Consult with project team and GMEC leadership to establish quantitative targets for driving optimization, and assigning an Optimization team member to the project team that can execute these goals for accelerated identification of low dose drug candidates
Guide Optimization team members in benchmarking experiments to evaluate models' performance and domain of applicability
Clearly communicate to project teams the rationale behind the selection of specific models and why they are best suited for the task at hand
Lead the development of a cohesive collection of internal models and workflows, to comprehensively address AbbVie's small molecule portfolio needs (suitable models to predict small molecule binding affinities for protein targets, and to predict pharmacological properties (PK parameters, etc.)
Partner closely with the GMEC leadership team to identify and address gaps where computational predictions are needed
Advance scientific expertise within the Optimization team and collaborates with cross-disciplinary teams from CDD and Information Research to advance programs and ensure computational capabilities are best implemented across programs
Proactively demonstrate leadership by providing expert advice and shared knowledge with direct reports, peers, and senior management
Identify and integrate emerging scientific trends from internal and external sources into functional objectives
Present program updates and research strategies to functional and non-functional leaders as well as potential and existing partners
Maintain awareness of emerging literature and science in the field and author scientific disclosures/publications
Maintain scientific presence outside AbbVie with appropriate publications and conference abstract submission highlighting innovative learnings in computational medicinal chemistry
Requirements
Highly organized and self-directed, experience leading multiple complex simultaneous research programs or initiatives
Extensive knowledge and experience in applying data science approaches for medicinal chemistry optimization
Extensive knowledge and experience in modern computational approaches for medicinal chemistry
Excellent written and verbal communication, as well as critical evaluation and data-driven decision making, particularly including an ability to explain complex ideas to non-specialists
Strong analytical and problem-solving skills with demonstrated ability to think critically and creatively, and provide solutions both individually and collaboratively with internal experts
Proven team leadership and management abilities, including experience mentoring, guiding, supervising, and developing scientific personnel with various backgrounds and training levels
Highly collaborative, team-oriented, and considerate of the needs of others
Strong interpersonal skills and ability to collaborate with diverse groups within the organization and external partners
Ability to create an inclusive environment where diverse ideas, viewpoints and backgrounds are valued; willingness and ability to lead inclusively and demonstrate a commitment to listen and consider all points of view
Preferred: has served as Project Lead for a campaign resulting in candidate nomination
Preferred: track record of driving design of early to late-stage discovery programs with inventive contributions to advanced programs
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
The compensation range described below is the range of possible b
Additional Information
Purpose:
This position brings an opportunity to make innovative contributions that will define how AbbVie leverages AI-enabled drug discovery across our small molecule portfolio. Reports to Head of Computational Drug Discovery (CDD) and will lead the computational Lead Optimization team. Will implement and enable collaborative design between members of the Optimization team and Global Medicinal Chemistry (GMEC) teams. Must possess strong expertise in modern medicinal chemistry, including a deep understanding of modern computational and experimental strategies, property-based drug design, and pharmacology needed to develop low-dose small molecule drug candidates. The ideal candidate will have a strong and established background in drug discovery from exploratory through candidate nomination including an established external footprint, and network as well as a proven track record of successfully leading diverse project teams to identify novel drug candidates. Past experience will have included mentorship of early/mid-career scientists in matrixed and/or direct reporting relationships.
Abbvie · North Chicago, IL