Executive Director, Pharmacometrics Head

Job Description

Objective /

Purpose:

Takeda is a global, values-based, R&D-driven, top 10 biopharmaceutical leader committed to discover and deliver life-transforming treatments, guided by our commitment to patients, our people and the planet.

Our Data and Quantitative Sciences Department (DQS) is made up of more than 700 quantitative scientists who harness the insight of data to speed the development of highly innovative treatments to patients. The scientists (from pharmacometrics, quantitative clinical pharmacology, DMPK&M, Translational biomarkers and bioanalysis (TB&B), Imaging, statistics, programming, outcomes research and epidemiology, patient safety & pharmacovigilance) bring their expertise to our global program teams and reimagine our disciplines.

They work with novel data streams, including real‑world data and digital tools, and apply advanced analytics including artificial intelligence and automation.

As part of DQS and Quantitative Pharmacology and Translational Science (QPTS), the Pharmacometrics team is a therapeutically agnostic team driving, implementing and executing an MIDD strategy for each asset from pre‑FIH through life‑cycle management within the global project team.

Position Objectives
:

• Strategically leads and drives the implementation of model‑informed drug development strategies across the early and late phase clinical portfolio to enable robust dose/regimen recommendations, trial designs, and go‑no‑go decisions through the life‑cycle of our products in collaboration with other functions (e.g. QCP, SQS, GEO).
• Drives the implementation of automation and the use of AI in the discipline of pharmacometrics (E2E) to enable increased capacity, quality and timeline efficiencies. By being integrated into the AI eco‑system, you will be constantly driving the advancement of the field and enabler of data and model‑based decision making across all phases of drug development.
• Is a recognized expert internally and externally in the field of mechanistic modelling and more traditional pharmacometrics with demonstrated experience optimizing clinical drug development. Demonstrated expertise in applying MIDD principles to emerging data sources (RWD, natural history registries, omics data, HER data, etc.) to fully inform development programs.
• Explores and excels in synergistic relationships with experts and leaders in statistics, and other key data science disciplines driving and integrated approach.
• Provides additional portfolio support through program reviews, collaborative decision‑making, infrastructure and best practice initiatives. Experience in applying quantitative approaches to evaluation of probability of technical success, including evaluating business development opportunities.
• Serves as an ambassador of Pharmacometrics, Quantitative Clinical Pharmacology (QCP), QPTS and DQS to the R&D organization and the external scientific community through high‑value participation at scientific meetings and impactful publications.

Accountabilities
:

• Leads and drives a team of in‑house pharmacometricians to deliver all pharmacometrics analyses internally and externally to support the Takeda clinical portfolio and Business development activities.
• Maintains a network and strong relationship with external vendors to support regulatory pharmacometrics analyses.
• Operates at an enterprise level, defines, leads and drives cross therapeutic area and platform level pharmacometrics strategies with the aim of driving the advancement of the Takeda portfolio through various decision‑making milestones. Seeks opportunities to extend MIDD based approaches beyond drug development to decisions impacting product valuation and reimbursement.
• Leads and Drives the evolution of our in‑house modelling platform capabilities with a vision of increased automation, integration of emerging data sources in addition to program‑level clinical trial data, and use of AI with an end‑to‑end mindset and process, in compliance with GxP.
• Works with colleagues in DMPK&M to enable the transition and implementation of mechanistic modelling and thinking (PK‑PD, PBPK‑PD, QSP) into the clinical portfolio as an asset progresses through IND, with…