Sr Principal Scientist/Principal Scientist

Role Summary

A position is available for an Sr Principal/Principal Scientist in Discovery Toxicology (DT) within the Pharmaceutical Candidate Optimization (PCO) organization at Bristol Meyers Squibb. The incumbent will have responsibilities to identify and address toxicology issues across discovery programs that inform on program advancement, optimization of lead candidates and progression into development. The candidate will have demonstrated experience leveraging computational toxicology tools and big data analytics to generate mechanistic insights and guide decision making in safety assessment. Scientists in DT work with biology, chemistry and biotherapeutics representatives along with integrating across the other disciplines in PCO, namely drug metabolism and pharmacokinetics and pharmaceutics and bioanalytical sciences to ensure that quality drug candidates are advanced into development. The DT scientist is expected to serve as a core discovery team member and to provide actionable insights related to target and compound safety, as well as other critical attributes of drug candidates.

Responsibilities

• Design, execute, interpret and report toxicology studies for evaluating potential toxicity of new drug targets, including new approach methodologies, within drug discovery and communicate these results across multiple disciplines and governance bodies
• Perform multifaceted data analysis using specialized software, including analysis of large data sets and/or use of statistical programming to analyze large biological datasets, including transcriptomics and proteomics, for the investigation of mechanisms of toxicity
• Apply appropriate models and testing strategies to elucidate mechanisms of toxicity, assess human relevance, and design tools for proactive evaluation and prediction of liabilities associated with new drug entities
• Participate in drug discovery teams as a toxicology expert including communication of issues, experimental strategies for resolution and interpretation of results
• Discuss and enable transition of drug candidates into the BMS Development organization
• Contribute to the collective research expertise in DT including laboratory efforts to advance new tools and innovation in mechanistic toxicology research

Qualifications

• PhD with 6+ years of academic / industry research experience in toxicology, or a closely related field
• Experience with computational toxicology approaches (e.g., in silico modeling, predictive toxicology, cheminformatics) and/or large-scale data analysis, including machine learning, and ability to translate findings into actionable insights on safety for drug discovery programs
• Versed in computational methods, with the ability to identify and evaluate emerging computational trends, and make informed recommendations on their adoption to support early toxicology risk assessment strategies
• Ability to generate thorough toxicology target liability assessments for proposed drug discovery targets, including providing suggested approaches and whether proactive follow-up is warranted based on weight of evidence
• Strong communication skills, both verbal and written, are essential. Additionally, the successful candidate is expected to be able to work in a highly collaborative manner with an enterprise mindset and patient-focused values

Preferred Qualifications

• A Ph.D. in toxicology or a closely related field, along with 6+ years of postdoctoral and pharmaceutical industry experience in drug discovery is preferred
• A broad-based knowledge of toxicology, with emphasis on investigating molecular mechanisms of toxicity
• Experience collaborating with computational teams and interfacing with IT to develop innovative approaches, enhancing toxicology prediction capabilities within the organization
• Practical experience with organoids, microphysiological systems or other new approach methodologies
• Experience in systems pharmacology or metabolism-mediated toxicity
• Strong and demonstrable skill set in design and implementation of mechanistic toxicology studies and use of models to support in vivo, ex vivo and in vitro mechanistic or translational toxicology studies. The ability to design in vivo studies across species is also desired