Sr. Scientist/Principal Scientist, QSP Modeling

Full Time

Woburn, Massachusetts, United States

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Job description

Scismic is supporting the growth of a biotech company that is developing organ-on-a-chip technology.

We are seeking a highly motivated Scientist - QSP Modeling to develop in vitro-in vivo extrapolation (IVIVE) methods for bioengineered, multi-organ microphysiological systems (MPSs (e.g., liver, gut, BBB, brain)). The role will involve developing human physiologically-based pharmacokinetic (PBPK) models constrained by the in vitro MPS data and in vivo clinical data. Experience with drug-drug interaction (DDI) and transporter-dependent ADME is preferred. The PBPK Modeler will extend existing models and implement new models; collaborate with other computational modelers on parameter estimation and model integration; and participate in cross-functional teams that include biomimetic engineers and experimental biologists conducting the MPS experiments.
  • MS or PhD with some industry experience.
  • Demonstrated expertise in IVIVE and PBPK methods.
  • Technical skills in programming (e.g., Python, MATLAB, R) and presentation (e.g., PowerPoint) are required; experience with GitHub is preferred.
  • The following are desirable: Industry experience with small molecule pharmacokinetics (DMPK); Industry or academic experience with modeling drug-drug-interaction (DDI) and/or transporter-dependent ADME processes; Understanding of ADME processes in liver, gut, BBB, and brain; Experience with relevant databases (e.g., UW DIDB, DrugBank, ChEMBL); Experience with QSP, PK/PD, or pop PK modeling.
  • Able to work well under direction; self-motivated and able to work as a team in a multidisciplinary, fast-paced, dynamic, and results-oriented environment.
  • Development and application of IVIVE methods for DMPK-on-a-chip (e.g., analysis of in vitro MPS data and scaling of in vitro ADME parameters)
  • PBPK model development, calibration, and validation to predict human drug distribution and clearance
  • Parameterization of PBPK models using IVIVE with MPS data
  • Model-guided prediction of human ADME properties and DDI
  • Curation of data needed to support IVIVE and PBPK modeling (e.g., clinical data, parameter values, etc)
  • Collaborate with other computational modelers on model integration
  • Participate in cross-functional teams and client meetings that include occasional presentations to experimentalists
  • Contribute to planning the larger modeling strategies and model-guided suggestions for experimental design

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