Leonid Gibiansky has more than 25 years of academic and industry experience in areas as diverse as pharmacometrics, PK-PD modeling and simulation, in vitro-in vivo correlations, statistical design and analysis of clinical trials, statistical algorithm design and software development, bioinformatics, and optimization in mathematical physics.

Ekaterina Gibiansky started her pharmaceutical industry career in 1992 in the first-in-industry modeling and simulation group in Sandoz (now Novartis) and subsequently worked in small and large pharmaceutical companies, biotech companies, and consulting companies. She has broad drug development and modeling expertise and the first-hand experience in interactions with clinical teams, advisory boards, and the FDA.

Specific areas of expertise:

    Population PK Modeling:

  • Application of nonlinear mixed effect modeling methods to describe pharmacokinetics of small molecules and biologics, including extensive experience with the target-mediated drug disposition models;
  • Population analyses to support dosing regimens or label claims; to describe pharmacokinetics of special populations (elderly, with renal or hepatic impairment, pediatric) in lieu of or in addition to the special populations studies; to predict exposure for PK-PD analyses;
  • Model-based simulations to design/optimize dosing regimens satisfying specific requirements either for the overall exposure or for the specific shape of the concentration-time profiles.

    Population PK-PD Modeling:

  • PK-PD analyses of exposure-response data using both naïve-pooled and nonlinear mixed effect modeling approaches, and employing empirical, indirect-response and semi-mechanistic physiologic models;
  • Classification and Regression Tree (CART) analyses of exposure-response data; use of CART methodology to describe complex relationships between multiple predictors (characteristics of exposure and continuous or categorical covariates) and a categorical response variable;
  • Model-based PK-PD simulations to select dosing regimens for Phase II - III studies; to predict probability of study success taking into account both efficacy and safety measures; to compare various dosing regimens of an investigational product with the standard of care and placebo;
  • PK-PD analyses of the odd-type data, including modeling of binary response data and ordered categorical data (e.g. pain and sedation scores);
  • PK-PD analysis of the sleep patterns explored using time-to-event models or Poisson models for count data;
  • PK-PD analysis of survival data.

    Model-Based Drug Development of Biologics:

  • Mechanistic population PK and PK-PD analysis of monoclonal antibodies and other biologics with target-mediated drug disposition;
  • Target-Mediated Drug Disposition (TMDD) equations, approximations of the TMDD equations, and analysis of parameter identifiability based on available data;
  • Design and analysis of fist-in-man, Phase 1, Phase 2 and Phase 3 studies for drugs described by the TMDD equations.

    Advanced Model Evaluation Techniques:

  • Implementation of the model evaluation tools such as R scripts to facilitate bootstrap analysis, leverage analysis, objective function profiling, predictive check simulations and posterior predictive check simulations, investigation of the individual objective function distributions;
  • Model evaluation using informative graphics, bootstrap analysis and predictive check simulations for all final and key intermediate models.

    Optimization of Trial Design via Simulations:

  • Development of algorithm and software tools for implementation of clinical trial simulations and visualization of the simulation results;
  • Simulations of clinical trials to optimize study design (sample size, dosing regimens, number and timing of PK and PD samples) and evaluate range of possible study outcomes.

    Pharmacokinetic Design and Analyses of Pediatric Studies:

  • Design and analyses of pediatric trials incorporating previously accumulated data from adult population;
  • Algorithm development and software implementation of adaptive dosing schemes to combine prior knowledge and study-acquired data to provide optimal dosing of pediatric patients.

    Design, Analysis and Simulations of QTc Prolongation Trials.

    Design, Analysis and Simulations of IVIVC Trials:

  • Development of algorithms and software tools for IVIVC modeling (one of inventors and developers of PDx-IVIVC®);
  • Development of a Level A IVIVC.

    Analysis of Immunogenicity (ELISPOT) Data from HIV Vaccine Trials.

    Bayesian Approach that Combines Prior Knowledge and New Data:

  • Markov Chain Monte Carlo approach (MCMC) using PKBUGS and WINBUGS;
  • Use of NONMEM PRIOR subroutine;
  • Simulations with uncertainty implemented via custom-made R scripts.

    Microarray Gene Expression Analyses:

  • Algorithm development for the analysis of microarray data;
  • All aspects of statistical analyses of microarray data, including normalization, clustering algorithms, principal component analysis, class comparison and class prediction.

    Efficiency of the Analyses:

  • Enhanced efficiency due to use of custom-made set of R scripts that facilitate all aspects of data analysis; including data creation, model diagnostics, model evaluation, and preparation of the reports;
  • Model evaluation algorithms are implemented in R scripts that prepare NONMEM control streams and data files for model evaluation runs, execute multiple NONMEM runs taking advantage of multi-processor computer environment, and summarize results of the analysis.

    Modeling and Drug Development Experience in the Variety of Therapeutic Areas, Including:

  • Oncology;
  • Inflammatory and Auto-immune Diseases;
  • Allergy/Respiratory;
  • Cardiovascular;
  • Central and peripheral nervous system;
  • Pain / Analgesia;
  • Infectious Diseases;
  • Metabolic Diseases;
  • Gastroenterology;
  • Musculoskeletal Diseases;
  • Hematology/Coagulation;
  • Ophthalmology;
  • Pediatrics.