Job Description:
The Computational Modeling and Sciences (CMS) group in GSK R&D China is seeking 
a Mechanistic PBPK/PD Modeler to integrate ADME data into PBPK models that can 
be linked with systems pharmacology to understand drug safety and efficacy. 
Applicants should have a desire to drive model based drug design and 
development in support of projects.
This role involves developing PBPK/QSP/QST models to influence critical 
decisions in drug discovery and development, from target selection to the 
identification of the best modality and delivery route to engage the target to 
the optimal dose selection including inputs into clinical trial design.
Working in a dynamic and multidisciplinary environment the successful candidate 
will develop, calibrate and use complex QSP/QST models connected with PBPK 
models linking drug disposition and target biology with clinical outcomes for 
various diseases.
This role will address the relationships between drug properties, its 
disposition and the pharmacological and toxicological response translating 
between in-vitro, in-vivo preclinical species and human. This involves the 
integration and interpretation of data from many sources to help drive project 
decisions.
Responsibilities:

*   Responsible for providing appropriate modeling support to Discovery 
Performance Units (DPU)/Therapeutic Areas (TA)/Platform Technology and Science 
(PTS) line and peer review modeling work from colleagues as appropriate, 
insuring high quality standards for the modeling work

*   Further develop unique expert modeling skills. Provide expert modeling 
consultancy, training and support to others in your unique areas of expertise

*   Develop and execute a modeling strategy for each DPU/TA/PTS line assigned 
insuring availability of appropriate modeling capability

*   Build, expand and refine the modeling capabilities and platforms

*   Promote and increase the reputation of the modeling both internally within 
R&D and externally including regulatory agencies

*   Aid the interpretation of the data we generate and integrate it with that 
of clinical and pre-clinical partners to help project decisions

*   Use modeling as a thinking tool to help generate better hypothesis and 
design better, model informed experiments

*   Provide consultancy and training resource to increase the overall kinetic 
thinking and modeling  capability of staff both within the department and 
outside in PTS and R&D

*   Exceptional collaborative behaviours to build and maintain relationships 
with both R&D customers as well as the wider modeling community in GSK
Basic Qualifications:

*   Advanced degree in chemical, mechanical or biomedical engineering, 
biochemistry, physics, applied mathematics, bioinformatics, scientific 
computing or related field

*   A minimum of 5 years  experience of applying mechanism based mathematical 
modeling techniques in the pharmaceutical industry (e.g. PBPK or QSP or QST 
modeling)

*   Core competency in numerical analysis focusing on differential equations

*   Knowledge and understanding of drug delivery, absorption, distribution and 
metabolism, pharmacology and toxicology, PK/PD modeling, physiological based 
modeling and translational sciences

*   Experience of building, solving and using mathematical models to integrate 
available data and applying these to answer practical questions that have a 
positive impact on projects

*   Scientific computing and programming particularly Matlab and SimBiology

*   Experience of using at least one physiological based modeling software 
package e.g. GastroPlus or Simcyp

*   Evidence of identifying, developing, and applying innovative solutions to 
scientific and technological problems faced in systems modeling

*   Evidence of strong critical thinking skills, troubleshooting and problem 
solving skills

*   Demonstrated collaborative behaviors both within the computational 
community and with the modeling customers in pharma

*   Excellent written and oral communication skills and the ability to interact 
effectively with scientists in other disciplines with a positive, collegial, 
collaborative attitude

*   Successfully leading in a matrix environment, working across 
functions/disciplines

*   Evidence of developing self and others
Preferred Qualifications:

*   PhD degree strongly preferred

*   Experience in one of: finite element, computational fluid dynamics, 
numerical optimization, agent based modeling, stochastic differential 
equations, advanced image analysis

*   Knowledge and understanding of systems biology, data analysis, image 
analysis and computational sciences

Hiring Manager:
[email protected]
15821883201
Hongkang Mei


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