GSK R&D China job post
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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