Opportunities to test and bring new drugs and technologies to clinical care are delayed by our current clinical research ecosystem that is often extraordinarily complex and expensive.
It is now recognised that existing datasets can be used to help redesign clinical trials, by building statistical models as a proof of concept. Realistically, AI, machine learning, and deep learning tools and techniques will be able to analyse existing dataset at a much quicker pace to improve clinical trials ultimately designed.
Exploristics flagship simulation platform KerusCloud aids the design and analysis of clinical trials and has enabled customers to achieve real world success by transforming their clinical development plans.
Clinical context and detail of the proposed Project:
This collaboration will provide the opportunity for the successful student to work on an innovative project that will explore respiratory datasets and design clinical trials in conditions such as bronchiectasis and Cystic Fibrosis (CF) to accelerate drug development and ultimately benefit patients in these populations.
The proposed PhD project has the following objectives:
- Develop expertise in key data science methods (relevant data opportunities, optimised data mining, automation)
- Develop code to leverage large volumes of data to provide insights on clinical trial design
- Use real-world data from existing respiratory sources to design/redesign clinical trials that will support the development of new medicines in key respiratory conditions. In the industry placement to provide technical expertise both internally and as a service to customers.