Principal Scientist, DMPK

3 days ago

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Cytokinetics

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Description

• Lead and manage in-vivo and in-vitro ADME/PK studies to support drug discovery and early development of small molecules. • Collaborate with medicinal chemists to design drug candidates that avoid metabolic liabilities. • Mentor and motivate the in-house DMPK team, fostering a collaborative and proactive environment. • Provide technical expertise and support in the use of standard PK and PD data analysis software, including Phoenix WinNonlin, NONMEM, and similar tools. • Deep understanding of drug metabolism and how contribute in drug exposure. Preferable hands on experience with hepatocytes MetID. • Evaluate and interpret in vitro and in vivo DMPK data, working with DMPK colleagues to design studies that address key project issues. • Provide scientific expertise on experimental design, data analysis, interpretation, reporting, and leading the PK/PD analysis for the assigned projects. • Perform and lead non-compartmental PK modeling. • Assist in troubleshooting and routine sample analysis of established bioanalytical methods and develop/optimize method of analysis as needed. • Contribute to protocols and reports for IND submissions. • Manage and troubleshoot DMPK activities and instrument/assay issues as they arise.

Requirements

• PhD degree in Pharmacokinetics, Drug Metabolism, or a related life sciences degree with 12+ years of experience in small molecule development; industry experience is highly preferred, but will consider commensurate postdoc experience. • Demonstrated experience designing and conducting experiments in support of DMPK lead optimization and candidate selection activities. • Hands-on experience designing, analyzing and interpreting drug metabolism and PK studies. • Expertise and experience in the following areas: • State of the art bioanalysis by LC/MS/MS and related techniques. • Metabolite identification and reactive metabolite chemistry. • Hands on ADME assays like CYP enzymes inhibition, induction and/or transporters assays. • Principals, theories and approaches to understand pharmacokinetics, drug disposition and drug interactions. • Application of modeling and prediction methods using software packages. • Familiarity with a range of laboratory automation instrumentation including robotic liquid handlers.