COMPANY:
At BioCryst, we share a deep commitment to improving the lives of people living with hereditary angioedema (HAE) and other rare diseases. We leverage our expertise in structure-guided drug design to develop first-in-class or best-in-class oral small-molecule and injectable protein therapeutics, led by the efforts of our team of expert scientists in our Discovery Center of Excellence in Birmingham, Alabama. Our global headquarters is in Durham, North Carolina, we have a regional office in Boston, Massachusetts, and our employees span the globe across sites in multiple countries. We are proud of our culture of engagement and accountability that rewards people for innovative thinking and achievement of key objectives. For more information, please visit our website at www.biocryst.com or follow uson LinkedIn and Instagram.
JOB SUMMARY:
The Sr. Manager, Translational Modeling, leads translational modeling efforts across several programs within the Nonclinical and Translational Sciences department. This role is responsible for developing and executing modeling strategies that support discovery and development, applying mechanistic approaches such as PK, PBPK, PK/PD, and QSP to inform candidate selection and progression and key development decisions. The Sr. Manager, Translational Modeling will also provide oversight and review of the required regulatory documentation in support of IND, NDA, BLA, and other submissions.
The Sr. Manager partners closely with other key groups within BioCryst, such as DMPK, Bioanalytical and Biomarker, Toxicology, Discovery Biology, Medicinal Chemistry, Regulatory, and Clinical Pharmacology and represents Translational Modeling in cross-functional teams.
ESSENTIAL DUTIES & RESPONSIBILITIES:
- Provide expert mathematical modeling to lead development of mechanistic modeling strategy for drug discovery, and early development through clinical with a strong focus on biologics, and protein therapeutics.
- Lead the design, implementation, calibration, validation, and documentation of mechanistic modeling approaches to address MIDD questions across programs.
- Develops PBPK, PK/PD, QSP models, and mechanistic pathway models, ensuring scientific rigor and consistency.
- Drive translational modeling strategies to support discovery and early development decision-making.
- Integrate data from multiple sources (in vitro, in vivo, and emerging datasets) to build robust translational models.
- Collaborate closely with cross-functional stakeholders (DMPK, toxicology, bioanalytical, biology, clinical pharmacology) to ensure alignment and impact of modeling approaches.
- Present modeling strategies, results, and recommendations to cross-functional teams and guide program discussions.
- Guide study design and data generation strategies to maximize translational value.
- Author and review modeling components of regulatory documents (e.g., IND-enabling packages, briefing materials) and support regulatory interactions as needed.
- Promote and implement best practices in modeling workflows and ensure high-quality, reproducible outputs.
- Evaluate and apply emerging methodologies, including AI/ML, to enhance modeling capabilities.
- Coordinate modeling deliverables across assigned programs and ensure timelines and quality expectations are met.
- Contribute to external scientific engagement through publications and conference presentations.
EXPERIENCE & QUALIFICATIONS:
- PhD in systems biology, chemical, mechanical or biomedical engineering, biochemistry, physics, applied mathematics, bioinformatics, or scientific computing.
- Minimum of 5 years of experience in pharma/biotech with significant experience in translational modeling.
- Strong proficiency in scientific computing and programming, with strong preference for Matlab/SimBiology.
- Extensive experience developing and applying mechanism-based mathematical models of biological systems.
- Proven experience with MIDD approaches in particular with PBPK and QSP modeling workflows across multiple programs with a track record of translational modeling impacting program cadence/success.
- Strong understanding of translational science and drug development from discovery through early development and related disciplines (pharmacometrics, pharmacology, pharmacodynamics, toxicology, bioanalytics)
- Demonstrated ability to contribute to and guide program-level decision-making using modeling and simulation approaches.
- Track-record of utilizing M&S to guide experimental design specific to modality-driven target hypotheses
- Strong analytical, problem-solving, and data interpretation skills.
- Excellent written and oral communication skills with the ability to influence cross-functional teams.
PREFERRED QUALIFICATIONS:
- Experience across multiple therapeutic areas, modalities and delivery routes.
- Experience contributing to regulatory submissions (e.g., IND, briefing documents).
- Experience leveraging or evaluating AI/ML approaches in modeling workflows.
- Established scientific publication record.
- Experience working with external partners, vendors, or collaborations.
The statements in this position description are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of responsibilities, duties, and skills required of personnel so classified. The manager may assign additional responsibilities and assignments from time to time.
BioCryst is an equal opportunity employer and is committed to providing equal employment opportunities without regard to age, race, religion, sex, sexual orientation, gender identity, national origin, Veterans status, disability and/or other protected class characteristics. Additionally, BioCryst is committed to achieving its business objectives in compliance with all federal, state and local law.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.
