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The International Society of Anti-Infective Pharmacology is an interdisciplinary scientific society for the study of pharmacokinetics and pharmacodynamics (PK/PD) for the improvement of dosing of anti-infectives. ISAP's efforts are focused on expanding basic and applied knowledge in PK/PD of anti-infectives through the organization of symposia, discussion workshops, and educational workshops with international participation, in connection with major scientific meetings devoted to the treatment of infectious diseases (ASM microbe, ICC, ECCMID, etc.), and other scientific societies with common interests, as well as Regulatory Authorities (FDA, EMA).

Anyone with an interest in PK/PD, dosing, resistance of anti-infectives, and outcome of antimicrobial therapy can apply to become a member of ISAP. We welcome applications from everywhere worldwide.

Job openings

(Active) PhD Position in Poitiers - Cerebral Antibiotic PBPK/PD Optimization and Evaluation of Innovative Regimens against Antibioresistance in ICU patients with cerebral infections

Title

Cerebral Antibiotic PBPK/PD Optimization and Evaluation of Innovative Regimens against Antibioresistance in ICU patients with cerebral infections

Keywords

Cerebro-meningeal infections, ICU, antibiotics, pharmacokinetics, pharmacodynamics, modeling, hollow-fiber infection model

Start of thesis

October 2024

Abstract

Nosocomial cerebro-meningeal infections in intensive care unit (ICU) patients remain a therapeutic challenge due to the limited distribution of antibiotics in the central nervous system (CNS) and increasing bacterial resistance. The objective of the project is to optimize antibiotic exposure in ICU patients with CNS infections by developing new approaches including physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models.

The project is divided in 3 work-packages:

  1. Development of a generic physiologically-based PK model (PBPK) characterizing the CNS distribution of antibiotics with different physicochemical properties
  2. Evaluation of antibiotic efficacy in a dynamic in vitro model (hollow-fiber)
  3. Development of a PBPK/PD model to optimize antibiotic dosing regimens in the treatment of cerebro-meningeal infections

 

Background

Nosocomial cerebro-meningeal infections, such as ventriculitis or meningitis, are serious infections mostly caused by bacteria and often responsible for severe neurological damages, with a high mortality rate (≈30%). However, reaching appropriate concentrations in CNS remains challenging especially because of barriers (blood-brain barrier and blood-cerebrospinal fluid barrier) and cerebrospinal fluid (CSF) turnover. Moreover, antibiotic dosing regimens recommendations for meningitis treatment are currently based on generic pharmacokinetic/pharmacodynamic (PK/PD) targets that have not been specifically defined for the treatment of CNS infections. Therefore, a better understanding of antibiotic CNS distribution and PK/PD relationship is crucial to treat severe life‐threatening CNS infections and to prevent resistance.

Topic description

Through this project, we propose to develop a physiologically-based PK/PD model to optimize the use of antibiotics in ICU patients with cerebro-meningeal infection. This project follows a multi-center clinical trial in ICU patients, during which the CSF distribution of 9 antibiotics with different physicochemical properties was evaluated (https://clinicaltrials.gov/ct2/show/NCT03481569).

The candidate will have to evaluate the efficacy of some of these antibiotics on clinical and reference strains in a dynamic in vitro hollow-fiber infection model. The resulting data will be analyzed using a PK/PD modeling approach to optimize antibiotic dosing regimens.

This thesis will be co-supervised by Dr Alexia Chauzy and Pr Sandrine Marchand, from the "Pharmacology of anti-infectives and antibiotic resistance" UMR INSERM 1070 team in Poitiers.

Methods

The project is divided into 3 work packages (WP). The candidate will be recruited to work on WP2 and 3.

WP1 aims to develop a PBPK model based on plasma and CSF concentrations of 9 antibiotics obtained from ICU patients.

WP2 will consist of reproducing in an in vitro hollow-fibers model the PK profiles of several antibiotics as observed in the LCS of patients. These experiments will allow to assess antibiotic efficacy, through bacterial counts over time, and the emergence of resistance following the administration of different dosing regimens. Antibiotic concentrations will be measured by LC-MS/MS. Resistance mechanisms will be investigated by sequencing and RT-qPCR.

In WP3, hollow-fibers data will be used to develop a PK/PD model. The in vitro PK/PD model will then be linked to the PBPK model to simulate the antimicrobial effect at the infection site for different dosing regimens.

Requirements

The candidate should have a good level of pharmacokinetics and pharmacokinetic/pharmacodynamics modelling, particularly with mixed-effects models.

They should have basic knowledge of the use of R and Nonmem/Monolix software.

They should have basic knowledge in microbiology experiments (MIC measurement of an antibiotic by microdilution, time-kill experiments…).

They should have a good understanding of written scientific English, and may be a French and/or English speaker.

Diploma required: Master 2 or equivalent.

What we offer

The future PhD student will benefit from the expertise in pharmacometrics of Dr Alexia Chauzy, as well as from the scientific and organisational support provided by the U1070 team.

They will take part in international scientific conferences (e.g. PAGE, ECCMID, etc.).

Gross salary: €2,100 per month

Contract duration: 36 months

Application procedure

Provide a cover letter and a CV including your higher education curriculum and professional experience (especially research internships)

Email addresses of at least two referrals (e.g. internship supervisors)

Send to Dr Alexia Chauzy: This email address is being protected from spambots. You need JavaScript enabled to view it.

