AVP/ Head, Quantitative Pharmacology & Pharmacometrics - Oncology

Merck•Rahway, NJ

4d•$282,200 - $444,200•Hybrid

About The Position

Our company is seeking a head of Quantitative Pharmacology & Pharmacometrics (QP2) to lead pharmacology strategy for our oncology pipeline. Our QP2 organization uses trial and external data, advanced analytics, model-informed drug development, and deep therapeutic-area expertise to inform the safety, efficacy, dose, schedule, patient-selection, and benefit-risk strategies for the pipeline. The QP2 team integrates clinical pharmacology, pharmacometrics, quantitative systems pharmacology, exposure-response analysis, translational modeling, biomarkers, real-world data, and emerging AI/ML-enabled approaches to support decision-making across discovery, early clinical development, registration, and life-cycle management. The Head of QP2 Oncology will serve as the enterprise point of accountability for QP2 strategy, ensuring quantitative science is used to shape program design, dose and regimen strategy, regulatory interactions, governance recommendations, and portfolio decisions. The leader will provide strategic leadership and scientific oversight, supervise and mentor other scientists, directly shape strategy for priority programs and business-development opportunities, and build a modern quantitative operating model for oncology development.

Requirements

Ph.D. or equivalent degree
At least 15 years of experience in drug development, including at least 5 years in oncology in industry
Educational background in biopharmaceutics, pharmaceutical sciences, pharmacometrics, mathematics, statistics/biostatistics, computational biology/chemistry, chemical/biomedical engineering, or a related field.
Drug development expertise within the oncology therapeutic area, including a record of both internal and external impact in driving model-informed drug development strategies
Experience with multiple modalities such as ADCs, small molecules, TCEs and/or biologics
Track record of publications or presentations in quantitative pharmacology for oncology
Ability to influence regulatory strategies including experience independently authoring and defending regulatory filings for marketing authorization (NDA/MAA) for more than one modality (biologics, ADCs, small molecules, cell therapy)
Demonstrated ability to participate in and to lead an interdisciplinary team, and to oversee the work of other scientists
Experience in performing population PK/PKPD analyses using standard pharmacometric software
Up to date on emerging trends/works in field (peer intelligence, methodology emerging analyses
Scientific understanding of biopharmaceutical and ADME properties of both small molecules and biologics
Proficiency in written and verbal communication, interdisciplinary collaboration, and problem scoping and planning.
Ability to formulate and articulate scientific strategy to support for portfolio decisions
Ability to embed MIDD early in asset strategy, including population PK, PK/PD, exposure-response, dose optimization, simulation-based trial design, model-based meta-analysis, quantitative systems pharmacology, disease-progression modeling, and translational modeling
Ability to recommend and defend dose and regimen decisions supported by integrated evidence packages that address efficacy, safety, tolerability, exposure, biomarkers, patient selection, and regulatory expectations
Has a comprehensive understanding of global regulatory expectations for oncology development for dose and pharmacology; contributing to cross-functional regulatory strategy; reviewing INDs, CSRs, CTDs, NDAs/BLAs/MAAs; and representing QP2 leadership at regulatory interactions
Willingness and experience to apply AI/ML, automation, real-world data, biomarker, translational, and digital data-stream approaches where they improve prediction, accelerate learning, or strengthen development decisions
Ability to serve as a senior representative for QP2 in cross-functional teams, governance discussions, portfolio reviews, and business-development or licensing evaluations
Experienced in team building and maintaining a high-performing, modality-agile organization in close collaboration with discovery oncology and with strong oncology expertise, technical excellence, regulatory credibility, consistent modeling standards, and the ability to influence across functions
Must be able to lead with influence to partner with others to build effect models and datasets,
Must have excellent communication and collaboration skills.
Business Intelligence (BI)
Cellular Therapies
Clinical Development
Clinical Pharmacology
Clinical Reporting
Clinical Research
Clinical Trial Development
Database Design
Data Engineering
Data Modeling
Data Science
Data Visualization
Drug Development
Drug Research
Machine Learning (ML)
Matrix Management
Mechanism of Action
Model Development
Model Driven Design
Oncology
Pharmaceutical Sciences
Pharmacodynamics
Pharmacokinetics
Pharmacology

Nice To Haves

Current Employees apply HERE
Current Contingent Workers apply HERE
US and Puerto Rico Residents Only:
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance
Search Firm Representatives Please Read Carefully
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are place, introductions are position specific. Please, no phone calls or emails.

Responsibilities

Serve as the enterprise point of accountability for QP2 strategy, ensuring quantitative science is used to shape program design, dose and regimen strategy, regulatory interactions, governance recommendations, and portfolio decisions.
Provide strategic leadership and scientific oversight.
Supervise and mentor other scientists.
Directly shape strategy for priority programs and business-development opportunities.
Build a modern quantitative operating model for oncology development.
Influence regulatory strategies including experience independently authoring and defending regulatory filings for marketing authorization (NDA/MAA) for more than one modality (biologics, ADCs, small molecules, cell therapy).
Participate in and lead an interdisciplinary team, and oversee the work of other scientists.
Perform population PK/PKPD analyses using standard pharmacometric software.
Stay up to date on emerging trends/works in field (peer intelligence, methodology emerging analyses).
Formulate and articulate scientific strategy to support for portfolio decisions.
Embed MIDD early in asset strategy, including population PK, PK/PD, exposure-response, dose optimization, simulation-based trial design, model-based meta-analysis, quantitative systems pharmacology, disease-progression modeling, and translational modeling.
Recommend and defend dose and regimen decisions supported by integrated evidence packages that address efficacy, safety, tolerability, exposure, biomarkers, patient selection, and regulatory expectations.
Contribute to cross-functional regulatory strategy; reviewing INDs, CSRs, CTDs, NDAs/BLAs/MAAs; and representing QP2 leadership at regulatory interactions.
Apply AI/ML, automation, real-world data, biomarker, translational, and digital data-stream approaches where they improve prediction, accelerate learning, or strengthen development decisions.
Serve as a senior representative for QP2 in cross-functional teams, governance discussions, portfolio reviews, and business-development or licensing evaluations.
Build and maintain a high-performing, modality-agile organization in close collaboration with discovery oncology and with strong oncology expertise, technical excellence, regulatory credibility, consistent modeling standards, and the ability to influence across functions.
Lead with influence to partner with others to build effect models and datasets.
Apply AI/ML, automation, real-world data, biomarker, translational, and digital data-stream approaches where they improve prediction, accelerate learning, or strengthen development decisions.