Purpose
- Lead medicinal chemistry design at speed using AI-enabled molecular design; evaluate generative proposals, apply deep SAR judgment, and direct CRO synthesis to rapidly close DMTA cycles.
Accountabilities / Responsibilities
- Design and optimize drug candidates using SAR, multi-parameter optimization, and ADME-embedded design.
- Critically evaluate AI/ML-generated proposals; integrate computational outputs with medicinal chemistry judgment.
- Partner with Computational Chemistry to close DMTA cycles; help define next design iterations.
- Provide strategic oversight of CRO synthesis programs (compound lists, synthetic routes, quality and delivery timelines).
- Embed selectivity, developability, and IP considerations from the outset.
- Interpret X-ray/cryo-EM structural biology data to guide optimization.
- Stay current on emerging chemical matter and methods; proactively apply new approaches.
- Contribute to AI/ML training datasets via standardized, decision-ready capture of experimental data.
Qualifications & Competencies
- PhD in medicinal or organic chemistry.
- 12β15+ years drug discovery experience; strong lead optimization and candidate nomination track record.
- Expertise in SAR-driven design, ADME optimization, and multi-parameter optimization across programs.
- Experience directing CRO-based chemistry programs (vendor oversight and delivery management).
- Working knowledge of AI/ML design tools; ability to challenge computational outputs.
- Structure-based drug design experience; ability to read proteinβligand structural data.
- Therapeutic area experience across Takeda Research portfolio preferred.
- Thrives in SWAT/rapid-response/focused asset environments; prefers productive urgency over firefighting.