity. We have phenocopied aggressive PCa in the laboratory by genetically silencing PDE4D7 with siRNA in the androgen sensitive LNCaP PCa cell line which then adopt the aggressive neoplastic growth phenotype. We propose to use this cellular model to test the hypothesis that the augmentation of PDE4D7 activity (with novel peptide activators and an innovative PDE4D7 RNA vaccine) can not only reprogramme the molecular genotype and retard the aggressive growth phenotype but also resensitize the cells to currently used chemotherapies.
If successful we will trial the best treatment in an animal model of prostate cancer that is derived from our reprogrammed cells. Our ultimate goal is to develop a companion therapeutic to use alongside the prognostic power of PDE4D7 in stratifying patients into “at risk” groups.
Investigating the Therapeutic Efficacy of a First-in-Class MDM2 Dimerisation Inhibitor Against MDM2-MDMX Driven Acute Myeloid Leukemia
Primary Supervisors:
Industrial Partner: Disruptyx Therapeutics Limited (DTx)
Dr Connor Blair
Project summary:
MDM2 is a protooncogene which plays an essential role in negatively regulating the tumour suppressor p53 (TP53). TP53 is important for inducing cell cycle arrest and apoptosis in response to cellular stress. Utilising DTx-098D-R, this project will look to develop a precision medicine approach to treating MDM2 ± MDMX driven acute myeloid leukemia (AML). DTx-098D-R is a first-in-class cell-penetrating peptide capable of selectively binding MDM2, disrupting formation of the MDM2-MDM2 and MDM2-MDMX complex, and subsequently blocking its E3 ligase activity. DTx-098D-R potently inhibits cancer cell proliferation, in-part through upregulation of pro-apoptotic signaling pathway(s). Crucially, DTx-098D-R anti-proliferative activity occurs independent of TP53 mutational status, highlighting a role for DTx-098D-R in TP53 wild-type and TP53 mutant cancers.
Current MDM2 inhibitors (e.g., Idasanutlin, ALRN-6294, etc.) solely regulate TP53-dependent signaling associated with MDM2, making them appropriate therapeutic options for TP53 wild-type cancers. However, these therapies are in-effective against cancers that harbour a loss of function TP53 mutation - de-novo AML (~5-10%), therapy-related AML (~30%) and elderly AML patients (70%). As MDM2 ± MDMX are precedented drivers of TP53 wild-type and TP53 mutant AML, novel approaches to exploiting MDM2/MDMX (independent of TP53) are urgently needed especially for therapy related and elderly AML patients who have a dramatically poorer prognosis and limited treatment options. DTx-098D-R represents such a novel approach.
Utilising a bespoke panel of human AML cell lines and patient-derived primary samples, this project will assess the therapeutic efficacy of DTx-098D-R against TP53 wild-type and mutant AML alone and in combination with current standard of care chemotherapeutics.
Project Q&A Session
Friday 2nd December, 10-12 hrs.
ZOOM Meeting
https://uofglasgow.zoom.us/j/83498101995?pwd=V1I2Z0RPM09PSHIwWWxzVzhMSDRvUT09
Email: PrecisionMedicine-dtp@glasgow.ac.uk for password information.