Euraxess link : https://euraxess.ec.europa.eu/jobs/205138

(Active) PhD Position in Poitiers - Therapeutic drug monitoring of betalactams by using population pharmacokinetics and machine learning

Title

Therapeutic drug monitoring of betalactams by using population pharmacokinetics and machine learning

Keywords

Therapeutic Drug Monitoring, beta-lactam antibiotics, pharmacokinetics, modelling, machine learning, ICU.

Start of thesis

October 2024

Abstract

It is possible to adapt the dosage of antibiotics for ICU patients by carrying out Therapeutic Drug Monitoring (TDM), using an approach based on mathematical models called Model Informed Precision Dosing (MIPD). However, its use in routine hospital practice is not widespread due to a lack of available tools.

In this project, we propose to develop new MIPD approaches for 4 antibiotics used in the ICU.

The project is divided into 4 work packages (WP):

  1. Development of MIPD approaches based either on the selection of a single model or on the simultaneous consideration of all available models (model-averaging).
  2. Development of MIPD approaches using machine learning.
  3. Validation of the developed approaches using drug concentration data from ICU patients from 3 university hospitals.
  4. Implementation of the best models in the free TDMx software.

Background

The treatment of infections in ICU patients requires individualisation of dosage regimens because of the many pathophysiological changes in these patients.

It is possible to adapt the dosage by measuring the patient's plasma concentration at specific times and then adapting the dosage by comparing the measurements with a predefined standard. However, this approach does not allow individual patient characteristics to be taken into account, and is often inapplicable on a routine basis because concentrations are measured outside the predefined times.

Model Informed Precision Dosing (MIPD) uses mathematical models to predict patient concentrations. It becomes possible to use concentrations measured at any time during treatment, and to incorporate all the individual characteristics of the patient. However, their routine use is not widespread due to a lack of available tools.

Topic description

Through this project, we propose to develop new MIPD approaches for 4 antibiotics commonly used in the ICU (amoxicillin, piperacillin, cefotaxime, meropenem).

The candidate will have to develop TDM approaches based (i) on the selection of a single model, (ii) on the simultaneous consideration of the various models available, (iii) on the application of machine learning methods. They will then have to implement the best solutions in the TDMx open-source software.

This thesis will be co-supervised by Pr Nicolas Grégoire, from the "Pharmacology of anti-infectives and antibiotic resistance" UMR INSERM 1070 team in Poitiers, and Pr Jean-Baptiste Woillard, from the "Pharmacometry & Modelling" team in the Pharmacology and Transplantation UMR INSERM 1248 laboratory in Limoges.

Methods

The project is divided into 4 work packages (WP).

WP1 will develop MIPD approaches based either on the selection of a single model or on the simultaneous consideration of all available models (model-averaging). The population pharmacokinetic models as well as the model selection and model-averaging algorithms will be coded in R software.

Work package 2 will consist of developing machine learning (ML) models trained on data produced by Monte Carlo simulation generated from the various population pharmacokinetic models.

In WP3, data on the concentrations of 4 antibiotics in ICU patients from 3 hospitals will be used to validate the models developed. Hybrid algorithms combining individual estimation by population pharmacokinetics and ML may be developed.

In WP4, the best models validated in WP3 will be implemented in the free TDMx software.

Requirements

The candidate should have basic knowledge of the use of R software.

They should have a good level of pharmacokinetics and modelling, particularly with mixed-effects models.

They should have a good understanding of written scientific English, and may be a French and/or English speaker.

Diploma required: Master 2 or equivalent.

What we offer

The future PhD student will benefit from the expertise in pharmacometrics and machine learning of Profs Grégoire and Woillard, as well as from the scientific and organisational support provided by the U1070 and U1248 teams.

They will have the opportunity to develop collaborative project management skills, interfacing with the teams of Pr Jullien (Hôpital Jean Verdier) and Pr Wicha (Univ. Hamburg).

They will take part in international scientific conferences (e.g. PAGE, IATDMCT, etc.).

Gross salary: €2,100 per month

Contract duration: 36 months

Application procedure

Provide a cover letter and a CV including your higher education curriculum and professional experience (especially research internships)

Email addresses of at least two referrals (e.g. internship supervisors)

Send to Pr Nicolas Grégoire and Pr Jean-Baptiste Woillard : This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it. (make sure you send it to both email addresses !)

Euraxess link : https://euraxess.ec.europa.eu/jobs/203480

Postdoc at Bayer facilities (Frankfurt, Germany)

A postdoctoral placement in an industrial environment in Bayer facilities (Frankfurt, Germany) is available starting in 12/2023. 2 mandatory prerequisites to be eligible for the program: a) Australian or New Zealand citizenship, b) PhD thesis in relevant field being submitted latest Oct 2023. Respective applications, consisting of cover letter, curriculum vitae and a scientific dossier covering their synthetic / biochemical topics from Bachelor-, Master-, PhD-work (maximum 5 pages in total), are to be sent to This email address is being protected from spambots. You need JavaScript enabled to view it. by 15th February 2023 in order to allow time for preparation of interviews.

This email address is being protected from spambots. You need JavaScript enabled to view it.
PhD position at Leiden University

Dr. Anne-Grete Märtson is looking for a PhD candidate to join her research group at Leiden University. Her focus is translational research for optimising antiviral therapy. The group uses experimental and computational modelling approaches for optimal dosage design and viral dynamic modelling. For more information see the add, or contact: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

https://www.universiteitleiden.nl/vacatures/2023/q4/14167-phd-candidate-in-antiviral-translational-pharmacology

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