Job Responsibilities / Department Description
Sanofi is seeking a highly motivated Senior Scientist and to join the growing Bioanalytical Development team in the Gene Therapy program at the Sanofi Genomic Medicines unit in Waltham, MA. The candidate is expected to have a strong scientific background in cell-based assays to assess potency and impurities and in PCR methods to detect transgene expression and the presence of impurities. This role requires skills and interest in performing method development, management of critical reagents and early phase GMP testing. The successful candidate will lead the design and development of cell-based potency assays and cell-based impurity assays using ELISA, ddPCR, and PCR-based methods to support preclinical and early phase clinical lot release and stability testing for viral and non-viral gene therapy products. In addition, the senior scientist will participate in technical transfers to CROs/CMOs and in method life cycle management.
Define scientific approaches and analysis methods for gene therapy potency and impurity bioassays.
Lead the development, qualification and early phase -testing of cell-based assays and molecular assays in a regulated GMP environment.
Lead troubleshooting initiatives ensuring efficiency of approach and define workstreams required for the generation of complex reagents.
Participate in the execution of lot release and stability tests for drug substance and drug product.
Efficiently prepare GMP data packages. Lead investigations into deviations and CAPA resolutions as appropriate.
Ensure timely completion and delivery of analytical results and associated documentation (data packets, technical reports, SOPs, etc.) to support early phase product development. Review regulatory submission documents.
Provide guidance and mentorship to junior staff to support their career growth.
Lead the establishment of a critical reagents program within the bioanalytical group.
PhD. in Cell Biology, Biochemistry, or related discipline with 4 years of relevant experience working in the biotechnology/pharmaceutical industry, or Master’s Degree in Biochemistry or related disipline and at least 8 years of relevant experience or Bachelor’s Degree and at least 10 years of relevant experience.
Proven experience in developing and qualifying/validating analytical methods to support product development and regulatory filings for viral and/or non-viral gene therapy products.
Strong background in bioassay and molecular methods (e.g. potency, infectious titer, ligand binding and residual assays), excellent method troubleshooting skills, as well as appropriate experience in developing data analysis approaches (e.g. 4 parameter fit, linear fit, parallelism and equivalence assessment and LOD assessments with respect to regulatory guidance).
Working experience in a GMP environment and ability to adhere to all appropriate GMP standards (e.g. invalid result investigations, deviations, and CAPAs) will be considered advantageous.
Good understanding of regulatory requirements for early and late-stage development of Gene Therapy products including compendial requirements as well as requirements associated with the assessment of critical quality attributes, control strategies, stability, and comparability as outlined in ICH Guidelines and FDA guidance documents.
Excellent verbal and written communication skills and experience working cross-functionally.
Demonstrated ability to work in a matrixed environment and interact productively with associates, scientists and management at various levels, both locally and internationally
Understanding of MOA for different gene therapy therapeutics and ability to initiate the cell-based assay with no or minimum guidance.
Familiarity with software packages to analyze dose-responses, statistical analysis and parallelism or equivalence testing.
Experience with flow cytometry, molecular biology (RT-PCR, qPCR, ddPCR), ELISA, FRET, cell-based platforms and/or effector function assays (ADCC, CDC, FcgR binding) to characterize Gene Therapy products.
General understanding of statistical principles supporting method performance and robustness assessments as well as Design of Experiment approaches used for method development/optimization.
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