AIRx, Senior Director, DMPK & Modeling Lead

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Takeda Research is constructing a Lab of Tomorrow built on AI automation new ways of working and talent with the singular vision of delivering differentiated medicines to the clinic at speed and cost. To catalyze these efforts Takeda is creating two complementary units: AI Research Accelerator (AIRx) and Discovery Automation & Robotics (DAR).

AIRx will have a group of a dedicated group of experienced biologic drug hunters with the autonomy of a biotech and the resources of a leading pharmaceutical company. It is designed to incubate the future AI-powered operating models for large molecule discovery and deliver candidates to the clinic at industry leading speed and success rates.

OBJECTIVES/PURPOSE: (3-4 bullets)

Takeda is creating an AI Research Accelerator (AIRx) group consisting of a dedicated group of experienced drug hunters with the autonomy of a biotech and the resources of a leading pharmaceutical company. It is designed to incubate the future AI-powered operating models and deliver candidates to the clinic at industry leading speed and success rates.

DMPK is a critical component of each AIRx team. As the AIRx DMPK & Modeling Lead you will establish the quantitative and mechanistic foundation that drives portfolio decisions integrating ADME PK PBPK/QSP and AIenabled modeling to guide programs from target hypothesis to clinical hypothesis. You will operate within a highly externalized AIpowered discovery model defining how modeling is used to enable rapid highconfidence decision making.

Profile:

The AIRx DMPK & Modeling Lead will combine extensive scientific and strategic expertise in DMPK and modeling with the agility to thrive in an externalized AI-powered operating model leveraging DMPK and modeling depth and pragmatism to direct and integrate quantitative data and decisions at speed. This will include knowledge and experience of DMPK requirements for diverse modalities (e.g. small molecules biotherapeutics).

Responsibilities include directing CRO partners with precision and accountability to generate high-quality interpretable data that feeds into AI-powered DMTA cycles and connecting experimental biology to translational strategy and clinical outcomes.

ACCOUNTABILITIES:

• Portfoliolevel impact across AIRx programs
• Quantitative Strategy & Decision Leadership: Owns the DMPK PK/PD and modeling strategy across the AIRx portfolio. Ensure all programs have: Robust human PK and dose projections Clear exposure target engagement efficacy/safety hypotheses Quantitative line of sight to clinical success. Drive model-informed decision making (MIDD) for target modality and candidate progression. Establish biomarker and modeling frameworks that link preclinical data to clinical outcomes.
• AIEnabled Modeling & DMTA Integration: Embed DMPK & modeling into AIenabled DMTA cycles ensuring rapid iteration and learning. Integrate: In vitro / in vivo ADME data PK PBPK and mechanistic (QSP) models AI/ML-driven predictions and simulations. Ensure modeling outputs are decision-ready interpretable and fit-for-purpose.
• Design and oversee CRO-based DMPK and modeling activities with speed and rigor. Ensure: High-quality reproducible and interpretable data packages Alignment between CRO outputs and modeling need Build scalable workflows for externalized AI-enabled DMPK operations.
• Challenge scientific assumptions across the team; ensure DMPK integrity and mechanistic depth underpin all program decisions
• Represent DMPK perspectives at Takeda governance forums; contribute to IND-enabling packages.

Technical/Functional (Line) Expertise

• Strong expertise in: ADME PK PK/PD and application/ interpretation of mechanistic modeling in the pharmaceutical or biotech industry from early discovery to development.

EDUCATION BEHAVIOURAL COMPETENCIES AND SKILLS:

• Expected: PhD degree in a relevant scientific discipline with 12-15 years industry experience in pharmaceutical DMPK and modeling
• Proven contributions to IND filings; experience supporting IND-enabling DMPK packages
• Track record designing and managing externalized CRO DMPK programs; ability to scope oversee and critically interpret study data
• Ability to connect DMPK to clinical hypothesis and translational strategy
• AI/ML data integration experience; comfortable working with large multi-source datasets
• Experience in at least one therapeutic area represented across the Takeda Research portfolio
• Excellent cross-functional collaboration skills; able to operate effectively in a lean fast-paced team

ADDITIONAL INFORMATION

• The position will be based in Cambridge MA. This position is currently classified as hybrid by Takedas Hybrid and Remote Work policy

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors including the qualifications of the individual applicant for the position years of relevant experience specific and unique skills level of education attained certifications or other professional licenses held and the location in which the applicant lives and/or from which they will be performing the actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical dental vision insurance a 401(k) plan and company match short-term and long-term disability coverage basic life insurance a tuition reimbursement program paid volunteer time off company holidays and well-being benefits among others. U.S. based employees are also eligible to receive per calendar year up to 80 hours of sick time and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

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