Head of Automated Molecule Synthesis

Job Description

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible to bring life-changing therapies to patients worldwide.

Objective /

Purpose:

The Research Scientific Director, Head of Automated Small Molecule Synthesis, is based in Cambridge, MA, within the R&D — Research division, specifically supporting Takeda’s Digital Discovery & Development Engine. This full-time Director-level role is instrumental in building and leading the automation of small molecule synthesis for Takeda’s Discovery Automation & Robotics (DAR) initiative to implement highly efficient, AI-integrated DMTA (Design–Make–Test–Analyze) cycles toward rapid and reliable small molecule discovery.

The Head of Automated Small Molecule Synthesis leads the strategy, design, and execution of small molecule synthesis using fully automated, robotic platforms to accelerate decision-making across Takeda’s discovery portfolio by quickly and reliably generating compound sets for testing. The role collaborates closely with medicinal chemistry, in‑vitro pharmacology, DMPK, data science/AI/computational chemistry, and automation engineering to ensure seamless integration of compound synthesis with AI‑driven design, and includes integrating retrosynthetic planning, route design, and advanced chemical reaction miniaturization capabilities.

• Define and execute the automation strategy for small‑molecule synthesis, aligning platform capabilities with organizational discovery and development goals and the Lab of the Future roadmap.
  • Prioritize and sequence automation investments in equipment, software, and talent based on scientific impact, throughput gains, and cost‑to‑value ratios.
  • Promote the adoption of digital‑first and automated approaches across the research community as a change champion.
• Establish a closed‑loop DMTA vision by integrating robotics, digital data capture, and AI/ML to boost synthesis throughput, reduce cycle times, and enhance decision quality.
  • Design end‑to‑end automated workflows for reaction scouting, parallel synthesis, scale‑out, and purification (e.g., flash/Prep‑HPLC) to ensure reproducibility and traceability.
  • Standardize method libraries and digital SOPs, covering reaction templates, purification methods, and analytical routines, to enable rapid and consistent deployment across programs.
  • Continuously evaluate and integrate new technologies such as liquid‑handling robotics, continuous flow, microreactors, smart reactors, and generative chemistry tools.
  • Accelerate DMTA cycles through high‑throughput experimentation (HTE), parallel synthesis arrays, flow chemistry, and automated purification integrated with ELN/LIMS and scheduling/orchestration systems for efficient, low‑touch labs.
  • Establish and refine a vision for fully integrated workflows that encompass compound design, purification, QC data capture, analysis, and sample preparation for testing.
  • Define, track, and report KPIs such as workflow efficiency, data accessibility, and cycle time improvements.
  • Encourage method innovation, including novel reaction classes on automation, greener conditions, and continuous processing.
• Drive reliability engineering, preventive maintenance, and improvements
  • Integrate EHS, machine safety, and cybersecurity.
  • Ensure up‑time with scheduled maintenance, spares management, incident handling, and corrective action.
  • Scale workflows from prototype to routine and maintain lab safety and compliance for automated operations.
  • Oversee change control, validation, risk assessment, and conduct drills and post‑mortems.
• Engage externally through contributions to patents, publications, and presentations that highlight platform advancements, and by active participation in consortia and conferences to share knowledge and gain insights to remain at the forefront of best practices.

• Contribute to data governance practices that promote longitudinal learning across Takeda’s discovery portfolio.
• Uphold Takeda’s values of Integrity, Fairness,…