Utilisation et développement de techniques pharmacocinétiques avancées afin d’améliorer le développement de molécules pharmaceutiques

Despite the scientific and technological breakthroughs that have graced the last century, the path to bringing a drug to the market is fraught with risk and remains an expensive and time-consuming process.  Significant improvements to this process are needed if patients are to continue to benefit from new therapies.  The objective of this thesis is to demonstrate the use of modeling and simulations in this regard.  It will show how advanced pharmacokinetic (PK) techniques can be used to answer critical questions that arise during the drug development process, and that their use can lead to cost and time savings. The first part of this thesis shows how modeling and simulations, including the development of an innovative model, can be used for the relative bioequivalence assessment of a new sodium ferric gluconate complex intravenous formulation.  Compared to traditional methods, this approach did not make inaccurate assumptions about drug characteristics, nor did it necessitate the enrollment of hundreds of subjects.  Thus, this scientifically robust approach was associated with significant financial savings and economy of time.  Although this research was conducted within the generic drug development, it could also be applied to innovator or biosimilar drug development. The second section illustrates the use of modeling and simulations in the development of an innovative biological therapeutic agent, pegloticase.  This approach allowed us to answer important questions pertaining to the factors influencing pegloticase’s PK and pharmacodynamics (PD), confirming that no special dosing adjustments were required, thus contributing to the official product labeling.  These questions were answered without conducting additional trials or performing supplementary assessments on patients, which resulted in significant cost and time savings.  In the future, such PK/PD models could be used to better understand other biological agents, including their immunogenicity profiles which remain a concern for clinicians. The third part of this thesis focuses on the use of modeling and simulations to select optimal dosing regimens for the Phase 2 study of the novel antibiotic TP-434.  A PK model for TP-434 was developed with Phase 1 data.  This model was continuously updated and confirmed as new Phase 1 data became available, similar to the approach advocated by Sheiner’s learn and confirm paradigm.  Based on simulations performed with this model, and knowledge of PK/PD relationships for another compound, Phase 2 dosing regimens were recommended that were likely to show efficacy in the patient population.  This rational approach to dose selection ensured that patients were not needlessly exposed to the drug, and that efficacy would likely be demonstrated in Phase 2.  Consequently, it was unnecessary to dose additional cohorts or conduct additional trials, which would have lengthened the process and been expensive.  Moreover, this was the first published account of Phase 2 dose regimen selection based solely on simulated Phase 1 data for an antimicrobial drug.   In summary, the research presented in this thesis illustrates how advanced pharmacokinetic techniques like modeling and simulations, including the creation of innovative models, can efficiently answer key drug development questions, leading to significant cost and time savings.

Keyphrases: population modeling, pharmacokinetics, pharmacodynamics, drug development