Quantitative developer h1.location_city

• Role Overview

We are seeking PhD-level consultants with deep expertise spanning preclinical development through early clinical stages. The ideal candidate has led or meaningfully contributed to programs navigating the path from target validation through first-in-human studies, and can independently drive strategic decisions at key inflection points. Consultants will support a range of high-impact deliverables - from preclinical study strategy and data interpretation through clinical program design and quantitative analysis. * * * Key Areas of Expertise We are looking for depth in one or more of the following areas. Candidates with breadth across multiple domains are especially valued. 1\. Preclinical Study Design & Execution - Designing and executing in vivo studies that link molecular mechanism to disease-relevant phenotypes - Selecting appropriate preclinical systems (in vitro, ex vivo, animal models) with a clear rationale for human translatability - Developing biomarker strategies that span target engagement through clinical response, including practical considerations around sample collection and assay performance - Evaluating formulation and delivery approaches for tissue access across different modalities - Troubleshooting inconclusive or negative preclinical results and recommending next steps 2\. Preclinical Data Interpretation & Decision-Making - Building exposure-activity relationships from in vivo datasets to inform clinical predictions - Evaluating whether preclinical evidence supports drug activity at the intended site of action - Updating mechanistic hypotheses as new data emerges and designing experiments to resolve ambiguity - Assessing early safety observations and developing hypotheses for their biological basis - Evaluating immunogenicity risk and its potential downstream consequences - Supporting portfolio-level decisions (advance, pivot, terminate) grounded in data quality and residual uncertainty 3\. Early Clinical Program Design - Determining safe and pharmacologically relevant starting doses for human studies, including cross-species scaling and its limitations - Designing dose escalation schemes informed by expected pharmacodynamic timecourses and safety margins - Powering early-phase studies appropriately given biological variability and expected effect sizes - Defining patient selection and enrichment strategies using available biomarker and epidemiological data - Selecting endpoints - including when surrogate measures are sufficient vs. when clinical endpoints are required - Planning interim analyses, safety monitoring, and adaptive decision rules 4\. Quantitative Pharmacology & Clinical Modeling - Exposure-response analysis and model-informed dose optimization - Population PK and PK / PD modeling, including covariate identification and impact assessment - Model-based support for dose escalation decisions using accumulating trial data - Longitudinal efficacy modeling, including time-to-effect and trajectory-based analyses - Sensitivity analyses addressing missing data, protocol deviations, and intercurrent events 5\. Clinical Biostatistics - Statistical analysis planning across endpoint types (binary, continuous, time-to-event) - Multiplicity-adjusted hypothesis testing and sample size determination - Subgroup and heterogeneous treatment effect analyses with appropriate false discovery controls - Handling of estimand-related considerations, including missing data frameworks and dropout patterns - Adaptive and interim monitoring design, including futility boundaries and alpha-spending functions * * * Ideal Candidate Profile - PhD, MD, and / or PharmD in pharmacology, pharmaceutical sciences, biostatistics, quantitative biology, or a related field (PharmD, MD also considered) - 5+ years of industry experience in pharma, biotech, or CRO environments - Based in the United States or United Kingdom - Direct experience supporting at least one program from late preclinical stages through IND or into early clinical development - Ability to independently evaluate complex data packages and deliver clear, actionable recommendations - Strong communication skills for technical and non-technical audiences