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Therapeutic drug monitoring at the point-of-care: clinical prototyping, automated chemistry and machine learning

  • Full or part time
  • Application Deadline
    Tuesday, September 03, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description


This project aims to develop a point-of-care in-vitro diagnostic device, capable of rapidly quantifying drug concentration in patient blood. This will be a critical tool in the delivery of personalised dosing and is made possible through the co-implementation of automated clinical chemistry and machine learning-enhanced data analytics. The project shall cover the engineering of hardware and software solutions that can be deployed as automated workflows in a clinical environment. There will be opportunity to validate this system with real patient samples and to develop predictive dosing algorithms which reference the administered dose, recorded blood levels and patient pharmacokinetic profiles. The dovetailing of these two novel approaches shall enhance the management of narrow therapeutic index (NTI) drugs on a local scale, revolutionising clinical pathways, benefitting both patient and healthcare system.

UCL is one of the leading multidisciplinary universities in the world with around 8,000 staff and 25,000 students. The position is advertised by the Adaptive & Responsive Nanomaterials (AdReNa) Group led by Dr Stefan Guldin (Associate Professor) and based within the Department of Chemical Engineering. Funding is provided through an EPSRC Case Award studentship which is sponsored by Vesynta Ltd, a recent UCL start-up company committed to data-guided personalised drug dosing via rapid patient monitoring. Close contacts exist with NHS and EU partners in clinics and pharmacology. The AdReNa Group are the UK ambassadors for the Opentrons open-source robotic labware start-up based in New York, with whom some further collaborative opportunities exist.

The post is fully funded (stipend and fees) for 4 years and is available as of December 2019.


NTI drugs are used to treat a plethora of conditions including cancer, epilepsy, autoimmune and microbial infections. However, small differences in blood levels of NTI drugs can result in either life-threatening toxicity or in no beneficial effect on the patient, making the accurate dosing of these therapies a significant clinical challenge. Moreover, current dosing protocols do not sufficiently account for the intra- and inter-patient variability their exists to drug response. This issue of sub-optimal dosing is felt most by at-risk patient populations, namely: paediatric, geriatric and neo-adjuvant groups, where varying pharmacokinetics, poly-therapy and poor evidence, hinder efficacious and safe treatment.

Traditionally, optimised dosing via dose titration and therapeutic drug monitoring (TDM) involves invasive and expensive processes; placing demands upon technical staff and infrastructure. As a result, these tests are either not performed or more recently out-sourced to centralised hubs. This prevents timely feedback into the patient’s dosing regimen and leads to a higher incidence of adverse drug events (ADEs). To improve health outcomes and reduce the burden on healthcare services, a rapid and point-of-care method of patient dose monitoring is required.

The successful candidate will have the opportunity to work closely with the UCL start-up Vesynta and will be exposed to intellectual property, device regulation and quality management practices. Close ties exist with industrial, academic and clinical collaborators, including TDM leaders in NHS and EU-based oncology clinics.

The AdReNa group has a track record in using chromatographic and optical approaches to sensitively detect NTI drugs from patient blood. We possess expertise in robotics development and hardware fabrication, to harness this technology towards point-of-care application. The group is currently composed of 7 PhD candidates and 4 postdoctoral researchers and successfully works with industrial partners while maintaining a high publication profile. The group have filed patents and within this PhD opportunities will arise for further intellectual property generation.


The candidate will have, or be expected to obtain, a first degree (minimum 2:1) in engineering (bio, chemical, computer science, electronic & electrical, mechanical or medical), physics or a related subject. The ability to work in an interdisciplinary environment that tackles questions across various fields of biomedical research is expected. Effective written and verbal communication, good time-management and the ability to work in a team are essential.

Funding Notes


Due to funding restrictions the post is to applicants with UK home status, i.e. nationals of the European Union who have been ordinarily resident in the UK for at least three years prior to starting the CDT studentship.
For further information on the work of the Adaptive & Responsive Nanomaterials group please visit: View Website. If you have any queries regarding the vacancy, please contact the principal supervisor of this studentship Dr Stefan Guldin, ().

Please apply at: View Website

Your application should be supported by a CV, a personal statement (approx. 500 words) and contact details of two referees.

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