Translational Biology Expert

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