Post-doctoral fellow/PhD position in Translational Pharmacology

Project title: PKPD relationships and dose rationale for drug combinations in tuberculosis. Background: Tuberculosis is the leading cause of death by an infectious disease worldwide. According to the World Health Organization (WHO), an estimated 10 million people became ill with tuberculosis in 2018, and 2 million died. Standard tuberculosis treatment is based on a combination regimen of four drugs that were all developed more than 60 years ago. Treatment lasts for at least six months and, in the case of resistance to the standard drugs, can be as long as two years. The current drugs are inefficient by today's standards and a new, faster-acting and safer treatment is required to reduce the length of therapy and to overcome the threat of drug-resistant strains. Until now, the development of new drugs has been slow and their incorporation into tuberculosis treatment regimens conducted in a sequential manner. While pharmacokinetic-pharmacodynamic concepts and advanced quantitative clinical pharmacology principles have been integrated into the clinical development of compounds across many therapeutic areas, human dose prediction and early clinical evaluation of the efficacy and safety of candidate molecules for tuberculosis remains empirical. Innovative approaches are required to enable effective translation of nonclinical data, providing insight into the selection of rational combinations and optimised clinical trial designs. A PhD fellowship and a post-doctoral research fellow position in translational clinical pharmacology have been created to support the activities of an ambitious consortium including European and global organisations responsible for the development and evaluation of novel candidate molecules for the treatment of tuberculosis. The primary objective of the research programme will be to establish the pharmacokinetic-pharmacodynamic (PKPD) properties of drug candidates progressing into clinical development. Different approaches will be applied to ensure 1) the systematic translation of pharmacokinetic and PKPD concepts from in vitro and in vivo systems to humans and 2) optimisation of clinical study protocols (e.g. first-time-in-human and early bactericidal activity). Required skills: In addition to enthusiasm, motivation and independent thinking, candidates must have working knowledge of pharmacokinetic-pharmacodynamic modelling and simulation, including some advanced statistical principles (nonlinear mixed effects modelling, Bayesian statistics, clinical trial simulations). Strong programming skills in R language, RStudio and NONMEM are essential. Willingness to learn and integrate knowledge from across different therapeutic areas. Behavioural attributes such as teamwork, accurate listening, strategic thinking, along with very good oral and written English language skills will be critical for the successful implementation of the project. PhD fellowship: Candidates with a degree in Medicine, Pharmaceutical Sciences, Biomedical Sciences or Bioengineering are encouraged to apply, especially those with a MSc/MRes thesis or equivalent research experience in PKPD modelling and simulation. Post-doctoral research fellow: Candidates should have completed or obtained a PhD in a relevant discipline (quantitative clinical pharmacology, pharmacometrics, population pharmacokinetics, PKPD modelling, PBPK modelling), and have published their research in a peer reviewed journal. The successful candidates will be co-located with the modelling team at the CNR (Consiglio Nazionale delle Ricerche) in Rome, Italy. Applicants for the PhD fellowship should be nationals of a EU member state. Further details on the application procedures can be obtained by email. Please contact Prof O. Della Pasqua ([email protected]<mailto:[email protected]> or [email protected]<mailto:[email protected]>), including a short CV. Deadline for applications: 17th July 2020. Kind regards, Salvatore D'Agate Clinical Pharmacology & Therapeutics School of Life and Medical Sciences University College London E-mail: s.d'[email protected]