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Associate Scientific Director, Translational Quantitative Pharmacology

3 weeks ago

Mumbai, Maharashtra, India Merck Specialities Pvt. Ltd. Full time

PURPOSE OF THE ROLE

The Associate Scientific Director, Translational Quantitative Pharmacology (TQP) position in Quantitative Pharmacology (QP) within the broader Clinical Measurement Sciences (CMS) organization is a scientific and cross-functional role, responsible for developing and executing Model Informed Drug Development (MIDD) strategies across the R&D lifecycle.

This position will be responsible for all TQP assignments either executed internally or in collaboration with external TQP related CROs by providing close scientific and technical supervision. The incumbent will be expected to manage multiple projects simultaneously and participate in discussions and presentations.

The role requires the candidate toalso communicate TQP related science and strategies to all interfacing disciplines at the project or non-project levelsand help develop modeling toolboxes to assist  project teams in making quantitatively-driven decisions.

SPECIFIC JOB DESCRIPTION

KEY ACCOUNTABILITIES
  • To be an independent contributor in the field of translational quantitative pharmacology to help advance the fundamental science of the field, to help guide, educate, mentor and contribute to the success of the discipline within the company.
  • To be able to independently develop quantitative mechanism-based PK/PD models that will inform compound progression decisions from lead optimization to clinical proof of concept and beyond for the immunology and oncology pipelines for all modalities of interest.
  • The incumbent will have responsibilities for performing human PK predictions and quantitative DDI predictions, the design and analysis of pre-clinical PK/PD experiments and data to support preclinical development, and translational PK/PD analyses to support FIM dose estimates for all modalities of interest.
  • The incumbent will work to develop models or use commercially available software tools to understand and quantify toxicological signals such as cardiovascular, hepatic, renal, dermal etc to determine the therapeutic index and help guide project decisions
  • To be able to interact with various project team members in a clear and timely manner, understanding the functions of other team members and being able to explain and educate model-based analyses and results to team members from various backgrounds
  • The incumbent candidate will work in a dynamic team with frequent interactions, both within the team and with associated functions, and will be responsible for the development and implementation of innovative modeling and simulation platforms/strategy that ensure that the right drug is administered to the right patient at the right dosage.
  • As a member of project teams and sub-teams, the incumbent will represent QP and present analysis outcomes to cross-functional teams, at department meetings, project review committees and conferences.
  • The candidate will contribute to the preparation and presentation of both internal and external documentation (e.g. Investigator's Brochure, IND, CTD) and program strategy.

STRATEGIC IMPACT

  • Provide technical expertise to promote and deliver on MIDD strategy of the QP organization

COOPERATION

Interfaces with other Departments/Functions:

  • Oncology and Neurology & Immunology Research Units
  • Clinical Pharmacology (CP)
  • Biostatistics
  • Safety Sciences (Toxicology)
  • DMPK
  • Biomarkers
  • Pharmacometrics
  • Data Sciences
  • Project Teams

    External Interfaces:

    • Represent company/ organization in consortia (e.g. IQ working groups) and academic research partnerships.
    • Represent function and department in interactions with contractors
    • Present and publish work in relevant journals and MIDD related conferences.
CANDIDATE'S PROFILE

Qualifications, Experience, Knowledge & Competencies:

EDUCATION/LANGUAGES
  • A minimum of 5 years in industry and/or academia in a relevant background
  • A PhD in Pharmacokinetics, Pharmaceutical Sciences, Biomedical/Chemical Engineering, Applied Mathematics, or a related discipline with a proven track record of applying modeling and simulation approaches to biological problems
  • Fluency in English.
PROFESSIONAL SKILLS & EXPERIENCE
  • Sound knowledge of the theory and principles of Quantitative Systems Pharmacology plus hands-on competence in mathematical modeling of pharmacologic effects with mechanism-based models using relevant software or programming languages (e.g., MATLAB/SimBiology, NONMEM, R, Monolix).
  • Experience in applying translational PK/PD M&S including QSP approaches in research and early clinical development to inform confidence in target/ mechanism, dose/ regimen, and combinations.
  • Knowledge of basic principles of biology and pharmacology at the organismal, cellular and molecular level, preferably in one or more of the following areas: oncology, immuno-oncology, immunology
  • Ability to rapidly assimilate knowledge of complex biology of drug action for novel mechanisms and transform such understanding into multi-scale mathematical models, with requisite mathematical and computational proficiency
  • Experience in applying PBPK modeling and simulation using relevant software (e.g., MATLAB, Simcyp, GastroPlus) is desirable.
  • Experience with toxicological predictions using tools such as DILI Sym/RenaSym for hepatic and renal toxicity respectively is highly desirable
  • Ability to mentor, educate and explain modeling concepts and approaches to colleagues within QP/CMS and the larger organization as well
  • Flexibility and keen pursuit of innovation throughout all phases of the drug discovery and development process
  • A desire to develop and grow by way of taking responsibility and engaging in additional tasks and operations.
  • Ability to work independently and deliver results in a timely manner
  • Publications in conference proceedings and peer-reviewed journals is desirable
  • Excellent communication skills with the ability to translate and summarize outcomes of modeling and simulation analysis as relevant for research and development projects