Vacancy for master thesis student

Master thesis on Bayesian optimal design for nonlinear and ordinary differential drug stability kinetic models

 

In defining the stability profile of a novel or candidate pharmaceutical product or it’s ingredient(s) one of the advances that our industry is pressing forward is in the use of accelerated stability studies. In such studies we follow-up the kinetic profile of the candidate compound over a short period of time (usually up to 6 weeks, and at well-designed discrete time points) at a series of higher temperature conditions. Following Arrhenius Law we may then build a thermo-kinetic model to forecast the stability trend over years at lower storage temperatures and draw strategic decisions (e.g. forecasted shelf life, decisions about cold chain management or restriction(s) for long term storage in hot and/or humid climatic regions etc..) . Fitting the models are well understood and 2-step based Ordinary Differential Equation (ODE) models have shown to be very promising for such applications. One remaining open question is how to set an optimal experimental plan (time and temperature points) for such accelerated studies. This problem is related to optimal designs for true nonlinear models (not normal polynomial models) where in essence an approximate expectance of the coefficients are necessary to well set optimal points. Using prior information from previously developed pharmaceutical compounds in a Bayesian framework could be instrumental in solving this question.

For this, with the master thesis student we want to explore the use of Bayesian optimal design for ODE, where we evaluate how we could implement such an algorithm in SAS for 1 and 2-step kinetic ODE models. The steps in this work would be as follows:

 

Step 1: Literature study to gain insight in both accelerated stability kinetic models and Bayesian Optimal designs + draft a time-plan for his work.

Skills to develop:

  • Learn to summarize (tabulate) and distill the key from literature (we will kick-start the candidate).
  • Learn to communicate and interact with both academic and statisticians within Sanofi (we will facilitate).
  • Plan

Step 2: Develop both the ODE and the Bayesian optimal design platform in SAS, keeping in mind that the platform will have to receive true and synthetic datasets (simulations).

Skills to develop:

  • Learn to be proficient in SAS coding (PROC DATA/SQL and SAS MACRO programming).
  • Self-learn how to model ODE’s in SAS.
  • Learn how to program visual outputs using the SAS ODS platform.
  • Create a discipline of listing the required inputs and outputs before the very first line code is written.
  • Create a discipline of early code commenting.

Step 3: Cross-validate the developed Bayesian optimal design and the ODE fitting platforms using pre-generated synthetic datasets. Preferentially this will be done with input from subject matter experts (stability managers), which provide theoretical ‘school’ examples of kinetic profiles for different pharmaceutical platforms such as small (organic) molecules, therapeutic proteins (e.g. monoclonal antibodies) and vaccines.

Skills to develop:

  • Create good version management and archiving ethics. At this point the output is huge and a good tracking of both code updates and statistical output makes or breaks the project. (We will show the candidate how to automatically create new output directories).

Step 4: Present & report 

Skills to develop:

  • Presentation skills: The candidate starts drafting the presentation as early as step 2 as a blueprint of the storyline and concepts will help in engineering SAS MACRO’s with the right output.
  • We trust the candidate has basic scientific reporting skills.

If interested, please send your application to GHENThr@sanofi.com.

 

About Ablynx

Ablynx, a Sanofi company, is a biopharmaceutical company dedicated to creating new antibody-based medicines called Nanobodies® which are making a real difference to society. Ablynx currently has over 400 people working on the development of Nanobodies for the treatment of a wide range of diseases, including inflammation, immuno-oncology and rare diseases.

About Sanofi

Sanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions.

With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.

Sanofi, Empowering Life