Statistical Design & Analysis of Clinical Studies using Personalised Healthcare under Biomarker Uncertainty
Lead Research Organisation:
University of Warwick
Department Name: Warwick Medical School
Abstract
Programme overview:
This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to undertake important applied biomedical research in partnership with industry. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.
Project:
Statistical design and analysis of clinical studies using personalised healthcare under biomarker uncertainty
In collaboration with Roche (Industry partner), the PhD student will address an important issue on the role played by continuous biomarkers in the identification of patients most likely to benefit from a particular treatment within the setting of Personalised HealthCare. In order to identify cut-offs that define the targeted subgroup of patients, novel statistical and machine learning methods will be used on large datasets from clinical trials. The research problem shall form a crucial part of the biomarker-driven drug development programme from a pharmaceutical industry perspective.
This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to undertake important applied biomedical research in partnership with industry. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.
Project:
Statistical design and analysis of clinical studies using personalised healthcare under biomarker uncertainty
In collaboration with Roche (Industry partner), the PhD student will address an important issue on the role played by continuous biomarkers in the identification of patients most likely to benefit from a particular treatment within the setting of Personalised HealthCare. In order to identify cut-offs that define the targeted subgroup of patients, novel statistical and machine learning methods will be used on large datasets from clinical trials. The research problem shall form a crucial part of the biomarker-driven drug development programme from a pharmaceutical industry perspective.
People |
ORCID iD |
| Deepak Parashar (Primary Supervisor) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/R015910/1 | 01/10/2018 | 30/09/2026 | |||
| 2106026 | Studentship | MR/R015910/1 | 01/10/2018 | 30/09/2022 |