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Takeda

Director, Head of Biopharmaceutics Predictive Modeling - Oral Drug Product Boston, MA Category: Pharmaceutical Sciences

Takeda · Boston, Massachusetts, United States

Full-timeOn-sitePosted 13 October 2026
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Job description

Director, Head of Biopharmaceutics Predictive Modeling - Oral Drug Product Boston, Massachusetts Apply Now Job ID R0189625 Category Pharmaceutical Sciences Subcategory Research & Development Business Unit Research & Development Job Type Full time By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use . I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description ACCOUNTABILITIES ● Provides strategic and operational leadership for the Biopharmaceutics Predictive Modeling function, with a focus on mechanistic biopharmaceutics, PBPK/PBBM, and model-informed drug development to support oral drug product development and portfolio objectives. ● Builds and develops a high-performing team of biopharmaceutics and modeling scientists who work across the Oral Drug Product organization to integrate mechanistic understanding, computational modeling, and experimental data into development strategies. ● Leads the development and implementation of biopharmaceutics and predictive modeling strategies to inform API and formulation selection, oral dosage form design, dissolution performance, dose selection, and clinical development decisions across the product lifecycle. ● Directs the application of physiologically based pharmacokinetic (PBPK), physiologically based biopharmaceutics modeling (PBBM), mechanistic absorption modeling, and dissolution–absorption modeling to predict drug product performance, systemic exposure, and clinical pharmacokinetic outcomes. ● Oversees the integration of API physicochemical properties, solubility, permeability, dissolution, precipitation, supersaturation, gastrointestinal physiology, and formulation characteristics to understand and predict the impact of drug product attributes on absorption and bioavailability. ● Provides scientific and organizational leadership in model-informed drug development, including PBPK/PBBM, mechanistic oral absorption, food-effect prediction, relative bioavailability, exposure prediction, in vitro–in vivo correlation (IVIVC), and in vitro–in vivo relationship (IVIVR) development. ● Works closely with the formulation scientists and project teams to evaluate formulation and process changes, support clinical bridging, assess biopharmaceutics risk, and inform decisions related to formulation selection, dose and dosage form optimization, and product lifecycle management. ● Partners with key CMC stakeholders (formulation development, analytical sciences, clinical pharmacology, drug metabolism and pharmacokinetics (DMPK), regulatory) to integrate modeling and biopharmaceutics assessments into development plans and program decisions. ● Directs the preparation and scientific justification of biopharmaceutics and modeling contributions to regulatory submissions and health authority interactions, including model qualification, verification, sensitivity analysis, uncertainty assessment, and model credibility. ● Establishes functional strategy, scientific standards, best practices, and governance for biopharmaceutics modeling and simulation across oral drug product development, ensuring fit-for-purpose model application and appropriate integration of experimental and clinical evidence. ● Builds organizational capability through training, talent development, resource planning, external partnerships, and continuous advancement of mechanistic modeling and biopharmaceutics capabilities. ● Drives innovation in predictive biopharmaceutics to improve the probability of clinical success, reduce development uncertainty, accelerate formulation and clinical decisions, and enable more efficient development of oral drug products. DIMENSIONS AND ASPECTS ● Deep expertise in oral biopharmaceutics, pharmaceutical development, mechanistic absorption, PBPK/PBBM, and model-informed drug development, with a demonstrated record of applying these approaches to pharmaceutical development decisions. ● Strong understanding of the relationship between API physicochemical properties, formulation design, dissolution and solubilization, gastrointestinal physiology, absorption, and systemic exposure. ● Demonstrated expertise in developing, applying, interpreting, and evaluating mechanistic models to predict oral drug product performance and clinical pharmacokinetics, including scenarios involving poorly soluble compounds, modified-release drug products, food effects, and formulation changes. ● Ability to integrate in vitro dissolution and biopharmaceutics data, preclinical and clinical pharmacokinetics, and mechanistic model outputs to inform formulation strategy, clinical study design, and regulatory decisions. ● Proven ability to lead programs and cross-functional initiatives within a complex global development organization, aligning scientific priorities, resources, timelines, and portfolio objectives. Leadership ● Hires, develops, trains, and mentors a high-performing team of biopharmaceutics predictive modeling scientists responsible for advancing the Pharmaceutical Sciences in silico modeling strategy for Oral Drug Product Development. ● Establishes a clear functional vision centered on mechanistic biopharmaceutics, PBPK/PBBM, oral absorption, and prediction of clinical drug product performance. ● Influences scientific and development strategy through recognized expertise, effective cross-functional partnerships, and the ability to translate complex modeling outputs into actionable development recommendations. ● Mobilizes and leads cross-functional teams across multiple programs, driving alignment, accountability, scientific rigor, and disciplined execution. ● Champions inclusive leadership, talent development, succession planning, and continuous capability building. Decision-Making and Autonomy ● Operates with high autonomy and accountability in defining modeling strategies, scientific plans, resource requirements, and external partnerships within established governance. ● Makes and communicates risk-based recommendations on formulation selection, biopharmaceutics risk, clinical bridging, food-effect assessment, dose and dosage form optimization, and development strategy. ● Uses model-informed assessments to evaluate competing development options, identify critical uncertainties, prioritize experiments, and guide decisions affecting scope, budget, timeline, and product quality. ● Establishes appropriate standards for model applicability, verification, qualification, sensitivity analysis, and uncertainty assessment, ensuring that conclusions are proportionate to the available evidence and intended regulatory use. Interaction ● Partners with Oral Drug Product function heads and teams, Pharmaceutical Sciences, analytical development, clinical pharmacology, DMPK, regulatory affairs, quality, and other CMC stakeholders to develop integrated, model-informed strategies. ● Works closely with clinical pharmacology and DMPK teams to integrate preclinical and clinical PK data, characterize absorption and exposure, and refine mechanistic predictions. ● Leads technical interactions with external modeling experts, consultants, software providers, academic groups, and development partners. ● Supports external collaborations and contracting in partnership with procurement, legal, and relevant governance functions. Innovation ● Evaluates and implements emerging PBPK/PBBM methods, mechanistic absorption approaches, and model-informed development strategies relevant to oral drug products. ● Advances the use of predictive biopharmaceutics to support early formulation selection, reduce unnecessary experimentation, optimize clinical study design, and improve development efficiency. ● Promotes integration of experimental, preclinical, clinical, and modeling evidence to address complex development questions and improve t

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