Clinical Pharmacology and Pharmacometrics Lead-Contract- (12 Months)

Job description

Contract roles are geared toward independent professionals interested in temporary or project-based work.

Sia Title: Project Consultant (Exempt Contractor)

Project Title: Clinical Pharmacology and Pharmacometrics Lead

Level: Mid-Senior

Project Length: This is a temporary position with an expected duration of 12 months (with potential extension)

Project Hours: 40 hours per week

Location: Remote

The expected compensation for this contract is approximately $205k per year. The exact pay rate will vary depending on a wide array of factors, which may include but are not limited to skills, experience, and location.

Key Responsibilities: One of our premier clients is seeking a Clinical Pharmacology and Pharmacometrics Lead. This contractor will be reporting to the Head of Clinical Pharmacology and Pharmacometrics (CP&P), the Clinical Pharmacology and Pharmacometrics Lead (CP&P Lead) will lead the development of computational approaches to address high priority project development efforts at the Institute. The CP&P Lead will work with project teams to implement and communicate model-informed drug development strategies, to enable and accelerate internal decisions. The CP&P Lead will develop and build a diverse set of approaches to tackling discovery and development questions across the pipeline, including PK and PK-PD, QSP, PBPK, and data science approaches. This contractor will build partnerships with academic and CRO partners to facilitate the development of fit for purpose computational models. The candidate will also collaborate with DMPK, Biostats, Clinical development, discovery, and other functional groups across the organization to deliver on quantitative sciences objectives. This contractor will lead technology initiatives geared towards enabling a robust simulation platform, based on well-calibrated models, constrained by diverse data streams, and advanced approaches in developing virtual patient populations commensurate to simulating clinical scenarios of interest. The candidate will ensure alignment of client values and innovate culture with our talent strategy and programs.  

Responsibilities include but are not limited to:

• Provide strategic leadership in Clinical Pharmacology and Pharmacometrics for both late-stage and early-stage assets, particularly in infectious diseases with focus on Tuberculosis and Malaria. 
• Develop advanced models of drug exposure, exposure-biomarker response, and disease progression to facilitate informed drug development decisions. 
• Collaborate extensively with internal and external stakeholders across various therapeutic areas, offering expertise in modeling, data science, visualization, and data analytics. 
• Act as a Study Director and Clinical PK Scientist for infectious diseases programs. 
• Contribute to regulatory documents related to Clinical Pharmacology, draft sections for clinical development plans, and engage in regulatory interactions. 
• Assess the feasibility of clinical studies, providing critical input on the design and review of clinical protocols. 
• Execute and manage Pharmacometrics and Modeling & Simulation (M&S) plans, interpreting and reporting results to support clinical development milestones. 
• Integrate data from various compounds across development programs to inform strategic portfolio decisions. 
• Represent the department in cross-functional teams, proactively addressing development opportunities. 
• Lead cross-functional teams covering multiple assets, mentor junior Clinical Pharmacology scientists, and promote a culture of scientific excellence and innovation. 
• Handle both small molecules and biologics programs effectively. 
• Support project milestones in discovery and development phases using mathematical modeling and simulation tools, including PK/PK-PD, drug-drug interaction evaluation, PBPK-based dose/exposure scaling, QSP, and formulation/PK assessment. 
• Demonstrate proficiency in Model-Informed Drug Development (MIDD), applying principles to ensure clear and timely communication of modeling results, thereby enhancing decision-making. 
• Utilize advanced data analysis techniques and develop algorithms to detect patterns and associations in data, leveraging diverse datasets to inform models relevant to disease biology.